http://www.mysocialnetwork.net/blog/481/y7/ en Copyright 2007 Mon, 11 Dec 2006 15:25:30 -0500 http://www.sixapart.com/movabletype/ http://blogs.law.harvard.edu/tech/rss It all ties together... An analysis of social network structures In this assignment I have divided the analysis into 4 main topics and for the majority of the topics, analyzed the data in the 18-22 group and 33+ group as well as analyzing the data by sex (male/female). (1) Social Support & Network Density :: Social Support :: Social support in this study is measured by the size of the core discussion networks - the number of people listed that the respondent discusses “important matters” with. Network density, which is defined by Monge and Contractor (2003) as the “ratio of the number of actual links to the number of possible links in the network” (33), is measured by how well the respondent’s ties know one another (strangers vs. know each other vs. especially close). I found that with the 18-22 group, there were an average of 5.4 ties for males and 5.86 for females. This is a surprisingly high number considering that McPherson et. al (2006) found in 2004 that the typical American had 2.08 discussion partners. This may be related to several factors: (1) the fact that all the respondents I surveyed currently attend college and would skew the results in comparison to the GSS survey participant pool (2) probing them to reconsider if they had less than 6 ties may have had an effect and (3) social pressure & design of the survey (see limitations section). In the 33+ group, I found results much closer to those found by McPherson et. al. The women averaged around 3 ties and the males around 2.75 ties. This may be due to the fact that with age, comes a “shrinkage of the friendship network…the older people are, the fewer friends and fewer friendship contacts they report” (Kalmijn, 247). Limitations of my sample may have also skewed these results, and I will discuss this in further detail in the limitations section. :: Network Density :: In the 18-22 age group it seems that the women have more densely connected networks. The majority of the ties were listed to “know each other”, followed by “especially close” and then “strangers”. There was a surprising lack of connectivity in the male group and 4/5 respondents had listed the majority of their close ties as “strangers”, which goes against Granovetter’s theory of the forbidden triad. Granovetter believes that if A and B are strongly linked and A has a strong tie to some friend C, the tie between C-B should not be absent (1363). This could be caused by the discrepancy in the percentage of kin found in both groups- men had a significantly higher proportion of kin than females did in my sample as will be explained in the section below. In a college setting, parents rarely have the opportunity to meet our friends, which would have made many of these ties “strangers”. In the 33+ group I found that the networks were much more densely connected. Majority of the ties either “know each other” or are “especially close”. One interesting difference is that the people listed in the men’s networks were more likely to be “especially close” than with female respondents. This is partially explained by Kalmijn’s study (2003) in which he found that “women have more separate contacts than men and that they less often share friends with their spouse than men” (247). :: Kin in our social networks :: McPherson et. al also found that with this remarkable drop in size of core discussion networks, also came “ a shift away from ties formed in neighborhood and community contexts and towards conversations with close kin” (353). This can be seen in both age groups but there was a significant difference in gender. In the 18-22 age group, all of the males listed at least 1 kin member in their core discussion network and had an average of 40% of kin in their overall core discussion networks. For females, only 3 listed at least 1 kin member in their core discussion network and females had an average of 12% of kin in their overall core discussion networks. This is interesting because according to McPherson et. al’s study (2006), they saw that “women still have significantly more kin in their networks than men do, but they no longer have fewer non-kin confidants than men”(362). While the latter part of the findings was true in my case, it is interesting that there would be such a huge discrepancy in the data. In fact, McPherson noted that “the kin-dominated nature of women’s networks is one of the staples of the social capital literature” (362). I think that this can be partially attributed a cultural/ethnic factor because the respondants I surveyed were unfortunately all of Asian ethnicity. In Asian culture, it is not common for the male children to be closer to their parents, which may have skewed the data in that way. In the 33+ group, there is a significantly higher proportion of kin in their social networks (males 79%, females 89%).This is again supported by Kalmijn’s findings that with age, social networks shrink and become more kin-based. (2) Network Size :: Network Size :: The position generator is used to measure network size and also access to social capital. Position generators, first proposed by Lin and associated used a sample of ordered structural positions salient in a society and asked respondents to indicate contacts that they knew on a first-name basis. Based on the Lin et. al (2001) article, I ranked the jobs from 2 (lowest, laborer) to 30 (highest, judge) and from these responses it was possible to construct measures of (1) Extensity of heterogeneity of accessibility to different positions (total number of positions accessed; (2) Upper reachability of accessed social capital (status of the highest position accessed) and (3) Range of accessibility of different hierarchical positions (distance between the highest and lowest accessed positions. Firstly, the 33+ age group had significantly more access to social capital/resources than the younger group As we can see from the tables, the older respondents on average have higher levels of extensity, upper reachability and also range. Lin et. al found that “white males tended to access more position, there was no significant difference between males and females in terms of upper reachability (the highest prestige score) or the range of scores” (67). Although I did not survey white males, the gender discrepancy was also quite significant in my study. Males overall ranked higher in terms of all three categories with the exception of upper reachability in the 33+ age group. Two of the women I surveyed- my mother and my aunt are very much “connectors” like Lois Weisberg (Gladwell) and may have contributed to this upper reachability difference. (3) Community Scholars like Wellman argue that “community is much less likely now to be locally based and locally observed” (15). Interestingly, I found that that may not necessarily be as clear-cut with the data I collected. In the 18-22 group I found the following results: The majority of the people that the respondents discuss important matters with actually either live in their neighborhood (33.8%) or house (16.2%) as well as live in the same country (29.4%). Also, all of the kin that were listed did not live in the same neighborhood, city or state, but were in the same country. There were also significant gender differences in the distance of their core discussion networks. For females, their discussion partners tend to live in the same building/dorm (66.7%) neighborhood (65.2%) or city (62.5%). For males, they tended to live farther away with 65% only living in the same country. I’m not sure why this is the case, but it is probably attributed to the fact that in my sample, many of the male respondents listed more kin, and therefore would result in a higher percentage of data in the “same country” category. (4) Homophily :: Age :: Age and education levels are pretty homophilious across the board. What I did find interesting was the gender homophily. :: Gender :: Firstly, in the 18-22 age group, it seems that there were slightly more female to male interactions (35.3%) and in the 33+ age group, there are significantly more males seeking female discussion partners (40%). In fact, for males aged 33+, 72.7% are more likely to turn to a female than a male. That seems to be reflected in the general trend as well. This could be interpreted to reflect Kalmijn’s findings that show “women are socially less dependent on the marriage than men, a pattern which is directly the opposite of dependencies in the economic domain” (247) and thus men are more likely to turn to their spouses (hence the higher M-F %). Limitations & Conclusions :: Measurement :: Sociometric questioning does have some limitations in its validity. Firstly, Zwijze-Koning & Jong (2005) noted that “an important issue is the truthfulness of respondents’ self-reports…for reasons of social desirability they may report different network relationships than they actually have” (434). I think that in our Social Network Survey this was definitely the case and also because of the structure of the survey itself. Having a table with 6 rows made a lot of people write in more discussion partners than I think they would’ve had it not been presented that way. There also may have been some social pressure to “give the impression that they have a broader network or play a more central role than they do in reality” (Zwijze-Koning & Jong, 435). Also, the probe question may have pressured them into writing more names than they would’ve had I not asked them the “anyone else” question. In addition, Zwijze-Koning & Jong also noted that forgetfulness may be a concern and that they “may also forget to mention certain exchange relations they have in an organization” (435). It may also be because of status/proximity of these contacts- it is highly possible that many in the 18-22 group listed their college friends because of the proximity/geography factor. :: Analysis :: I think that some of the measurements that were left out of our particular survey that could’ve been interesting are (1) race and (2) where the respondent lives. Firstly, I think that racial/cultural factors did play a part in the results I got and also my comparison with many of the studies, which usually surveyed upper-upper/middle class white people. It would have been interesting to see if race does account for certain trends or if there is as much racial homophily we think there is. Secondly, Fischer had some interesting points in his articles from week 5 that address the issue of urbanity/urbanization and our social relations. Since some of the people I surveyed do not live in the city, it would have been interesting to see if that did play a role. For example, does living in a suburb account for the fact that you may know your local dry cleaner, truck driver, etc? It would be an interesting point of comparison. :: Data Collection & Interpretation :: I found that I had a lot of trouble with the data collection process. Firstly, many people I feel interpreted the question “discussed matters important to you” differently. I know for a fact that one respondent thought that meant work-related issues and not personal issues, and some felt it was financial issues. As an objective data collector, I could not tell them necessarily what “important matters” constituted, but their interpretation may have skewed the results. There was also a significant amount of error in filling out the survey. Many people left out boxes or filled it out wrong and I had to get them to read it over again, or in some cases chase them down to correct their mistakes. One unforeseen mistake was misinterpreting the distance question- 2 respondents checked “same house” for their kin members when I know for a fact they don’t live with them now. Also, I know that my analysis is limited because I only managed to collect 3 females and 4 males over 33. I tried to compensate by surveying more in the 18-22 range, but that will skew my data significantly. In addition, because of my workload this week I was really unable to survey strangers. I completed the majority of my 33+ age group surveys with respondents on the phone. I had emailed them a copy of the survey beforehand and asked them to have a copy in front of them while I guided them through it and recorded their answers. I understand that this wasn’t really the point, but it was the only way I realistically could get the data. Lastly, I feel that my data was skewed because I didn’t get a very wide range of people to fill it out. In the 18-22 age range I got many of my friends to fill it out and many of their networks are overlapping and very similar. In the 33+ range I surveyed 1 friend and the rest were family/extended family. These factors may have led to a more homophilious and less representative data set. :: Conclusions & Final Thoughts :: It was really interesting to see everything tie together with this final project. I regret not being able to put more time into it and the same goes for the work over the course of the semester. Having to work part-time and juggle a full class load and extracurriculars really proved to be too much for me to handle and I would’ve liked to have been able to devote more time to the material learned in this class. I hope you don’t take that as a sign of disinterest/boredom, because I truly feel that there was a lot of value in the readings, our discussion and also the learning style (blogs and such). Conducting our own research certainly proved to be an effective way of having to synthesize the course materials. I think that with the Social Network Survey I was able to see the trends we found in the reading apply to “real life”- the social networks around me. At the same time I realized that are so many limitations to data collection (type of data, how you collect it, etc.) that every study is only able to show a slice of the bigger picture. ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/12/it_all_ties_together.html http://www.mysocialnetwork.net/blog/481/y7/2006/12/it_all_ties_together.html Assignment #4 COMM 481 Mon, 11 Dec 2006 15:25:30 -0500 The first article, “Social Isolation and the Underclass” looks at the relationship between poverty and social isolation, the role that neighborhoods play in social isolation and also the gender differences in the structure of social isolation. Fernandez & Harris assess social isolation and also Wilson’s theory of the underclass. They have defined “social isolation” as a lack of personal contact between members of the underclass and mainstream society, isolation from institutions/lack of participation in local organizations and also marginalization from the social networks that extend beyond the local community. They obtained some pretty interesting results: Firstly, Fernandez & Harris found that not only are women more likely than men to be poor, but women have more constricted networks than non-poor women. In addition, “there are no class differences among males, but poverty serves to isolate females” (273). Could some of these effects be attributed to the disproportionate number of single-mother families in impoverished neighborhoods. According to the article, the survey respondents were asked to name up to 3 non-kin, non-spouse friends and up to 6 people they could “depend…for everyday favors” and up to 6 people they could turn to for help in a major crisis. I think that one issue with their measurement is that they measured “percentage of kin in support network” solely based on the relationships found in “daily” and “crisis” support networks. What are some of the issues with this measurement? Finally, Fernandez and Harris also conclude that “ if the experience of poverty is more isolating in the context of very poor neighborhoods, then an argument can be made for policies that redistribute the poor among nonpoor neighborhoods.” This made me think back to Gladwell’s article on social networks and his statement that “poverty is not deprivation. It is isolation”. (6) In the article, he quoted Lois Weinberg saying: "I don't believe poor kids can advance in any way by being lumped together with other poor kids (10). She started a program where poor kids would be able to mix with middle class kids in their afterschool extracurricular activities and it was a great success. This links to the next article about social resources and mobility outcomes. Marsden and Hurlbert discuss the effects of social network resources & social capital on job changes. They looked at several measures: occupational prestige, wages, industrial sector, firm size, possession of authority and closeness of supervision. It is interesting that they found that tie strength had a significant negative effect on status and an insignificant positive effective on prestige. But perhaps one of the most significant findings was that the industrial sector of the contact has a substantial effect on the respondent’s current job. This supports the homophily principle and the idea that employers have core contacts. The debate on weak vs. strong tie continues with this article. Marsden & Hurlbert found that the use of weak ties is associated with experience and firm size and that “the finding for experience is consistent with a network-building argument that suggests that useful contacts are accumulated over time” (1051). But at the same time, contacts reached by weak ties tend to be of higher prestige than those reached via strong ones (1052). It is interesting to note that in this situation, the strength of the tie is not a very strong predictor. The authors conclude that the strongest effects on access to social resources reflects homophily patterns: higher prestige persons reach higher prestige contacts and people tend to find contacts in the industrial sector within which they are employed. Is this advice useful if we are looking for a job as a college grad? If we are looking to work in another industry? http://www.mysocialnetwork.net/blog/481/y7/2006/12/social_isolation_resources.html http://www.mysocialnetwork.net/blog/481/y7/2006/12/social_isolation_resources.html Week 18 Readings COMM 481 Tue, 05 Dec 2006 09:19:33 -0500 The Small World Study @ UPenn In a class of 18 students, 10 of the folders were successfully delivered to their target people. A completion rate of 55.6% is very high in comparison to previous small world studies and to the 27% completion rate found in the Stevenson et. al small world class project. While this is not too surprising, the discrepancy between the success rates of the two targets, is quite alarming: 80% of the completed chains were to Susan Yoon and only 20% to Antonio Polley. This made me ask the question: what factors are likely to make a folder successfully reach its target? What factors helped a folder delivery succeed? :::::Tie Strength?::::: Firstly, I looked at tie strength. Granovetter argues that more people can be reached through weak ties: “whatever is to be diffused can reach a larger number of people, and traverse greater social distance (i.e. path length), when passed through weak ties rather than strong” (1366). Burt would agree and suggest that we hand it off to a weak tie because “the strong relations between people in the network means that each person knows what the other people know, so they will discover the same opportunities at the same time” (74). He adds that “there is no theoretical reason to expect a strong correlation between the strength of a relationship and the information benefits it provides” (85). To me personally, it seemed very logical, despite what Granovetter and Burt would say, to pass it on to a strong tie. Wellman & Wortley also suggested that “strong ties provide broader support than weaker active ties…many strongly tied network members enjoy helping each other” (566-567). In my Assignment #1 Part 1 blog posting, I said that this “relationship of trust will increase the likelihood of my folder reaching the target because I trust her and can depend on her to participate and complete the task in a timely manner”. Does trust matter? Burt states that “trust is critical precisely because competition is imperfect…the matter comes down to a question of interpersonal debt. If I do for her, will she for me? There is no general answer. The answer likes in the match between specific people” (72). This seems to be the case with the small world study. In my experience, passing it to a strong tie worked to my benefit, but from the class results, it seems that strong ties aren’t always reliable and trustworthy, and that tie strength may not be a decisive factor in a folder’s chain completion. SUSAN’S GROUP *Successful Chains* Very Weak/Weak: 2/8 (25%) Moderate: 2/8 (25%) Strong/Very Strong: 4/8 (50%) *Unsuccessful Chains* Very Weak/Weak: 1/2 (50%) Moderate: 0/2 Strong/Very Strong: 1/2 (50%) ANTONIO’s GROUP *Successful Chains* Very Weak/Weak: 1/6 (20%) Moderate: 3/6 (50%) Strong/Very Strong: 2/6 (30%) *Unsuccessful Chains* N/A :::::Gender Homophily?::::: Secondly, I looked at gender. In my Part 1 blog posting, I hypothesized that “June’s gender increases the probability of it reaching the target” and this was consistent with Milgram’s findings that “participants were three times as likely to send the folder to someone of the same sex as to someone of the opposite sex” (65) and Stevenson et al’s hypothesis that small world folders are more likely to be passed to members of the same sex (hypothesis #4). In Susan’s group, all the starters were female, attempting to reach a female target. 84.6% of the completed transfers were to females and 87.5% of the final transfers were female to female. While this group of results supports the gender hypothesis, it was slightly more varied in Antonio’s group. With this group the percentage of transfers to the same gender was 55.6%, but it is notable that of the completed chains (n=2), 100% 100% of the final transfers shared gender. In Milgram’s SW study: Female -->Female : 56/145 (38.6%) Male --> Male: 58/145 (40%) Female --> Male: 18/145 (12.4%) Male --> Female: 13/145 (9.0%) Both our class and Milgram’s results may highlight two important observations: 1) It is probably more difficult to complete a chain when the “starter” person is of a different gender than that of the target person. 2) Successful chain completion is probably more likely when the final transfer shares the same gender as the target person. There are some limitations to this since the male starter in Antonio’s group was also unsuccessful in complete the chain to the male target. This may just go to show that gender is not in itself a formula to the success of the chain completion. Lastly, although it was not examined in our small world study, I think that racial homophily may also play a small role. Stevenson et al argues that “SW studies have shown that those who are culturally and racially similar are more likely to be linked” (3). McPherson et. al’s 2001 article on homophily found that “homophily in race and ethnicity creates the strongest divides in our personal environments” (415). In fact, in Milgram & Korte’s study on acquaintance networks between racial groups, they found that the target race was a significant factor in determining the success of acquaintance chain points. Their results showed that 80% of the incomplete African American target chains never crossed the racial barrier. Although many of the successful chains were not racially homophilious, as I mentioned in the previous assignment, June’s race is an advantage because she is probably more likely to be aware of the communication structures of Asians on Penn’s campus. :::::Affiliation/School & History at Penn?::::: One of the most interesting connections of the small world study is of the affiliation/school (student/faculty; SAS, GSE, etc.) and history (years at Penn) and the success of the chain completion. Affiliation/School Stevenson et.al hypothesized that small world folders were likely to be passed within rather than between classes and occupational groups in a university because “small world studies in the organizational setting have shown that barriers between professional groups exist and these barriers make it difficult for SW folders to cross these barriers” (2). I initially also had this hypothesis: Susan’s “structural position poses a challenge. Why? Susan is an assistant professor at the Graduate School of Education. Not many undergraduate students take classes there or in the building. This limits the number of people I know who could potentially be in contact with her. The student population and class size at the Graduate School of Education is definitely smaller than the other schools, which also is an obstacle.” (Part 1 Blog). The way I overcame that barrier by passing it onto June, who is a student advisor/faculty member. She was accessible to the students yet her position as the director of the Pan Asian American Community House gives her access and familiarity with many different resources and people. However, with Susan’s group I found that many other starters had also passed it onto someone of a higher occupation/class, so it seems that it may not be too difficult here at Penn to break that barrier. In fact, 5/10 (50% ) of the starters were able to get it to a faculty/staff member right away and 4/5 (80%) of those chains were successful. Crossing that barrier proved to be necessary because as Stevenson et al hypothesized: “small world folders will converge on faculty and staff before reaching their target”. In fact, for all the completed chains, a faculty member was the final alter. Stevenson et al attributes this to the fact that students recognize that faculty members are “repositories of knowledge about the organization” (3) Is this linked with success of chain completion? Stevenson et. al found that “completed chains involve participants with higher occupational prestige” (2). As I mentioned in my previous assignment, June, like Lois Weisberg, is a “connector” with many weak ties just steps away (Gladwell). June knows both students, faculty and staff, and according to Milgram, “the larger and more varied the pool of acquaintances a participant can draw on, the greater the opportunity of choosing an effective link” (107). In addition, Milgram also found in his original study that occupational similarity was a factor that increased the chances of having the folder delivered to the target. In my case, June and Susan also have similar educational interests- they both have P.H.D’s in education/psychology/type fields, which may have been a reason for their acquaintanceship. With Antonio’s group, the results were quite similar. The 2 successful chains were both passed onto someone in the Wistar Institute which was the last or second-to-last alter before reaching the target, Antonio. But yet at the same time, folder G16 manage to get the folder to someone in the school of medicine & the Wistar institute, but was unable to reach the target, which was quite an interesting result. History (Years at Penn) In Stevenson et al’s study, “students exhibited a hierarchy of communication with upper-class students never passing folders to lower-class students” (6), but in our studies that was not the case. In Susan’s group, there were really only a couple instances of that happening and most of the time it was from a senior to a junior or a sophomore. With Antonio’s group, both successful cases were passed on from a 5th year to a sophomore. Stevenson et al’s rationale was that the respondents were likely to pass the folders to someone they knew and these connections “are likely to develop as an individual spends more time in the organization” (2). I don’t think that age, or the duration you have been at a place necessarily make you more connected or more aware of the resources available. Freshmen may be at a disadvantage, but with folder G23, it was passed through 2 freshmen and one new GSE student and then reached the target. On the flip side, G16’s chain had 4, 9, 5, 21 years of experience respectively and the folder failed to reach the target person. Conclusion: Is it a small world (Upenn) after all? On average, it took between 3.25 links (Susan’s group) and 4.5 links (Antonio’s group) between the starter and the target for completed chains, which is significantly fewer than Milgram’s average of 6 but quite a bit higher than Stevenson et. al’s average of 1.25 links. It is important to note that both our study and Stevenson et. al’s study was only done in a University setting: “small world studies in organizations have shown, given the relatively clear boundaries in organizations, the number of intermediaries between a starter and target is smaller, and more chains are likely to successfully reach their target in SW studies in organizations as compared to larger society”. (4) It is interesting that for incomplete chains the links were 1 (Susan’s group) and 2.33 (Antonio’s group), suggesting that the majority of the unsuccessful cases died out pretty early in the process. Perhaps this goes to show that in many cases, finding a suitable 2nd alter is very important to the success of the chain completion. While no ONE factor is crucial to the success of the chain completion, there are certainly attributes that would help increase the probability of success such as trust, gender/racial homophily and occupational prestige. However, it is not surprising that so many cases failed. According to Kilworth et. al, only “a level of accuracy of around 50% is present. This inaccuracy results in small world chains which are 40-50% longer than would be the case if ‘correct’ choices had been consistently made by network members” (94). Some of the other limitations are illustrated in the Zwijze-Konning & Jong article on data collection. One of the most obvious disadvantages to this study is that response rates are sometimes low and that this may lead to a “systematic bias” in the data (442). With the Small UPenn study, failed folders and missing information gaps within the data made it difficult to analyze the already small sample we have. In addition, although Zwijze-Konning & Jong argue that the small-world technique can help identify gatekeepers and “sociometric stars”, I don’t think our study achieved that. However, I do agree with Stevenson et al that “a small world study can be a useful tool for studying network connections between individuals in organization” (2). It has been an interesting research project and really ties in a lot of the readings and theories we have studied in class so far. ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/11/the_small_university_study_upenn.html http://www.mysocialnetwork.net/blog/481/y7/2006/11/the_small_university_study_upenn.html Assignment #1: Part 3 Thu, 30 Nov 2006 12:38:09 -0500 Cohen & Brissette’s article “Social Integration and Health: The Case of the Common Cold” looks at social integration, social network diversity and one’s susceptibility to the cold virus. Cohen and Brisette base social integration on “the numbers and types of social relationships, the extent of participation in social activities, or the perception of being an integrated member of the community” (2). Cohen and Brissette set out to investigate this by doing a study on the spread of the common cold in Pittsburg. They found that “social isolation constituted a major risk factor for the development of illness” (9) and while isolation accounted for the most of the effect, “the diversity of the network is more important than the number of network members and its association with colds is independent of the number of members” (8). They did not find, however that chronic stress had any effect on illness susceptibility (8). This article seems to tie into Burt’s structural hole argument that we are better off with lots of weak, rather than strong ties, since it is the diversity, not the strength/quality of the tie that determines one’s susceptibility to illness. Though the article was written in 2000, the measure of social network diversity only included face-to-face and phone interactions. Q: What, if any, effects would the internet have on this study? One explanation for the results of this study is that social diversity might be mediated by the function of the endocrine and immune systems (9). The other explanation is that a more diversified social network would broaden the subject to more social controls and engage in improved health practices (10). Are these results dependent on more place-based, physical communities? Would the rise of virtual communities then also affect our health? Dicken’s et. al’s article “Lack of Close Confidant, but not Depression, Predicts Further Cardiac Events After Myocardial Infraction” looks at the role of depression and the lack of social support before myocardial infarction (MI) in the UK. They had 2 main findings: (1) They failed to find an association between depression before MI and death rates and (2) Having a close confidant approximately halved the risk of having a subsequent cardiac event. Unlike Cohen & Brissette’s findings that the number and diversity of ties leads to better health, Dickens et. al’s study focused on the degree of intimacy of close relationships rather than the number of social contacts: “the close relationships may be protective of health and may promote recovery from depression” (521). While they did not determine the mechanism, some of they hypotheses included separation/association of lack of a close confidant, childhood separation & the rosk of ischaemic heart disease, or even a delay in seeking treatment if they are without a close confidant (521). This is a concern since a lot of the literature we have covered points to decreasing social capital, social networks and “close friends” we discuss important matters with. McPherson & Smith-Lovin discussed the dissolution of our core discussion networks and the loss of our broad scope of support. Not only is it affecting our social lives, but scholars like Dickens et. al prove that it is also affecting our health. However, this is not to say that this study doesn’t have its flaws. Firstly, it is hard to generalize the results of this study because it deals with a very small and select sample- elderly patients suffering from MI. Bearman et. al’s article “Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks” looks at how “local preferences shape the macrostructures in which individuals are embedded and hence affect both the potential for disease diffusion and the determinants of individual risk” (45). The authors do this by examining the partnership patterns and network structure in a sample of students at a Midwest Highschool, dubbed “Jefferson High”, hoping to measure the key structural characteristics of a largely complete romantic and sexual network through which STDs may diffuse (45). Their study showed some pretty surprising results. In contrast to popular myths, no “core group” of highly sexually active adolescents emerged but rather, were indirectly linked in long chains. Additionally, the number of sex partners proved to be less important than the position in a sexual network. However, as we have discovered through studies/articles like Kilworth’s “Estimating the Size of Personal Networks” in 1990, we still have little idea of the mean size of an informant’s network and little knowledge about our own social networks. The authors discuss 4 models of infection, but found that the spanning tree most closely corresponded to the situation at “Jefferson HS”. A spanning tree is a “long chain of interconnections that stretches across a population, like rural phone wires running from a long trunk line to individual houses” (51). It is characterized by a graph with few cycles, low redundancy, and very sparse overall density, and most frequently observed in large and complex generalized exchange systems. According to Bearman et. al, the network at “Jefferson”, “closely approximates a chainlike spanning tree” (52). The size of the large component of connected nodes is identified as the worst-case scenario for potential disease diffusion within the population. While there were many individuals at the end of the small branches in the large component with only one partner, “their risk for contracting an STD may be greater than an individual with multiple partners who is embedded in a smaller, disjoint component. Consequently, STD risk is not simply a matter of number of partners” (60). While in theory, spanning trees are the most efficient structures for diffusion (since the absence of redundant lines maximizes reach at lowest density), the good news is that their efficiency is counteracted by their fragility- spanning trees are highly susceptible to breaks in transmission (79). Thus, from this study, we can see that the most effective strategy for reducing STDs or other disease diffusion rests on creating these structural breaks. According to the authors, it is not so much which actors are reached for an intervention, but that some are. This is because “given the dynamic tendency for unconnected dyads and triads to attach to the main component, the structure is equally sensitive to a break at any site in the graph” (80). While this seems to be useful in future social and health policy, it also highlights the how having “an accurate sense of the real structure of a network matters for the effectiveness of an intervention” (80). Is it feasible to investigate all the network structures of schools and change the social policies towards STD education accordingly? Does this only apply to the school system? How reliable is our present system of assessing network structures? Regardless of those issues, however, it is useful to know that sending out a broad, widespread message, including those on the periphery, may be equally, if not more, effective than targeting high-risk groups only. ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/11/social_networks_our_health.html http://www.mysocialnetwork.net/blog/481/y7/2006/11/social_networks_our_health.html Week 13 Readings COMM 481 Tue, 28 Nov 2006 09:49:57 -0500 Assignment #3: New Media Note: As per my conversation with Professor Hampton, I have opted to revise/add to my answer and will have this marked a day late. Data Summary: - Total number of interactions: 194 - Number of people I interacted with: 71 - Total interactions using: 1. Cell Phone: 47 (24%) 2. SMS: 2 (1%) 3. Cell & SMS: 2 (1%) 4. Email: 118 (61%) 5. Instant Messenger: 24 (12%) 6. Skype or VOIP: 0 (0%) 7. Facebook: 1 (0.5%) :::::Question 1::::: (A) Interacted with most often: Michelle L.: Michelle is a junior in the College from Texas and also a member of my sorority, alpha Kappa Delta Phi Sorority Inc. We work very closely in our organization and also used to live together. I would classify Michelle as a “moderate tie”. Linda Z.: Linda is a junior in Wharton from Seattle and also a member of my sorority, alpha Kappa Delta Phi Sorority Inc. As President, I work closely with Linda, who is our Vice President of External Affairs. In addition, we are on the Asian Pacific American Heritage Week (APAHW) board together. As Coordinating Chair, I worked with Linda on fundraising efforts for the week. I would classify Linda as a “moderate tie”. Jean H.: Jean is a senior in the College from New Jersey. I have known her for around 2 years, but only became close friends with her in the last year. As leaders in the Asian Pacific American (APA) community here at Penn, we are present at different meetings and events together. She is also a member of the APAHW board and we are both members of the Oracle Senior Honor Society. Jing C.: Jing is a junior in Wharton from California and also a member of my sorority, alpha Kappa Delta Phi Sorority Inc. We are both involved in the APA community here at Penn, so we often attend events together. June C.: June is the Director at the Pan Asian American Community House at Penn. As well as being someone to talk to, she is also the advisor for the APAHW and helps out all the APA groups on campus. (B) Interacted most in that communication medium: 1. Cell Phone Michelle L.: (See Above) Jing C.: (See Above) Alan O.: Father Luis C.: Luis is a senior in the College from Florida. We met through our involvement in the APA community here at Penn but we also spend a lot of time together socially/outside of our extracurricular activities. I would consider him a “moderate” tie. Aileen L.: Aileen is a junior in Wharton and is on my executive board for the APAHW. We’ve worked together on APAHW for 2 years now, but only know each other in this context. I would consider Aileen a “weak” tie. 2. SMS Angel: Junior in Wharton, member of my sorority. Marianne: Junior in College, member of my sorority and also an executive board member for APAHW. Shirley: Junior in College, member of my sorority. 3. Email I think that the use of listservs is interesting here, because the majority of my emails sent are to multiple users. As leaders of the two groups, Asian Pacific American Heritage Week and alpha Kappa Delta Phi, I need to constantly keep in touch with my members and the use of listservs is usually the most efficient way around that. 4. Instant Messenger There wasn’t a significant difference in the people I communicated with via Instant messaging. The two people who had slightly more interactions were: Jean H.: (see above) Linda Z.: (see above) 5. Skype or VOIP none 6. Facebook Johnny Wang: Johnny graduated last year and is now working in New York. He is a friend and former board member of APAHW. :::::Question 2::::: (A) Tie Strength & Medium of Communication Close ties: Cell Phone (45%), Email (30%) and Facebook (25%). Moderate ties: Email (42%), Cell Phone (34%), Instant Messenger (19%) Weak ties: Email (71%), Cell Phone (21%), Instant Messenger (7%), Facebook (1%) I found that the with close ties, I communicated via cell phone, email and facebook use and with moderate ties I used email, cell phone and IM. From this, we can see that with close/moderate ties, several forms of new media are used. According to Wellman in “Physical Place and Cyber Place: The Rise of Personalized Networking”, “it is clear that most people communicate with their friends, relatives, neighbors, and workmates by any means available and necessary, online, and offline. The stronger the tie, the more media used” (243). This does seem to be supported in the findings because with my close ties, there is a pretty even distribution of 3 different kinds of media, suggesting that all 3 mediums are used to maintain these relationships. While a wide variety of different communications mediums were used with weak ties, the majority of the communication was communicated through email. (B) Type of Support Exchanged & Medium of Communication Gave Extracurricular Information -G7: Email (72%), Cell (25%), SMS (2%), IM (1%). Received Extracurricular Information -R7: Email (70%), Cell (15%), IM (10%), SMS (5%). Gave & Received Companionship- G/R7: IM (59%), Cell (30%), Email (11%). * Percentage based on the total number of interactions Firstly and not surprisingly, when giving OR receiving extracurricular information, Email seemed to be the predominant medium of communication. This may be explained by what Baym et. al stated about how the “internet was rated worse for maintaining relationships, and better for getting schoolwork done and exchanging information.” (304) It is interesting that the difference between the extracurricular information given or received is the use of SMS and IM. I am curious to know why others tend to use IM and SMS more to contact someone about information regarding an extracurricular activity. As Baym et. al stated, “we also found that chatrooms, message boards, and newsgroups were not serving as venues for meaningful social interaction in this population.” (302) This can possibly be explained by (1) Location (if they are at home, are they more likely to use IM?) or even (2) “Real time” interaction (IM like face-to-face interaction is synchronous) or even (3) Free SMS services (does this make people more likely to SMS rather than call?) It is interesting that the majority of my new media use is for giving/passing on extracurricular information (44%) followed by giving/reciving companionship (14%) and receiving extracurricular information (11%). Baym et al note that “it has been often argued that the internet is far better for the accomplishments of tasks than social interaction. However it was slightly more likely that internet interactions were identified as social rather than face-to-face conversations and telephone calls” (314). However, the “accomplishments of tasks” aspect to new media seems to still hold true in my case. Secondly, what I found interesting was that the majority of companionship I gave AND received was conducted via IM or Cell. I find this surprising because I don’t usually go on AIM very much, but then again this study is limited to studying new media use alone and not relative to “traditional” means of communication, such as face-to-face. I very much agree with Wellman in that “in-person contact is still-and will continueto be= the preferred means of communication…all but hermits will share tangible, intimate, domestic experiences in a most physical way”(247). (C) Age/Gender, Multiplexity and Medium of Communication Age College Aged (18-22), Older (23+), Younger (18-20): 58%. Gender Female: 78%, Male: 22% Age & Gender College Aged Female (F, 18-22): 64%, Older Female (F, 23+): 13%. College Aged Male (M, 18-22): 13%, Older Male (M, 23+): 10% * Percentage based on the total number of interactions It was not surprising to find out that my network is very homophilious in terms of age and gender. 78% of my total interactions that week were with females and 64% of my total interactions were with college-aged females. McPherson, Lovin and Cook’s article, “Birds of a Feather: Homophily in Social Networks” argues that networks are homogeneous with regard to many socioeconomic, behavioral and interpersonal characteristics because of the homophily principle. Homophily is the “principle that a contact between similar people occurs at a higher rate than among dissimilar people” (p.410, McPherson et. al) and that similarity breeds connection. In addition, “cross-gender friendships are more restricted in their topics of conversation” (Mesch and Talmud, 143) This brings up an interesting point about multiplexity. Multiplexity “is used to describe the different dimensions a relationship contains and is high when individuals are connected in multiple activities and discussions”. I noticed two significant trends: 1. Referring back to Q1, the majority of the people I interacted with the most using new media, were multiplex relationships 2. Also, looking at my data, I found that many of my college-age female relationships are more multiplex than college-age male relationships. As Mesch & Talmud stated, “background similarity or homophily increases the likelihood of multiplexity” (139). Percentage of Multiplex relationships in my college aged friends: College-aged females: 41% multiplex, 58% not multiplex College-aged males: 0% multiplex, 100% not multiplex *Note: I defined “multiplex” as having more than one relationship category listed off in the diary. :::::Question 3::::: Location of Interaction Home: 91 (46.9%) Classroom: 72 (37%) Work: 11 (5.7%) Street: 14 (7.2%) Other: 6 (3.1%) Interactions & Tie Strength Home: Close (9.7%), Moderate (48.6%), Not Close (41.7%) Classroom: Close (14.3%), Moderate (44.4%), Not Close (41.3%) Work*: Close (18.2%), Moderate (27.3), Not Close (54.5%) Street: Close (14.3%), Moderate (42.8%), Not Close (42.8%) Other: Close (0%), Moderate (16.7%), Not Close (83.3%) * For work, I only included personal interactions and not interactions on behalf of my company. Interactions & Relationship *Please click on thumbnail The data I collected doesn’t show a strong relationship between the location or public/private and a specific characteristic of the tie or person. However, I must say that new media is moving away from being placed-based to being person-based. New media is becoming increasingly mobile and portable. Here at school, I spend most of my nights doing work in a classroom (usually Huntsman). Having a cell phone, a laptop and wireless internet allows me the flexibility to send out my daily blast of emails from anywhere on campus. Hampton would say that this “asynchronous communication facilitates temporal flexibility” (226).However, the physical space is still important. According to Wellman, “many ties operate, in both cyberspace and physical space, using whatever means of communication is convenient and appropriate at the moment…physical space and cyberspace interpenetrate as people actively surf their networks online and offline” (248). :::::Discussion::::: Overall, I was pretty surprised at the results of the diary. The people I consider my “close ties” don’t all appear on the top 5 list in Q1. One of the major limitations to this study, is the absence of a duration recording. For example, I might speak to an acquaintance for several times that week, it may only be for a few minutes each time, whereas I might speak to my parents once a week, but for a longer time. Diary research also has its own limitations. According to the Zwijze-Koning and De Jong article, one of the major issues is reliability and it’s time restriction. Because of the high burden, a diary-based study would have to be short, and also they mention that there may be a seasonal variation: “what is gained by preciseness of the data collected may be lost in the study’s representativeness” (437). One of the issues our class faced was the fact that the study fell on the week of and after fall break, which may not have been a “typical” week at school. Validity can be an issue for diary research also, although I feel that in my case I was very diligent about recording each interaction on paper and on my laptop immediately after they occurred. And lastly, there is the issue of self-report and reporting socially desirable answers. During the course of the study, I was very aware of how many interactions I got per day and whether this week really was representative of my social network and media use. However, there doesn’t seem to be a solution to this problem with the diary based studies. ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/11/3_new_media_use_1.html http://www.mysocialnetwork.net/blog/481/y7/2006/11/3_new_media_use_1.html Assignment #3 COMM 481 Thu, 16 Nov 2006 13:16:32 -0500 Is this a contradiction in Wellman’s article? If so, can we say that while community interactions have moved inside the private home, that it has also pushed us away from those inside our homes? Marks’ article “Pentagon sets its sights on social networking websites” illustrates some of the consequences of personal information on the web. I know that personally I don’t like to put much of my information online- just because as many people have warned, employers, family, and new friends can so easily “google” you. The question I had is, does the quality of relationships online depend on the quantity of information you have online when it comes to developing new friendships? If profiles and such are our way of introducing ourselves to a community, how much is too much? This leads me to think about the privacy settings that are now popping up online. Especially with facebook, we can limit our profiles and our information not only to people in our school, but also to our friends. Ellison et. al looks at the role of Facebook in social networks and looks at how Facebook can be used to create various forms of social capital. Are we cutting ourselves off from certain types of social capital or resources by not participating in facebook, or even limiting our profiles on facebook? Kleinberg & Lawrence’s article “The Structure of the Web” looks at just that. They state that the web does not have an engineered architecture, but rather, is decentralized with billions of pages created by individual. Research has shown, however, that there is a great deal of self-organization and that the web contains a “large, strongly connected core in which every page can reach every other by a path of hyperlinks” (p.1849), much like the “small world” situation. Like the Google technology & hierarchy we discussed in class, the authors state that there is a mechanism of preferential attachment- that “the network grows by the sequential arrival of new nodes and the probability that an existing node gains a link is proportional to the number of links it currently has”, or as they have stated, a “rich-get-richer” process. One issue today, that Kleinberg et al touch upon is the process/technology of favoring highly linked sites. While we might say that this particular site is popular because lots of people search for it & click on it, at the same time, many of the newer, smaller, lesser known, niche sites get lost in this huge virtual network. When people search for a term, the same sites are coming up, and are we then just all getting the same information? I know that when I google something I rarely click past the 5th page. What are some of the implications of this self-organization & mechanism of preferential attachment? ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/11/online_infomation_the_dangers.html http://www.mysocialnetwork.net/blog/481/y7/2006/11/online_infomation_the_dangers.html Week 10 Readings COMM 481 Tue, 07 Nov 2006 09:57:48 -0500 Internet & Community (Is Internet good for creating new forms of community? Or will it destroy community altogether?) and Internet and Quality (What are the differences, if any, between the quality and strength of personal relationships created online and face-to-face?). Internet & Community Wellman & Gulia begin their article “Net-Sufers Don’t Ride Alone: Virtual Communities as Communities” with the question “can people use the Internet to find community?”. This article argues that social networks online serve to support the same ties while allowing other new community ties to be formed. In fact, the popular belief that people turn away from “real life” relationships is untrue. Wellman & Gulia argue the pundits worries “are confusing the pastoralist myth of community for reality. Community ties are already geographically dispersed, sparsely knit, connected heavily by telecommunications, and specialized in content” (355). They note that participants in online communities may invest more overall time in communities as a whole, rather than reducing time spent in real-life communities in favor of online ones (Wellman et. al, 353-4). Q1: Wellman & Gulia rely heavily on anecdotes rather than evidence, arguing that “the paucity of systematic research into virtual communities has rasied more questions than even preliminary answers”. What are the strengths and weaknesses of this methodology? Furthermore, can the experiences of individuals be generalized to the greater population? Do our experiences and feelings adequately reflect what effects we are actually seeing in the world today? Hampton’s article “Networked sociability online, off-line” also addresses the concerns about the decline of community. There has been a historical trend of an increase in privatism and a decline in public participation over the past quarter-century, but he argues that the Internet can actually help reverse this establishing trend. He notes the lack of existing institutional opportunities in neighborhoods to promote local interaction. Simply put, there are too few opportunities for people to form local social ties and therefore, the internet provides this “virtual common place” (225) for similar interaction. Kronholz’s article explains some of the potentially negative effects of e-mail. A ninth-grader, Shannon sends out a chain letter that she started as part of her science project and in less than a month, receives 160,478 replies. Shannon set out to see how fast information travels over the internet, but was left overwhelmed with too many responses. This article lacks evidence and I was skeptical about some of it- for example, did people really call her to let her know that they responded? However, like Milgram’s Small World study, this article does illustrate the immense size and reach of the global online community and how one message can so quickly disseminate to all different people to all different parts of the world. Internet & Quality Mesch & Talmud found in their article “The Quality of Online and Offline Relationships: The Role of Multiplexity and Duration of Social Relationships” that “online friends play a reduced and probably more specialized role in the lives of than face-to-face friends at extracurricular activities and parties” and that online friends were perceived as less close to face-to-face friends. In fact, online relationships are less integrated into our daily lives and generally differ in quality and type of support too. However, Baym et. al’s article, “Social Interactions Across Media: Interpersonal Communication on the Internet, Telephone and Face-to-Face. New Media & Society” has some different findings. In a study that looks at social internet use by college students in the U.S, they found that internet interactions were evaluated as slightly lower quality than face-to-face conversations and telephone calls, but on average were perceived as high in quality. In fact, students are “supplementing high quality face to face conversations and telephone calls with really good internet interactions” (316). Q1: It is interesting that these two study the youth population, but at different points in their lives (adolescent vs. college). Mesch & Talmud argue that online friends are perceived as less close because of the shorter duration, fewer discussion topics, fewer shared activities. In a college setting, would many of these effects be less exaggerated? Does the internet benefit different age groups in varying ways?]]> http://www.mysocialnetwork.net/blog/481/y7/2006/10/internet_community_friends.html http://www.mysocialnetwork.net/blog/481/y7/2006/10/internet_community_friends.html Week 9 Readings COMM 481 Tue, 31 Oct 2006 09:49:02 -0500 Centrality, Prestige & Power in Social Networks Freeman’s article “Centrality in Social Networks: Conceptual Clarification” discusses the different conceptual foundations of centrality in networks. He concludes that centrality of a point may be determined by (1) Degree (indexes of communication activity), (2) Betweeness (indexes of potential for control of communication) and (3) Closeness (indexes either of independence or efficiency). It is important to note that these three concepts are very sensitive to network size. With many of the smaller, simpler structures such as the line, start or circle, the effects of centrality are quite extreme. In larger, more complex networks, these advantages may vary. Wesserman adds an additional element- Information, which focuses on “the information contained in all paths originating with a specific actor which, in turn, is inversely related to the variance in the transmission of a signal from one actor to another” (194). While these concepts certainly do help with our understanding of centrality, it also raises a lot of questions. What situations might there be where being “central” might make someone less influential/powerful? Monge and Contractor note that “it might seem reasonable to interpret a high degree of centrality as a positive and desirable feature of the network, but it could also be justifiably interpreted as signaling a strain such as communication overload or a constraint on the node’s ability to function effectively.” (p.38). When is a high degree of centrality bad? In what situations can someone be influential but not central? It is interesting that Wesserman notes that the term “prestige” is not necessarily positive. The relationship can be one of “negative affect…actors who are prestigious on this relation are not held in very high regard by their peers” (175). He also notes that these “actors considered prestigious by their peers might be those that are senders, rather than receivers”. What difference, if any, does this have on the diffusion of information and the control of information by that actor? This makes an interesting comparison to Burt’s piece on structural holes (“The Social Structure of Competition”). Both Freeman and Burt agree, although using different terms, on how one can gain control in a network (betweeness). According to Freeman, “the central point can more or less completely control communication between pairs of others” (Freeman, p.222). Burt would relate this to the “tertius gardens” or the “third that benefits” who can play the two sides and control the information. Terrorist Networks & Centrality Krebs’ article “Uncloaking Terrorist Networks” is an extremely flawed study, yet interestingly connects terrorist networks with the issue of centrality and tie strength. Krebs states that “The best solution for network disruption may be to discover possible suspects and then, via snowball sampling, map their individual personal networks - see whom else they lead to, and where they overlap.” Some issues with this include: 1.In retrospect, things seem much more obvious. If you lay out the dots, you will try to connect them, and in many ways see what you want to see (e.g. the “serpent” shaped network). The signals can only be understood if you knew what they were going to do and it is very difficult to understand the information provided unless you understand the terrorist scenario. It is not simply a matter of “connecting the dots” because which dots should you connect? 2.While leaders like Mohamed Atta may be central to the network, he may also be replaceable – i.e. he may not necessarily be integral to the network’s survival. According to Wesserman, “one can take an actor with a large betweeness index and drop it from the network…counting the number of components generated by this deletion will give an indication of how much ‘betweeness’ this actor exerts over the network. Truly central actors will force many disconnected components to arise” (218). This does not appear to be the case in this network. Q: Is this a determining factor? What about degree, closeness and information…are they as important in this situation? 3.The network map is limited! There are many actors involved in the 9/11 attacks and in the terrorist organizations beyond al Qaeda and the U.S. Is a map of this size feasible? 4.Information vs. Action: Krebs assumes that to win this fight, all we need is “better information and knowledge sharing than the bad guys”. While this is partially true, it is not so simple! The fact is, that we DID have a lot of the information. The problem was doing something with that information and interpreting it.In fact, prior to 9/11 we knew that there would be some sort of air strike, but it was the fact that we assumed that it was going to be a regular hijacking rather than a cruise missile-type attack that left us wide open. It is also interesting to note the conflicting views on redundancy of ties. Robert Burt might argue that by increasing redundancy you are losing your network. Instead, you should try maximizing the number of non-redundant contacts to maximize the yield in structural holes per contact, and thus increasing efficiency. However, both Freeman and Wesserman argue that by having a large number of ties (degree), you are becoming more cost and time efficient because of the shorter distance traveled. Krebs adds that in a covertnetwork, that this was a hidden strength. The “massive redundancy through trusted prior contacts made the network very resilient…ties were solidly in place” (p.11). According to their theories on tie strength, how might Burt and Granovetter attempt to disrupt these terrorist networks? Peer Pressure: Popularity and Bad Behavior We often associate the “cool kids” with bad behaviors- smoking, drugs, promiscuousness, bullying, etc. Mouttapa et. al looks at bullying/victimization and popularity. They found that results were consistent with the social cognitive theory and that aggressive friends tend to nominate other aggressive friends in the participation of aggression. In fact, Mouttapa et. al found that “the presence of (a) aggressive friend is associated with lower rates of victimization” (327). In addition, male bullies did not differ from other males on sociometric status- males who occupy central positions in the peer network were heterogeneous in regard to aggressive behaviors. This however, was very different for females, who were not as “popular” but had more reciprocated friendships, suggesting that while they have less central network positions, they have stronger ties to their friends. Do the gender differences and the resulting differences in centrality of bullies affect how we should approach violence prevention efforts? Mouttapa’s findings also suggest that the number of connections in the friendship network, rather than the reciprocation of friendships, may protect students against victimization. How does this affect violence prevention efforts? This week we continue to investigate the causal relationship between popularity and smoking. Valente & Johnson found that popularity was associated with increased susceptibility to smoke, but yet smokers named fewer friends and that this was attributed to having more friends outside of the classroom. They also identified that isolates are early smokers, which seems paradoxical that both groups are more likely to become smokers. Some of the diffusion studies in Granovetter’s “Strength of Weak Ties” article sheds some light on some possible explanations: Kerckhoff, Back and Miller conducted a study in 1965 on “hysterical contagion” in a Southern textile plant. They found that while the first adopters of innovations are marginal (in fact, social isolates), the next group “early adopters”, are more integrated part of the local social system than the innovators. Therefore it is not as Valente et. al has claimed, that popularity leads them to smoke (328), but that they are likely to pick up the habit and influence others. But this also goes against the Pearson et. al’s findings of the homophily principle- that teens who smoke hang out with other teens. This could be attributed to the difference in the population of the two studies- geographically, demographically, etc. One other major difference was in the type of questions asked by each study- while Pearson’s asked about occasional/regular smoking Velente et. al tested for a general “susceptibility to smoking anytime in the future” and “ever smoked” (even if it was one puff, in the last 30 days), etc. Is targeting the ‘popular’ kids in a anti-tobacco campaign the best way to lower smoking rates in teens?]]> http://www.mysocialnetwork.net/blog/481/y7/2006/10/centrality_prestige_power_in.html http://www.mysocialnetwork.net/blog/481/y7/2006/10/centrality_prestige_power_in.html Week 7 Readings COMM 481 Tue, 17 Oct 2006 11:24:31 -0500 (Q1) Social & Societal Change. In the radio interview, Smith-Lovin attributes the “large scale social change in how we are spending our everyday lives” to the changes we are seeing in our core discussion networks. She notes that Americans are spending more time in the paid labor force and that the average American family spends many more hours working. In addition, with the women entering the workforce, we see women becoming increasingly similar to men in their network structure. While women are still the kin keepers, men have dropped off many non-kin ties, leaving them with smaller core discussion networks. Putnam adds that there is also a connection between the “lack of civic engagement and the collapse of our intimate networks” in the interview. In fact he states that there is a direct connection to how much we connect to broader society and how much we connect to the people close to us. Both scholars note the importance of religious institutions as a breeding ground for close personal ties. While people today are still members of many groups, according to Smith-Lovin, they are spending less time in those groups – time that it takes to “create close personal ties that are important to you”. Could it be that this is just a change in our life course? According to Kalmijn’s “dyadic withdrawal” hypothesis, “the life course pattern is dominated by strong continuous effects: the older people are, the fewer friends and the fewer friendship contacts they report”, the biggest effect occurring when people start dating and living together with their partners. (247). Smith-Lovin addressed this in the interview saying that while it is true that young people have more connections, this didn’t change from 1984-2004 and that their study was primarily on adult networks and that there is a change there. Putnam also adds that it may be that we are now having fewer friends earlier on, therefore “starting at a lower level”. Education and Geography According to the article, “The largest change, by far, is in the coefficient-related proportion kin in the discussion network to educational heterogeneity” (McPherson et. al (2006), p. 361). The study shows that there is a relationship between the level of education and the number of confidants in your personal network. Increased education leads to a greater number of confidants, but also a lower proportion of kin. This may at first seem counterintuitive, as the host noted, but Smith-Lovin argues that those advantaged educationally and who are not in a disadvantaged position economically, or in terms of class/race, are also likely to be advantaged in the network resources they have. People who are less educated and live in problematic neighborhoods may actually be afraid to go out and interact with people in their neighborhood. They might not think it is safe to sit on the front porch or to interact with each other. The two scholars both stress that our networks are linked to the types of communities we live in and that the two things are interrelated (community structure and the types of ties we have). Both scholars also note that geography is a factor- families today are more geographically dispersed and Americans are spending more time in the exurbs and suburbs. This leads to familits having longer commutes and according to Smith-Lovin, “the farther out you are, the faster these ties collapse”. Putnam believes that this is limited however, because geographical mobility has declined since WWII and has not been going up over the last 2 decades. (Q2) In both the radio broadcast and in the McPherson et. al article, the authors are talking about our “core discussion networks” – our intimate friends we discuss important matters with, or as Granovetter would classify as our “strong ties”. McPherson et. al argue that “the closer and stronger our tie with someone, the broader the scope of their support for us” (354). These social ties provide: Emotional & Social Support: The people we depend on for chicken soup, ties that “create a safety net for people to help us deal with problems” (Smith-Lovin, radio interview). They are also the people we turn to for “minor emergencies and major disasters” (Smith-Lovin, radio interview). In contrast to Wellman’s article “The Network Community: An Introduction”, the authors have actually found an increase in the number of close times coming from neighborhoods and co-memberships in voluntary organizations. Physical Health Effects: Putnam discusses the powerful physical health effects of having these strong ties. One of the risk factors for premature death is social isolation (almost as big as a risk factor for the death as smoking is).He argues that it has powerful effects on our mental health and that we can’t outsource our physical health. Safety: Putnam argues that these connections are also powerful predictors of crime rates in our neighborhoods. In fact, re-knitting our close networks can make it easier for people to organize themselves, thus helping with politics and crime, in turn making it easier to do more organization (the ‘virtuous circle’). A more densely-knit network will result in an increase in the types of support we have listed above (emotional, physical, social, etc). In addition, a more kin-based network will lead to greater financial support, “big services”, strong ties, broad social support from your parents and at the same time also emotional support and “small services” from your siblings (Wellman). McPherson et. al’s study also showed that we are relying more on our spouses for support. Bott’s study supports this in her finding that there has been an increase in the overlapping, or joint conjugal role relationships. This leads to a more “dispersed” and less interconnected network. Burt would argue that these redundant contacts provide the same network benefits (cohesion) and have the same contacts/sources of information (structural equivalence), therefore making the network less efficient, effective and minimizing the yield of structural holes, which is in a way our link to more novel information not contained in our homophilious network. Lastly, Putnam notes that it is very difficult for these ties to be replaced by other things or structures. The functions that these social (both near and distant) ties perform have very powerful and persuasive effects. Smith-Lovin also discusses the problems on 2 levels: On a personal level- these people you depend on for chicken soup and create a safety net for people to help us deal with problems are obviously necessary in our lives. The decreasing number of these close ties increases the dependency and limits our options. If we are depending on our spouse- what happens if they die, or if you get divorced? She also discusses the larger scale societal things. Social shifts of this magnitude are rare and are generally red flags for society as a whole. The ties we are discussing are connections between people and also the ties between groups in social positions that tie our society together. ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/10/important_matters.html http://www.mysocialnetwork.net/blog/481/y7/2006/10/important_matters.html Assignment #2 COMM 481 Thu, 12 Oct 2006 13:20:54 -0500 Network Homophily McPherson, Lovin and Cook’s article, “Birds of a Feather: Homophily in Social Networks” argues that networks are homogeneous with regard to many socioeconomic, behavioral and interpersonal characteristics because of the homophily principle. Homophily is the “principle that a contact between similar people occurs at a higher rate than among dissimilar people” (p.410, McPherson et. al) and that similarity breeds connection. McPherson et. al’s findings show that the strength of homophily patterns are seen in a range of ties from strong to weak. They state that “the pervasive fact of homophily means that cultural, behavioral, genetic or material information that flows through networks will tend to be localized”. Ronald Burt (1993) would probably argue that with the presence of structural holes , this may not necessarily be the case. While people live in clusters of others with whom they have similar interests and characteristics, the spread of information and new ideas can be facilitated by structural holes that connect people in different clusters. This is essential to the flow of information that integrates the different social clusters in our society. It was also interesting to note that in young children, girls are more likely to resolve intrasensitivity by deleting friendship choices and boys are more likely to add friendships. In fact, children would rather delete same-sex choice ties than add cross-sex ones, which leads to gender segregated cliques. This seems to be in line with Granovetter’s belief that the “forbidden triad”, because in both cases, they are eliminating the “cognitive imbalance”. However, he might add that it is more beneficial to get rid of strong ties rather than weak ones, as they contain novel information that is not contained within homophilous networks. It is interesting that the article reported that “alters of the same sex are significantly less likely to be connected than alters that aren’t matched on sex…this pattern appears because spouses are quite unlikely to know other sex-friends”. It is argued that this is especially true for men, whose wives are unlikely to know their female friends from other foci like work or voluntary organization membership. What would Kalmjin’s say? Pearson, Steglich and Snijders’ article “Homophily and assimilation among sport-active adolescent substance users” addresses the separating effects of homophily and assimilation, and also real world applications of social network analysis. While the study proved to have some very interesting results, the sample was limited to a cohort of pupils in the West of Scotland and does not necessarily reflect the patterns we see in a more racially diverse United States. It would be interesting to examine the racial differences in substance abuse and the degree to which it is related to the network structure. This study also leads me to question the perspective of non-users: are they choosing not to associate with users and has there been evidence of assimilation in the other (positive) direction? Network Size Hill and Dunbar’sarticle, “Social Network Size in Humans” examines the size of social networks based on the exchange of Christmas Cards. While this is a very interesting and creative study, it does have a fairly problematic methodology. Firstly, not everyone sends Christmas cards- not only are we limiting this to a particular religious group but also to a specific racial group (white British). This was done by the authors to “minimize cultural effects”, but does this diminish its usefulness to generalize to the rest of the population? The authors also seemed to use almost trivial things like a letter included with the card to make conclusions about the emotional closeness between the sender and recipient, posing questions about how conclusive the results are. Now with internet “e-cards” and e-mail, do you think this study is as applicable to today’s society? With technology making the process easier and more convenient, can we still use the assumption that “Christmas is the one time of year when individuals make an effort to contact all the individuals whose relationships they value”? As we saw with Milgram’s small world study, people are generally have a really bad idea of social capital. Even in the article by Kilworth et. al (2006) ,“The accuracy of small world chains in social networks”, they reported that people were really quite bad at guessing the right link with only 48% of the people choosing the correct link. Kilworth et al.’s 1990 article “Estimating the Size of Personal Networks” looks as the several different methods for measuring the mean size of an informant’s personal network. The authors concluded that we still have little idea of the mean size of an informant’s network, let alone how it varies between informants and across cultures. One of the strong points of this study is the range of questions they ask about a person’s network. The methods span from examining close ties with the GSS social survey (“with whom can you discuss important matters?”) and the questions on the support network (questions like “who is your best friend”) to examining weaker ties with the FT Phonebook and Reverse Small World (RSW) study. Perhaps the FT Phonebook method was a little too ambitious. It would be interesting to replicate that study in a smaller setting, such as a University setting, and using the student/faculty/staff directory to conduct a similar experiment. In addition, how can modern technology and the Internet help? Do programs like Facebook, Friendster or My Space also have some value in their ability to estimate the size of personal networks?]]> http://www.mysocialnetwork.net/blog/481/y7/2006/10/network_homophily_size.html http://www.mysocialnetwork.net/blog/481/y7/2006/10/network_homophily_size.html Week 6 COMM 481 Tue, 10 Oct 2006 07:12:54 -0500 Small University Experiment Part 1 Target: Susan Yoon, Assistant Professor at the Graduate School of Education 1. The first person I gave my folder to was June Chu, the Director of the Pan Asian American Community House. June is an Asian American female and also a staff member of the University. According to Milgram, gender is an important characteristic because “participants were three times as likely to send the folder to someone of the same sex as to someone of the opposite sex”.(65) Following that argument, June’s gender increases the probability of it reaching the target. Milgram also discusses race in another study. June’s race, is an advantage because she is probably more likely with the communication structures of Asians on Penn’s campus. June and Susan also have similar educational interests- they both have P.H.D’s in education/psychology/type fields. Lastly, June’s position as a director of a cultural resource center on campus gives her access to a variety of people. She, like Lois Weisberg, is a “connector” with many weak ties just steps away (Gladwell). June knows both student, faculty and staff and “the larger and more varied the pool of acquaintances a participant can draw on, the grater the opportunity of choosing an effective link” (Milgram, 107). In addition, according to Milgram, occupational similarity was a factor that increased the chances of having the folder delivered to the target. 2. June and I would have what classifies as a “strong tie”. We spend a decent amount of time together in many different contexts and is someone I can trust and depend on. This relationship of trust will increase the likelihood of my folder reaching the target because I trust her and can depend on her to participate and complete the task in a timely manner. This is an important factor because, like Milgram stated, “126 dropped out…these chains die before completion because on each remove a certain proportion of participants simply do not cooperate and fail to send on the folder” (65). 3. I think that Suasn’s personal characteristics make it more likely for me to get the folder to her, but her structural position poses a challenge . Why? Susan is an assistant professor at the School of Education, a Graduate students. Not many undergraduate students take classes there or in the building. This limits the number of people I know who could potentially be in contact with her. The student population and class size at the Graduate School of Education is definitely smaller than the other schools, which also is an obstacle. However, the fact that we are both Asian females does, according to Milgram, increase the chances of her receiving it because as his study in his 1970 shows, 80% of the incomplete African American target chains never crossed the racial barrier. 4. I’ve passed my folder onto June who knows Susan. 5. 1 Person, 2-3 Days. ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/09/one_step_away.html http://www.mysocialnetwork.net/blog/481/y7/2006/09/one_step_away.html Assignment #1 (Part 1) COMM 481 Thu, 28 Sep 2006 01:20:46 -0500 Weak Ties: Implications for society today An overwhelming amount of the literature on social capital/social structure in the media is about the increasing isolation and loneliness we are experiencing in today’s society. Putnam’s “Bowling Alone” on the collapse and revival of the American community has expanded beyond the study of social networks and into the ‘mainstream’. This week’s readings explore a refreshing perspective on how weak ties can be beneficial to our lives and are in fact a crucial part of our social structures. Weak Ties vs. Weak Online Ties In the article “The Strength of Weak Ties”, Granovetter argues that weak ties are important in expanding our knowledge of the world beyond our friendship circles and in terms of the access to information that is different from that which we already receive. But are weak ties necessarily making us more diverse? One of Granovetter’s hypotheses was that the stronger the tie connecting the individual, the more similar they are. With the spread of the internet and online technology, increasing numbers of people are seeking information about their interests and generally joining communities of people who are like them. Q: Do weak online ties share the same characteristics as the weak ties Granovetter talks about? Interestingly enough, does strength matter? According to Burt, whether a relationship is strong or weak, it generally benefits when it is a bridge over a structured hole. He argues that the weakness of a tie is not a causal agent, but the structural hole it spans it and that the weak tie argument leaves out the control benefits of structural holes. Finding a balance It is said over and over again, that with most relationships, “you get what you put into it”, which builds on Granovetter’s criteria of having “reciprocal services” in a tie for it to be a strong tie. My question is: should we be more concerned with quantity than quality? Q: Should we spend the time networking, rather than getting closer to the people we already know? What are the implications for these changes on our social life? In my opinion, it is necessary to have a fine balance between the two. No one is better than the other, because each is necessary for the existence of the other. Weak ties become strong ties, strong ties introduce weak ties, and more importantly, they provide very different things to our lives. I could not be happy with networking all the time and having 600 acquaintances but at the same time I would not be happy with only staying within my friendship circle. Weak ties are important in making possible mobility opportunities yet strong ties are important for us to stay emotionally sane- to have someone to talk to, cry to, share your life with. The McPherson et al. article “Social Isolation in America: Changes in Core Discussion Networks Over Two Decades” asked people with whom they discussed personally important topics with. They found that it still holds that American’s core discussion networks are heavily constituted by family. Perhaps it is because we have less time to invest in better to have 2 strong ones than 3 less than strong relationships. Work, mobility, leisure time and our ability to be picky- I think that all is a factor in who we now choose to talk to. Our relationships are increasingly specialized, and we talk to different people about different things. Competition: Relations vs. Attributes. Burt’s article on “The Social Structure of Competition” was definitely interesting especially as a senior looking for a job. Burt ends at the last section of his article that “competition is a matter of relations, not player attributes”. He adds that “the attributes of the players in whom the relations intersect- black, white, female, male, old, young, rich, poor- are an empirical curiosity irrelevant to the explanation”. This brings me back to last week’s discussion on the differences in poor and/or non-white social structures. Based on personal experience and the literature up to this point, I find it hard to believe that our personal attributes have no impact. Burt describes three main types of capital a player brings to the competitive arena: financial, human and social. Social capital, he says, is the final arbiter of competitive success and is of crucial value when financial and human capital is abundant. However, in reality this is not always the case, and a poor non-white applicant without an Ivy League education or a myriad of internship experience may not even be considered before he or she can display the social capital they have. ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/09/weak_ties_implications_for_soc.html http://www.mysocialnetwork.net/blog/481/y7/2006/09/weak_ties_implications_for_soc.html Week 4 Readings COMM481 Tue, 26 Sep 2006 10:00:49 -0500 Race, The Plastics & The Missing Pieces With race, is it black and white?. Stanley Milgram’s article “The Small World Problem” examines the probability that any two people, selected from a population, will know each other (62). The small world method consists of giving several “starting people” the task of passing selected information in a folder to a “target person”. Korte & Milgram’s article “Acquaintance Networks Between Racial Groups” breaks this study down to examine what happens to acquaintanceship chains as they are impinged upon by social structure (102). A major finding was that white target chains exhibited a greater chance of completion than the black chains. Many people today are trying to convince us that the world is getting smaller and closer with technological advances. However, this study also reflects that we may not be as close to living in a small, interconnected world as we think- in fact, the world is still a place divided by social barriers, class and race. The most common reason for the crossing of racial barriers was the occupational similarity- most acquaintances ties crossed were male and had professional status. In fact, more shockingly, 80% of incompleted “Negro” targeted chains never crossed the racial barriers, proving that perhaps it is only a small world within and not outside of racial groups. The Plastics The reality is, that many times people network to meet the rich and the beautiful. For those of you who haven’t seen Mean Girls (2004), "The Plastics" are the A-list clique, the groups everyone wants to meet, know and be. Gladwell’s article “Six Degrees of Lois Weisberg” examines some interesting connections between power and quality vs. quantity of relationships. As Gladwell states, “the old idea was that people got ahead by being friends with rich and powerful people—which is true, in a limited way, but as a pratical lesson in how the world works is all but useless…the old-boy network is always going to be just for the old boys” (12). In fact, you want to get to know “connectors”- not someone who is necessarily charismatic, beautiful, rich or extremely extroverted- but someone who can spread information and ideas, has the ability to connect varied and isolated parts of societies and someone with social power. A very interesting aspect of this is power in our relationships. Gladwell discusses Granovetter’s argument that “what matters in getting ahead is not the quality of your relationships but the quantity –not how close you are to those you know but, paradoxically, how many people you know whom you aren’t particularly close to.” While I agree that this may help with networking for jobs and climbing the social and corporate ladder, your emotional well-being is still dependent on the quality of relationships. No matter how many people we are friends with, in the end, it is your close friends that are going to be there when you need comforting, support and a shoulder to lean on. “Poverty is not deprivation. It is isolation” In last week’s readings, Wellman stated that “larger, more heterogeneous and denser networks provide more support” (25). Lois Weisberg argues that this also applies when helping the poor: "I don't believe poor kids can advance in any way by being lumped together with other poor kids (10). She started a program where poor kids would be able to mix with middle class kids in their afterschool extracurricular activities and it was a great success. While I agree that many times poverty is about isolation and not having the access or the knowledge of the necessary networks and resources, it is not about finding “a way to get out of [your] neighborhood altogether” (Gladwell, 12). While Wellman established that “neighborhood” is not synonymous with “community” in terms of its provision of support, the Watts article on “The ‘New’ Science of Networks” shows that network structure is important locally (because an individual neighborhood provides one with information and resources) as well as globally (in that it enables him to navigate when searching for information or resources outside his neighborhood). Leaving the “problem area” will only worsen the situation and is not a solution to the root of the problem. On a global scale, the human capital flight (or “brain drain”) phenomenon is widespread and increasingly problematic when the trained and most talented individuals leave the country. Simply put, the importance of the neighborhood community should not be lost in the development of impoverished areas. Missing Pieces Three major issues came up when I read the Milgram article. Firsty, while some of the cases were remarkably successful, such as the case with two intermediaries, how many were not completed, and what conclusions could we draw from this? As mentioned in the beginning of my blog, Milgram’s study was also not representative of the ‘real world’ with its predominantly white, upper middle class, professional makeup. Lastly, does the selection of the “target person” affect the outcome of the study? Had the target been someone less well established and of a different race/class, would the results be replicated? Killworth et. al also illustrates that in the real world, limited information available to individuals lead to more mistakes and is in fact predominant, leaving us with serious implications for deductions for issues like the spread of infectious diseases. Despite the limitations, in today’s increasingly technological and internet-based world, Milgram’s study could be stronger and more relevant than before. It would be interesting to further investigate a Milgram-style study via electronic mail and perhaps on a global scale. ]]> http://www.mysocialnetwork.net/blog/481/y7/2006/09/race_the_plastics_the_missing.html http://www.mysocialnetwork.net/blog/481/y7/2006/09/race_the_plastics_the_missing.html Week 3 Readings Comm481 Tue, 19 Sep 2006 04:48:07 -0500 Testing :) http://www.mysocialnetwork.net/blog/481/y7/2006/09/test.html http://www.mysocialnetwork.net/blog/481/y7/2006/09/test.html Test Sun, 10 Sep 2006 23:28:09 -0500