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November 2006 Archives

November 5, 2006

computerized networks

Kleinberg and Lawrence’s paper gives an overview of how the web works. The authors explain the different components of the web, “the core, upstream, downstream and tendril regions” (1849) at the local level, and also how the web behaves like a network at a more global level. Based on the explanations and descriptions of how the web works, what are some of the ways in which people/users might use its structure to their advantage? The authors also mention that an “analysis of the Web’s structure can help to define topics and social groupings of interest to its denizens” (1850). What are some of the strengths and limitations that would come along from studying social networks and communities through the use of the Web?

In his article, Marks describes how the Pentagon’s National Security Agency has started looking at the information that people post about their social networks on the Internet, and what kind of implications this could have on our lives. Even though as of now the NSA can only connect people through the data that individuals post on the internet, with advances in internet technology, very specific and personal information, such as financial transactions could be tracked. However, it makes me wonder how feasible this really is. As long as people are careful and don’t make too much information available on the Internet, I feel that, at least as of now, the amount of “connecting the dots” that the NSA can do is limited. And, even if advances of the internet technology do make more personal information available, new technology also means new and/or revised privacy policies which might limit the level of access that the NSA can have. However, this is also depends on whether people are aware of these privacy policies and the rights that they have to protect their privacy, which are not widespread knowledge. If what Marks says is true and future advances will mean exposure of private information, would this have an effect on individuals’ social networks?

Ellison et al studied the role that facebook plays in the “social capital formation and maintenance, integration into college life and psychological well-being” of students at Michigan State University. The researchers found that facebook is being extensively used as a tool to maintain and develop current offline relationships as well as old relationships, such as high school relationships. These relationships can be both strong or weak ties, with facebook playing a special role in stimulating latent ties into weak ties. Why do you think that, unlike the articles that we read for last week, facebook is predominantly used to maintain ties instead of creating new ties?
One of the weaknesses of the study, which the authors admit as their limitation, is that it was only carried out at one school, MSU. Being a state university, this may limit the generalizability of the study results to other schools. Also, the article was published in June, 2006. Since then, facebook has undergone a massive change and included numerous features that let users “monitor and follow” what their friends and others are doing with their lives and facebook use. Do you think these changes would have an impact on the results found by these authors if the survey were to be carried out now? What kind of impact do would you say that these changes have had on users’ social networks and the way in which they relate to people, both online and offline?

Wellman extensively overviews the way in which “affordances in computer-supported interpersonal communication affect the ways in which people connect with each other” (229). He states that the technological advances have provided individuals with new resources that move networks from being place-based to person-based, developing “person-to-person connectivity” (238). His article brings up several questions and issues that have been raised with the expansion of technology-based relationships and how these would impact offline relationships.
I think that his comment that “cyberspace fights against physical space less than it complements it” (247) is a very accurate description of how computer mediated relationships are being integrated to offline relationships. Nowadays, these cyberspaces are filling in the gaps in time that we don’t spend physically at work, school, with friends or family. They provide alternative ways in which we can still interact with these people and organizations, allowing people to be constantly aware and on top of things that are going on around them. What kind of impact would this have on people’s existing relationship and in the formation of new relationships?

November 13, 2006

diffuse, diffuse, diffuse~

In “Diffusion Networks” chapter 8, Everett talks about how interpersonal communication, mainly opinion leaders, affect the diffusion of information in networks. In doing so, he touches on different topics that affect such diffusion, such as homophily and heterophily, opinion leadership and the characteristics of leaders, the concept of critical mass, etc. He also provides different generalizations that he draws from other researches, which help further understand and sustain his argument that opinion leaders do matter in the diffusion in communication networks.

One of his generalizations with which I didn’t agree with was generalization 8-12: “Individuals tend to be linked to others who are close to them in physical distance and who are relatively homophilous in social characteristics” (341). In previous readings and weeks, we have seen that physical distance is not such an important factor in deciding whether individuals are linked to others or not. Especially with the introduction of new technological advances, such as the Internet, cellphone, and other portable electronic devices, physical proximity is a very inaccurate predictor of the structure of one’s network. Also, some individuals, namely those who can be denominated as bridges and/or structural holes within a network, are not mainly linked to others who are homophilous; they also have links with people who are heterophilous, and these are the links that allow these people to fulfill the structural position that they do.

Q: “The fact that certain innovations are adopted by clusters of individuals suggests that interpersonal networks among neighbors are powerful influences on individual decision to adopt” (335). If neighbors are important influences on innovation adoption, how would the fact that people are decreasing their interactions with neighbors affect adoption of innovations? Would people get their information from other sources? Would they stop adopting innovations? Would there be no more clustering of adoption of innovations?

Tepperman makes an interesting application of social networks and their analysis in the search of deviance, giving an example of how theoretical concepts and studies, such as the study of social networks, can be used and applied for meaningful and practical reasons. He explains the “features of a deviant search” and how these affect the way in which individuals engaging in the deviant search are affected by them and how they change their strategies in acting and looking in their social networks for the deviant object. The author mentions that during a blind search, a breadth-first search for a deviant object “will always find a shortest-length path”. However, wouldn’t this mean that the individual who is engaging in such an act also runs the risk of exposing himself to many people at the same time? If an individual carried out a depth-first method instead of a breadth-first search, then, even if the search ends at a dead-end, the individual will not have exposed him/herself to that many people. So maybe, even if a breadth-first search does yield the shortest path, it might not be the safest path, especially for someone who is searching a deviant object.

Q: We have just read about how new media can be an access to new sources of information by meeting new people and gaining access to otherwise limited data. How would a deviant search take place in an online community? Would the steps and factors listed by the author in the article be used in an online setting as well?

Burt also deals with the role that opinion leaders play in diffusion of innovations. He draws a relationship between the study of diffusion and social capital research by pointing out the resemblance of opinion brokers (in diffusion research) and network entrepreneurs (in social capital research). He begins by differentiating cohesion and equivalence, and how these affect contagion, and then applies the theory to studies that were carried out as evidence. The first study that Burt mentions corresponds to the adoption of medical innovations, and concludes that 1) “equivalent physicians followed one another in their adoptions of the new drug” (44) and 2) cohesion is irrelevant where equivalence makes its strongest predictions” (44). Could this finding be due to the fact that the study tracked a profession in which equivalence plays a strong role? Do you think that the same/different results would have been found if the study had been carried out regarding diffusion and contagion in other professions/situations in which equivalence didn’t play such an important role?

November 15, 2006

New media's invasion!

(1)
5 people with whom interacted the most often:
1. Daniel – 41 interactions; age 20; male; romantic partner; strong tie strength; known each other for ~1 year; currently resides in Lyon, France (distance: 3000+ miles)
2. HoJun – 25 interactions; age 20; male; sibling; strong tie strength; known each other for ~20 years; currently resides in Atlanta, GA (distance: 800+ miles)
3. Ainsley – 20 interactions; age 20; female; housemate/same organization (sorority)/friend; strong tie strength; known each other for ~2 years; currently live in the same house (distance: 0 miles)
4. Abby – 16 interactions; age 20; female; same organization (sorority)/friend; strong tie strength; known each other for ~2 years; currently resides in Barcelona, Spain (distance: 3000+ miles)
5. Nati – 12 interactions; age 21; female; friend; strong tie strength; known each other for ~2 years; currently resides in Washington DC (distance: 150+ miles)

Most frequent interactions per media:
1] Cellphone
1. Daniel – 13 interactions
2. Nati – 9 interactions
3. Ainsley – 7 interactions
3. Clara – 7 interactions; age 20; female; friend; strong tie strength; known each other for ~3 years; distance: 0.1 miles
5. Emo (Aunt) – 6 interactions; age 44; female; other relative; strong tie strength; known each other for ~21 years; currently resides in South Korea (distance: 3000+ miles)

2] SMS
1. HoJun – 8 interactions
2. Daniel – 3 interactions
3. Ainsley – 1 interaction
3. Nati – 1 interaction
3. Joaquin – 1 interaction; age 21; male; friend; strong tie strength; known each other for ~6 years; currently resides in Barcelona, Spain (distance: 3000+ miles)

3] Email
1. Ainsley – 12 interactions
2. Daniel – 9 interactions
3. Kate F – 7 interactions; age 19; female; housemate/same organization (sorority)/friend; strong tie strength; known each other for ~2 years; resides in same house (distance: 0 miles)
4. Jacki I – 6 interactions; age 20; female; housemate; moderate tie strength; known each other for ~3 months; resides in same house (distance: 0 miles)
5. Kelly J – 5 interactions; age 20; female; same organization (sorority)/friend; moderate tie strength; known each other for ~2 years; distance: 0.1 miles
5. Christina S – 5 interactions; age 20; female; same organization (sorority)/friend; strong tie strength; known each other for ~2 years; distance: 0.1 miles
5. Sarah G – 5 interactions; age 21; female; housemate; moderate tie strength; known each other for ~3 months; resides in same house (distance: 0 miles)

4] IM
1. Daniel – 4 interactions
2. Joaquin – 2 interactions
3. Abby – 1 interaction
3. Dad – 1 interaction; age 51; male; parent; strong tie strength; known each other for ~21 years; resides in Buenos Aires, Argentina (distance: 3000+ miles)
3. Ale A – 1 interaction; age 20; female; friend; strong tie strength; known each other for ~10 years; currently resides in Buenos Aires, Argentina (distance: 3000+ miles)
3. Uncle – 1 interaction; age 42; male; other relative; strong tie strength; known each other for ~21 years; currently resides in South Korea (distance: 3000+ miles)

5] Skype
1. Daniel – 2 interactions
2. Ale A – 1 interaction

6] Facebook message
1. Daniel – 6 interactions
2. HoJun – 1 interaction
2. Katie D – 1 interaction; age 20; female; same organization (sorority)/friend; moderate tie strength; known each other for ~2 years; distance : 0.1 miles
2. Marisa – 1 interaction; age 19; female; same organization (sorority)/friend; moderate tie strength; known each other for ~2 years; currently resides in Padova, Italy (distance: 3000+ miles)

7] Facebook Wall
1. Abby – 2 interactions
2. Nati – 1 interaction
2. Liz Lee – 1 interaction; age 19; female; same organization (sorority); moderate tie strength; known each other for ~1 year; distance: 0.1 miles
2. InHee – 1 interaction; age 20; male; friend; strong tie strength; known each other for ~3 years; distance: 0.1 miles
2. Clara – 1 interaction
2. Kevin – 1 interaction; age 21; male; acquaintance; weak tie strength; known each other for ~1 year; distance: 0.1 miles
2. Greg M – 1 interaction; age 20; male; friend; weak tie strength; known each other for ~3 years; distance: 0.1 miles
2. Maria DM – 1 interaction; age 22; female; same organization (sorority); weak tie strength; known each other for ~1 year; distance: 200+ miles
2. Cici Z – 1 interaction; age 20; female; same organization (sorority)/friend; moderate tie strength; known each other for ~2 years; currently resides in London, UK (distance: 3000+ miles)
2. Dan S – 1 interaction; age 21; male; friend; moderate tie strength; known each other for ~1 year; distance: 0.1 miles
2. Cara Hoy – 1 interaction; age 20; female; acquaintance; weak tie strength; known each other for ~1 year; distance: 0.1 miles
2. Marisa – 1 interaction

8] Skype Out
1. Daniel – 1 interaction
1. Nati – 1 interaction

9] Facebook Poke
1. Hojun – 11 interactions
2. Abby – 7 interactions
3. Daniel – 5 interactions
4. Clara – 4 interactions

10] Facebook picture (comment)
1. Dan S – 1 interaction

11] Blog posting
1. r5 – 1 interaction; N/A; N/A; classmate; weak tie strength; known each other for ~3 months; distance: 0.1 miles
1. r14 – 1 interaction; N/A; N/A; classmate; weak tie strength; known each other for ~3 months; distance: 0.1 miles

(2a)
For most of the communication media there seems to be a relationship with the strength of the tie. Weak ties, all of who were known from an offline setting, were mostly reached through the use of facebook. In their study of facebook, Ellison et al found that facebook is a great way to “capitalize on weak ties and convert latent ties to weak ties” (29) and this is clearly supported by my data. In contrast, strong and moderate ties made use of various media. Once again, facebook was also used for these ties, mainly to “intensity and solidify relationships that started offline” (Ellison et al, 32). Another interesting finding is that the stronger the tie, the more media used, especially those media that required an immediate and synchronous type of communication, as well as a significant amount of time (and maybe resource) investment, such as cell phones, texts, Skype and IM. Since “multiplexity increases ties strength” (Mesch and Talmud, 139), the more activities and interests shared, the stronger the tie, and thus, the more media used in order to address these different activities and interests accordingly. Email is the only media that didn’t show a relationship with tie strength; it was used for all three ties, although my pattern of usage suggests that it was mainly used with strong and moderate ties. Baym et al find that “email was the main internet medium for social interaction” (313) which could be why email isn’t necessarily associated with a tie strength and widely used across different strengths.

(2b)
Emotional aid and companionship were related to the use of almost all media. As Baym et al argue, “people will incorporate the internet into their social lives in ways that fulfill their particular social needs” (315), which suggests that different media are used to fulfill these supports from different people. Email was once again strongly associated with information exchange, and it was also the medium through which the only small service was exchanged.

(2c)
Synchronous media was associated with all types of relationships, except for classmates, acquaintances and professors. These latter were related to strong usage of email, and facebook was especially used for acquaintances. For all other types of relationships, cell phone was the preferred medium, followed by email, facebook, texts and IM/Skype. This pattern could not only be due to the type of relationship, but be associated with the tie strength as well. The romantic partner and sibling were the two type of relationships that made use of a wide range of varied media. Wellman and Wortley say that “siblings are similar to friends in providing emotional support” (574) which, related to the answer in (2b), could be why such varied media was used between us. McPherson et al find that spouses are among the few people with whom important matters are discussed with. Thus, it would seem to make sense that such an important tie would be accessed through different media.

(2d)
There was no clear-cut relationship between duration of relationship and medium used. It’s not so much about the duration of the relationship but more about the strength of the tie.

(2e)
Distance did not seem to play such an important role in determining the type of media employed. Cell phone was the most common medium used for both people in proximity and long distance, followed by email and facebook. Since everyone abroad with whom I have contact with are strong ties, it might be, again, that tie strength is the variable that is playing an important part in determining the usage of media instead of distance. This is consistent with Wellman’s theory that “people usually obtain support, companionship, information and a sense of belonging from those who do not live within the same neighbourhood or even within the same metropolitan area” (233): distance is not what matters since nowadays, the advanced technology for transportation and communication help maintain and support strong ties, wherever they are. Hampton points out that “while computer-mediated communication further reduces the friction of space, it can also afford local interactions” (225), which is a trend that can be seen in my data as well. Overall, the usage of Internet mediated communication (such as email and facebook) was for both long-distance ties, as well as locally proximal ties, since “the Internet supports “glocalization” ” (Hampton, 226).

(2f)
Age did seem to play a role when deciding what medium to use. Older people in my social network tended to make use of the cellphone to get in contact with me. This may be so due to the fact that the cellphone resembles the traditional mainline phone in its purpose and use. However, it should also be pointed out that those older individuals did contact me via computer-mediated communications, such as email and IM, but these two were males and both did it while they were at work, suggesting a relationship between their use of specific media and their environment since in other settings, such as when they were at home, they contacted me via cellphone instead. Consistent with Hampton’s argument that “a large proportion of those who emailed family members did so to seek advice and social support” (224), my email interactions with the older people (both family members) was to obtain emotional support and small services (advice in this case). Furthermore, compared to younger people, older individuals used less of a variety of media, but this fact could have been due to other external factors, such as their lack of accounts in facebook. Younger people did not show a specific relationship with any specific type of medium, and instead made use of a variety of media, and again, these choices were mediated by the strength of the tie.
Gender did not seem to have relationships with media use. However, it is true that the people with whom I have engaged with in the analyzed week are predominantly women, which provides evidence for the tendency of homophily (according to McPherson et al, baseline homophily in this case), and also to the fact that “emotional support [is] substantially provided by women” (Wellman and Wortley, 581), (which is in fact, the highest support received and given through my communication with these people.

(2g)
There was a tendency for age-similarity among the people in my network, as well as, as mentioned on (2f) a tendency for gender-based homophily. However, these similarities did not have a relationship with the medium of communication employed. The same media were used for both older and similar-aged groups, as well as gender.

(2h)
The role that new media plays in our social networks seems to be considerable, and it is a “legitimate, supportive means of social contact”, as well as “one form of communication amongst many” (Hamptom, 223). The variety of communication options play a special role with those individuals with whom face-to-face contact is difficult but with whom strong ties are still shared, since they provide ways in which such relationship can still be sustained and continued. (Ellison et al). Strength of tie seems to be the most important variable in determining what type of medium will be used, especially when it comes to the choice of asynchronous and synchronous media. Email is the exception to this, but this can be explained by the fact that it “can engage others not only one-on-one, but as a broadcast of one-to-many” (Hamptom, 226), which is a very useful and practical feature in communicating with multiple people in short amounts of time and in an economic way (this factor being especially important for college-aged students).

(3)
Both strong and weak ties were contacted from home and public places, and none of the personal characteristics listed played a role in deciding whether the interactions were carried out from home or public places. In general, most of the interactions were carried out from home, and most of the strong tie interactions were carried out from home as well, whereas weak ties were carried equally in home and public settings. I believe that this is the case because strong ties have been predominantly contacted through cellphones. According to Wellman, “mobile-phone users can choose where they call from, but they have less control over where they receive calls” (239). Thus, the home setting may liberate this latter problem, which is why cellphone interaction with strong ties has predominantly taken place there. However, it is also the case that cellphone’s do indeed “afford person-to-person contact […and] liberation from both place and group” (Wellman, 239), and thus are employed in public settings with strong ties as well. Age could potentially be a personal characteristic that played a role in determining the interaction setting: except for one interaction which took place in public space through cellphone, all the other interactions with older people were at home. Once again, this supports Wellman in that cellphones free people from being bound to a specific location for communicating and open possibilities to the public locations as well. However, the age factor could also have been the result of the difference in time since all the older people reside in other countries and time zones.

New media’s changing the composition of our social networks mainly by blurring the boundaries between public and private settings. As Wellman says, new media “use shifts community ties from linking people-in-places to linking people wherever they are. Because the connection is to the person and not to the place, it shifts the dynamics of connectivity from places to individuals” (238). And this is exactly what’s happening. Especially with cellphones (although they will soon be joined by “portable” computers), people have access to other people wherever they are, and thus change the composition of our networks because it will increase and change the connectivity and the type of interaction and relationship with individuals instead of with groups of individuals, such as household (Wellman). Fischer says that people in urban settings choose which kin they want to spend more time with. New media may just be offering the exact same thing, but to a broader audience: by allowing connectivity within individuals and not groups, we may be able to choose and select those people with whom we want to establish what kind of social tie and support, and when.

November 27, 2006

health and social networks

Dickens et al study the relationship between having (or lack of) a close confidant to the development of future/further cardiac events. Their initial hypothesis looked at whether “depression, lack of social support, or both before MI” (518) could be associated with further developments of adverse events, but their results showed only the lack of social support was associated with this. I was surprised to find out that depression after the initial MI was related to increased mortality, but not depression before the initial MI. It would have been interesting to see whether the depression that developed after the initial MI was also related to lack of social support or not. If the authors had found a relationship, then I believe this could have been used as further evidence to support their claim that lack of social support does indeed have very negative effects on the probability of developing future adverse events.

Cohen and Brissette investigated whether having a greater network diversity helps boost one’s immune system. They found that indeed, it is the diversity of one’s network that matters when it comes to fighting colds, not the number of members that one has in one’s social network. It was very disappointing that the authors could not determine what factors within one’s network diversity were the ones responsible of decreasing one’s susceptibility to colds. They briefly mention different possibilities, “such as network density, weak ties and structural holes” (9). How do you think these possibilities could potentially positively aid one’s immune system?

Q: The authors have mentioned that “for these types of studies, concise instruments are at a premium and intensive measurement is reserved for the rare cases…” (11). What kind of measurements that we have studied could be helpful in solving/dealing with this aspect of measurement that could potentially lead to mis-measurements?

The last reading for this week dealt with the structure in which romantic and sexual relationships among adolescents at a high-school, Jefferson. The authors’ main finding is that the network structure of this high-school’s romantic and sexual relationships is one that follows a spanning tree format, in which a key norm rules the way in which these relationships limit themselves (and thus form the tree): a norm against second partnerships. I was a little surprised at the only explanation that the authors provided for this norm that they found; the fact that adolescents are aware, and care about what others think about their relationships and how this in turn, affects their status among their fellow adolescents. I do agree that this could be a reason behind such tendency, but I somehow feel that there should be other explanations too that the authors failed to mention in their paper. What other reasons do you think could account for such a norm to develop within the romantic and sexual relationships in the high-school?

It is interesting that the authors make a point to differentiate adult network structures to adolescent network structures, and how this difference might lead to the need of having different approaches when dealing with health problems and issues in each of these structures. I do believe that even in the adult world, people are aware of how others think of them, and thus, the way in which their relationships, both romantic and sexual, develop is, in a way, dictated by the status that the relationship and the partner provides, just like in the adolescent world. Even if this presence might not be as prominent in the adult world, it would seem that the conclusion that they drew was a little hasty. If adults’ relationships are also influenced by “local status” (79), how would this influence the way in which adults ultimately decide on partners?

November 30, 2006

small university experiment - part III

link:
http://www.mysocialnetwork.net/blog/481/y1/2006/09/lets_get_delivered.html

The results of our Small University Experiment are in, and several points of interest have emerged from these. Overall, it was striking to see the differences in the rate of success for the two target people in our study: Susan had an 80% success rate, whereas Antonio only had 25%. When making a comparison to Stevenson et al’s study, who carried out a similar Small University Experiment, their results were a 27% success rate, which resembles Antonio’s success rate and also Milgram and Korte’s (22%), more than Susan’s.

The number of total mean links was different as well: Susan’s 3.25 links and Antonio’s was 4.5 links (Stevenson et al only provide the number for completed chains). Stevenson et al say that “more chains are likely to successfully reach their target in SW studies in organizations as compared to the larger society” (5). Could it be said that the Education School is considered an organization, given its smaller size and relative “isolation”, whereas the Medical School would be “the larger society”, which would partially explain the differences in success rate?

Another point that Stevenson et al make is that “upper-class students were more involved in the completed chains” (6). Our results show a similar patter: except for g23, whose success involved freshmen, mostly upperclassmen were involved in the experiment as a whole, for both successful and unsuccessful chains as well. As the authors mention, this could speak to the relative isolation of freshmen from the rest of the university: this fact is especially pronounced in our case since our experiment was carried out during the Fall semester, a period in which freshmen are still trying to adjust to the new life in college (whereas the Stevenson et al study was conducted in the Spring).

The authors’ second hypothesis states that “folders are more likely to be passed within a class than between classes and occupational groups in a university” (3), which was supported by their results. However, the same pattern could not be seen in our data: there was no real “hierarchy of student communication links” (6), since in general, we passed it to people in our same year, ~40% for both Antonio and Susan, lower classes, ~30% for Antonio, 60% for Susan, and higher classes, ~30% for Antonio. Thus, it would seem that, in terms of class and occupational groups, our results go against this type of homophily and McPherson et al. On the other hand, our results are in line with Milgram’s finding that there is occupational similarity between alters and the target.

However, our results and Stevenson et al’s do agree in that the folder tended to reside within students until it was passed to graduate students, staff or faculty members, followed by the target. There was no regression in terms of hierarchical status. Everett says that “homophily and effective communication breed each other” (306); thus it makes sense that, students, who are homophilous in terms of occupational status, would have kept the folders among themselves to ensure that the folder would reach a faculty, graduate or staff member adequately and not have to regress to the students, since these two groups would have a harder time communicating effectively based on their occupational heterophily. Unfortunately, there doesn’t seem to be any data explaining what characteristics these gatekeepers had since there is no pattern to be detected in terms of years at Penn, school, department nor gender.


There were also some interesting similarities and differences between the results of our own targets. In the case of Susan, a high percentage of the (completed) last intermediate links shared school: 75%, 12.5% shared the same department and 37.5% shared the same affiliation. In Antonio’s case, 0% shared school, 50% shared the same department and 0% shared affiliation. This marked difference could be explained by the sizes of the schools in which the targets resided. Since the Education School is smaller and contains a less variety of departments, the probability that someone will share departments is higher than the Medical School.

Gender was one aspect in which strong homophily was found. Stevenson et al found a strong homophilous tendency among women undergraduates: “6 out of the 8 paths that originated from undergraduate female students went to other females”. (7). Our date shows a similar patter: not only was the last intermediary for completed chains of the same sex in 87.5% cases for Susan, and 100% for Antonio, but also, in the total percentage of transfers to same gender, Susan’s binder went through members of the same gender in 85.7% of the links and for Antonio, it was 50% of the links. Also, it is interesting to see that, even if the majority of starters were women, depending on the target person, the proportion of members of the same gender adjusted to the target person. For example, for Susan, almost everyone was a female, whereas for Antonio, we see a higher presence of males than in Susan’s case. However, as addressed in my blog for part I, this tendency can just be a result of the fact that the Education school has a higher number of women than men, whereas the Medical school is more balanced in its proportions, instead of being a consequence of homophily. Therefore, it would seem that, unlike Stevenson who said that “women relied more on homophilous ties to pass folders compared to men” (8), the gender homophily is more based upon the sex of the target, like Milgram had stated.

From the data that is available, it seems that for Susan, most of the completed binders used a moderate, strong, or very strong tie strength as their 2nd alter. Only 2/8 (25%) chose a weak and very weak tie. This preference for stronger tie strengths may be, as stated on part I, due to the fact that strong ties may feel more responsibility towards and task, and thus make an extra effort to make sure to not only deliver the binder to the next person, but to also think and pick the next alter because s/he was thought to be helpful, instead of just randomly choosing someone, like McPherson et al say. Further evidence is presented from the fact that, from those uncompleted chains for both Antonio and Susan, 100% of the weak ties only made it to one link from the starting alter, whereas 4/6, 66.6%, of the strong/moderate ties made it further than 1 tie. It was unfortunate that Antonio’s data for the tie strength for the 2nd alters was missing. However, as for uncompleted folders, there was a mixture of weak and moderate/strong ties, but even in this case, there seemed to be a preference for the latter.

One of the hypothesis that I brought up on my first blog dealt with the target’s race and how this could have potentially affected (or not) the success of the binder reaching them. However, since there is not information available as to the race/ethnicity of the intermediaries nor the starters, this aspect could not be analyzed.

As hypothesized in the first blog, the binders that were completed were mostly transferred to the target through someone in the same affiliation/department. Only 3/10 (30%) of them weren’t transmitted through someone from the same school as the target. As for the hierarchical transition that was initially predicted, I was surprised to find that it wasn’t the case in which there was a status descent, as Milgram and Korte’s study had stated. There were transfers from students, staff and faculty members, with slightly more student transfers that then latter two groups. Moreover, the hypothesis that people who had been longer at the Penn community would be more likely to make the deliveries wasn’t sustained either, since the length of time of the last alters varied considerably, even within people of the same affiliation.

Despite Milgram’s finding that there were individuals in one’s network that played the role of “principal point[s] of mediation between [one] and a larger world” (66), our data does not support this; there doesn’t seem to be any “funneling effect” (Korte and Milgram, 104). There was only one person, June C, present in Susan’s chains of binder, who delivered two folders to her. Since there is no further information about her, it is hard to determine the reason why she delivered two out of the eight binders that reached Susan.


There are several explanations for the failures of some of the binders. As Killworth et al state in their article, people are very inaccurate when choosing the right intermediate links. This may have led to some erroneous choices, which, in the case of Antonio who is part of a larger school, could have decided the folder’s success. Another cause might have been the fact that, since people are busy, the fact that there wasn’t anything rewarding for them, especially those in the latter part of the chain, might have been an extra challenge in the success. This is especially true for weak ties, since the delivery of a folder does take up time, and more importantly, individuals have to get together in order to pass the folder along: this might have been a turn off for those links who thought about passing the folder to a weak tie. Furthermore, the fact that undergraduates don’t have access to staff, faculty or graduate students that readily might have been a problem, especially if these were weak ties. This might have helped if facebook could have been used to contact these possible alters. Ellison et al found that undergraduate students use facebook heavily as means of keeping in touch and communicating with weak ties. Since the instructions only allowed contact and passing of the binder with people that one somewhat already knew (since there should have been several conversations out of the classroom with these individuals, and Ellison et al found that facebook is not good to initiate new conversations and create ties with strangers), the use of facebook could have been potentially beneficial for students when trying to make initial contact and/or to schedule a meeting. However, since this hadn’t been an available option, this could be an explanation as to why so many binders died with students in Antonio’s case.


Several causes for the success of binders can be accounted for as well. To begin with, the fact that starters were upperclassmen could have aided in the success since upperclassmen tend to know more people around campus, including both strong and weak ties, which according to Granovetter and Burt, can serve as useful information sources. This is further supported by the fact that the only two folders that reached Antonio were started by the super-seniors in our class; if Antonio was a hard to reach target, it would make sense that, under this line of thought, super-seniors would be the ones to know more people who could help reach him.


As for the success of my own binder, one reason that could explain this could be the fact that, knowing Killworth et al’s findings, I made a conscious decision to find someone who was a strong tie, since I wanted the person to make an extra effort in delivering the folder and giving the choice of the 3rd alter some thought, as McPherson et al have stated, as well as someone who knew someone within the School of Education. Moreover, the 3rd alter’s status as a student within the Education school might have been of potential benefit since Susan is an assistant faculty member, which means that she might have taught classes that are smaller in nature compared to big lectures, and thus gotten to know some of her students better. Furthermore, as Milgram noted on his study, “participants were three times as likely to send the folder on to someone of the same sex as to someone of the opposite sex” (65), and this is shown with my data: all five alters females, which could have enhanced the chances of the folder reaching Susan.

About November 2006

This page contains all entries posted to Social Network Blog - y1 in November 2006. They are listed from oldest to newest.

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