Social Network Blog - r32

Despite having a very biased sample, my data did seem to bear out many of the trends and theories that we encountered in this course. The first interesting thing I noticed was that the adults over 33 years of age knew on average 2.6 more people from the position generator than the college students. While this may seem obvious at first (due to the fact that as you get older you meet more people) it is interesting considering that all of the students surveyed go to a very prestigious school with many diverse departments. A possible explanation to counter this would be that age homophily (as proposed by Smith-Lovlin et al. in “Birds of a Feather Flock Together”) is playing a major effect here so that college students are mainly associating with other college students (who aren’t yet in the workforce) which is in line with Smith-Lovlin’s baseline homophily. Even though it is typical for strong ties to be age homophilous (which they definitely were in my study) weak ties on a college campus are often very age homophilous as well, considering most of the people making up weak ties will come from organizations, clubs, and classes within the university. In this setting, college students will not have as diverse a weak tie network and thus, it will be a lot less likely that they will have had any contact with people in these various jobs. An interesting related finding is that female college students knew more than twice as many people in these jobs as male college students. This phenomena doesn’t seem to be covered in the literature, but a possible explanation is that the specific jobs listed on this position generator are gender biased and more likely to be known by females (e.g. hairdresser, store clerk, dry cleaner). Beyond this rather unsatisfying explanation, this result is difficult to explain and is in need of much further research. In any case, college students appeared to have much lower social capital than adults, even though the students come from a prestigious school. While network size usually shows a curvilinear pattern with age, (Social Isolation in America) it’s interesting to note that in this case the most elderly person (who also had the lowest educational level) knew the most people in these positions, and while the sample size is tiny this helps bolster the college hypothesis, that age homophily is preventing students from having high “social capital” as defined by the position generator.

Interestingly, when comparing adults on the same measure I found that females on average knew fewer people in these positions (females: mean=7, males: mean=10). This is in line with Lin’s finding from Taiwan that men have better access to social capital than women (considering women are still not as well represented in the workforce). Furthermore, we see in this sample that among the women those in the baby-boom generation (late 40’s and early 50’s) had many more social contacts in these positions than the 71 year-old in this sample. While this sample size is obviously too small to make any significant findings, the fact that many of the middle-aged women had so many contacts in there positions might suggest a change, (reported in McPherson’s “Social Isolation in America”) in that women are catching up to men in terms of how many contacts they have outside the home. Furthermore, this may be due to education effects. This same article explains that now only those with bachelors and increasingly graduate degrees are the main connectors outside of the kin network, and in my case all of these mid-aged woman had attained at least this level of education (1 bachelor’s, 3 graduate). Men did know twice as many people in the “highest prestige” jobs, and may still have the highest reaching networks, however again it’s hard to say that this is significant with such a small sample size. Thus, many variables could be at play here but they do seem to be leading to the fact women are catching up to men in terms of social contacts and social capital outside the home. If Granovetter is right, and more social capital and weak ties really do lead to easier access to more jobs, then these finding make a lot of sense, considering the continually rising position and number of women in the labor force.

At the same time women still tend to be the kinkeepers in society as described by McPherson in “Social Isolation in America” and Wellman in “The Network Community.” This was quite obvious in my sample in which females listed 25 kin as people with whom they discuss important matters while men only listed 9 kin. In keeping with the trend described earlier (that women have larger networks), women were much more likely to list more confidants than men, with all women listing at least 5 confidants (except 1 outlier who listed 0). Compared to 7 women, only 3 men listed 6 confidants. Thus, women’s networks seem to be much larger with regards to strong ties and just about equal with regard to weak ties. It was interesting that among my participants only 1 person listed no one with whom they discuss important matters and everyone else listed at least 3. In the McPherson “Social Isolation” article, 25% of people were isolated compared to 5% in my sample and many people only listed their spouse. My data does not replicate that, but a possible explanation may be the overall higher education and prestige of the subjects in my sample. Typically, education increases network size overall and interestingly, in my sample, the only person who listed no one in this category was tied for the lowest level of education among the group (high school graduate). My data does however replicate the finding that spouses are seen as close confidants among most people, with 8 out of 10 people listing their spouse as someone with whom they discuss important matters. The only exception was an elderly couple who happened to have been fighting a lot recently!

Furthermore, my data seem to convey the theme that the entire nature of community is changing from geographically defined to network based. As Wellman shows in many of his articles, community is much easier to establish and maintain on a personal level, now that there are new technologies that can connect us so well, despite our physical location. In my analysis I found that 25 close confidants lived in the same home as the participant and 24 lived no closer than in the same country. Those in the categories same neighborhood, city, and state all had about equal numbers with 14, 13, and 12 respectively. This seems to show a shift where community has moved inside the home, yet people are still staying connected to their loved ones all across the country. On the one hand it seems that networks and communities are becoming very privatized and spouse-oriented, as Bott and Kaljimn explain in their articles. My data seem to show that many very important contacts occur right in the home and that often those who live in the same house (or have lived in the same house) are communicating the most via other mediums of communication as well. However, on the other hand we see that networks are extending far beyond their geographic boundaries. An obvious explanation in my case is that many college students have friends and family all over the country, and combined with the rapid diffusion of new technologies it is much easier to keep in touch. In Ellison’s, et al. article for example we see that the popular online site facebook is helping contribute to people staying in contact with their high school friends. While our study didn’t measure facebook contact, it was clear that college students were using IM dramatically more than adults, in order to speak with people all over the country and on their campus. This is in agreement with Baym’s analysis of college campuses which found that students use the internet as much as the telephone and less than face-to-face interaction for long-distance relation, yet also use the internet for short-distance relationships as well (though not as much as face-to-face). The only major difference seems to be that in that study, e-mail was the main source of communication, whereas in my study kids seemed much more inclined to communicate more days of the month via IM, when contacting their friends. My hypothesis is that e-mail has become a very institutionalized medium, connected specifically with school and business, and I feel that many people try to keep their personal life separate from that. Plus, IM makes it much easier for immediate emotional support which is a major facet of close relationships. Therefore, I think that the discrepancy can be explained in the fact that my data asked for close social confidants rather than total e-mail/vs. IM usage. Otherwise, it would make sense that e-mail was the most frequent internet medium among college students. Furthermore, I think the advent of cell phones has made it much easier for families to stay in touch with college kids. Among those who reported their parents as close confidants many talked to them via cell phone a majority of days each month. Interestingly, all of the college-aged participants listing parents as close confidants were female and this may just have to do with the small sample size or may show a larger social trend. This would need to be studied further to garner definitive results, but I still believe that cell phones make it much more likely that college aged kids will talk with their parents more, despite their physical separation.

Finally, these trends seem to show that we can receive social support no matter where we are on the globe. New media give us access to friends and family around the world who can provide emotional support, large services, and financial aid right when you need them (Wellman, “Different Strokes”). While neighbors and those around you still play an important role, they are not the only sources of social support available and this is evidenced by the fact 44 close contacts resided within the same neighborhood but 49 were located outside of the immediate neighborhood. Hence, Wellman’s data that shows that neighbors do not provide significant amounts of social support seems very plausible. It seems even more plausible considering the fact that many of the people considered “neighbors” were based on a college campus where people live literally within feet of each other and people come with a blank slate (meaning they often know no one). This overall geographic diversity seems to lead to a lot less network density than one would expect within a family or a closed community. The data show that an almost equal number of close confidants are especially close or strangers with other close confidants (53 and 52 respectively). Furthermore, 113 people who are close to the participant know others that are close to the participant but are not especially close. The invisible triad that we saw with Granovetter is thus, shown not to be true at all, and we see that in this digital age our confidants aren’t confined within one tightly packed network. Instead, we have access to a huge and diverse outside world and while much socializing may now take place in the home and be considered “private” we see from this data that in reality (as Wellman stated in the first reading we read) our communities have simply changed to encompass our own networks around the world. We can get all of the social support we need from all of the traditional sources no matter where we happen to be, and thus maybe the “privatization” of community is not truly a social deficit, but instead just a social change.

This data obviously needs to be taken with a grain of salt. As I have alluded to, the sample size was tiny and entirely biased as all of the participants were part of my personal network. Demand characteristics could be a huge factor here because many of the people in the survey are my friends and may want to just put down answers that they think will be “good” data. Furthermore, as we see in the literature there are many problems with the measures in the GSS and position generator themselves. As Van der Gaag et al note, the position generator is not very good at giving specific measures of social capital, and potentially the positions listed in this survey would give much different results than another list of positions with the same sample. A lot depends on people’s experience, field, education, and age, as I saw through some of my data. Furthermore, as noted in the Hampton and Marin paper, this study can be burdensome. People do not have a lot of time on their hands and often just want to get the survey over with, without really thinking about the questions. Additionally, some measures (such as number of days using each medium) are very hard to measure accurately with self-report data. Thus, while this survey may not give us perfect results that we can use to further prove the theories we’ve learned, it does provide some interesting findings and shows that social network measures as they stand are far from perfect.

According to this week's readings, this song lyric from Santana's "Maria, Maria" seems to hold true in actual studies of real-world phenomena. These reading seem to wrap up everything we've studied about social networks so far and used concepts such a multiplexity, homophily, range, volume, and prestige to show how these things divide us and how the current society we live in just tends to divide the rich and the poor even more. While we often tend to think of poverty in terms of lack of economic and consumer resources, these articles and the course in general seem to show that there's an extremely important social component here as well. Considering that we're social creatures and that we naturally tend to network in certain ways (for instance via homophilly) we're led to one of the major problems/questions we've encountered in this course. The question is that given the way that humans network how they do, how are we supposed to intervene and change a system that supports division and inequality? And does it even matter whether or not we do?

In the Fernandez article, they studied network data from a study of poor communities in Chicago, to determine if the ghetto class and extreme poor are socially isolated. They found that this is indeed the case varying over a variety of factors. For instance, ghetto men and women were much less likely to participate in organization and know people of the mainstream stable culture and black women were cut off from almost everyone. This has interesting connections to the Putnam interview we heard earlier in the semester which argued that there was a decline in volunteerism in America and that this was leading to social isolation and possible negative consequences, such as more crime, illegal activity, and social unrest (much like we see in the modern day ghetto). Fernandez et al. also showed that nonworking poor are much less likely to have a spouse than others and that they were less likely to name friends. We also see that increasing poverty in the neighborhood can make these factors even worse for the nonworking poor. This brings up some major concerns considering McPherson's article that very few people talk about important matters with anyone and when they do they often talk to their spouse. The status of poverty and social unrest in many of these neighborhoods is perhaps a testament to the importance of having this very important dimension in your life (of having close confidants). As we saw last week (Dickens), having close confidants is correlated with reduced likelihood of having further heart complicaitons after a heart attack, and in this case lack of close confidants seems to be correlated with increased poverty and misery. If this lack of close confidants really is diminishing trust and causing all of this unrest then we have a clear problem in society that we need to try and fix. Another interesting finding is that we see that black nonworking poor males rely more on kin than do black nonworking poor women and that neighborhood poverty tears men away from their kin while it brings women closer with their kin. This is very interesting considering Wellman's idea that women are the kin keepers, yet among the poor this doesn't seem to be the case. Women's relations with kin do however seem to alter with the neighborhood and in this case the data resemble Bott's in which women in working-class neighborhoods were getting much more kin support than men. The fact that this study can raise so many questions based on past readings shows that there are still many questions and answers needed in the field of social networks and that despite all of these very well-designed and carefully carried out studies (as was the case here) it's very hard to determine definitively what affects our networks in the real world. In any case this paper is strong in it's ability to explain the data and then clearly explain some implications and further research that will lead to the appropriate findings to affect policy and look at poverty dimensions more specifically (rather than just taking an aggregate).

The second reading by Marsden relied heavily on ideas from Granovetter about weak ties and their help in finding a new job. As we've discussed in class, there is a lot of debate around this topic and this is clearly shown in the article. Mardsen et. al question and reject the fact that tie strength is the only factor that's important in determining job-matching and that there are many other factors interacting as well (availability of social resources once they have information, the intersection of employee information seeking with employer information distribution attempts). Thus, just like the Fernandez article we see that there could be a major effect based on the interaction of several variables and this further extends the work of Granovetter, Lin, and Bridges. This article brings up the important point that there are no simple solutions to these major social network problems and issues (i.e. the affect of weak ties) and shows that in the real world too many complexities and factors influence the final outcomes. Rather than invalidating prior research this simply acts as a building block to keep us aware that there is no one magical solution to any problem and that while theories are nice and neat there is always more to consider. I think this article did a particularly good job and noting both the merits and deficits of these prior experiments, while clearly showing their value (even if they couldn't explain all phenomena). I also find this article interesting because it seems to show that the structure of our social networks inherently produces inequality, because those with more prestige have better access to others with more prestige and thus have a clear advantage among the competition. As we see here, prestige of the contact can be very important in obtaining a job and while the studies on wages were inconclusive it shows that people with more occupational prestige and greater resources are at least much more likely to have access to more prestigeous job information than others. This seems to show that although some things are very dependent on how you do on the job (i.e. wages), prior social resources inherently privelege those that are already priveleged and make it much harder for those with less social resources to rise up the ladder. This makes a lot of sense if we compare it to the important points of the Fernandez study, which show that the underclass typically has very few social resources. With this being the case we have a fundamental problem in our current system and these studies make clear we need to continue to study these phenomena and work towards a social solution that takes into account all of the complexities we see in the real world.

1. Based on your reading of the Fernandez study do you think it's possible to ever eliminate or at least greatly reduce the social isolation phenomena we see among the poor or is there always going to be a subset of the population socially isolated? If yes what are some ideas you have about reducing the social isolation? If no why do you feel this is impossible?

2. How do you reconcile the fact that while these studies have shown us a lot, it's very hard if not impossible to incoporate all of the complex factors involved in social networks in our studies? Are any individual studies playing too much of role in our knowledge of social networks or do you see the literature as fairly balanced and working together and building on each other to try and find a larger solution to these core network issues?

As with Steveson's data, our class data was very interesting and seemed to disprove a lot of our prior hypotheses about how this study would run. The first thing that was very striking was just how different the success rates were based on the target person. The fact that only 25% of Antonio-bound folders made it while 80% of Susan's made it, convincingly disproves my hypothesis from Part I that the target characteristics would not matter that much in whether or not the folder would reach the final target. The results seem to show that Susan is much easier to reach than Antonio and at a shorter average length (3.25 vs. 4.5). This leads in my mind to two possible conclusions as to why this is the case. The first may be that Susan is much more prestigeous or well-known in the Penn community and thus according to Monge has a higher in-degree within the community. The other is that the Susan Yoon group was significantly better at selecting their first target than Antonio's group. When looking at the data, there are a few dimensions that seemed to significantly differ when regarding characteristics of the first alter. One interesting difference is that the Susan Yoon group was much more likely to pass the folder first to a member of the same sex (8 out of 10) than the Antonio group (3 out of 8). Another difference seemed to be that (6 out of 8) people in Antonio's group passed it first to fellow students (while 1 passed it directly to faculty) while only 5 out of 10 of Susan's group passed it first to another student (and 4 handed it to faculty). As far as the first number is concerned, the literature seems to make no mention that choosing a second alter of the same sex increases final success. Milgram simply says that exchanges are much more likely to occur between member of the same sex and Killworth's paper on accuracy simply states that all network members only choose the correct alter (in order to reach the target on the shortest path) 50% of the time, without mentioning if same-sex passages were typically more accurate and/or successful. Thus, this doesn't seem to explain why so many more folders reached Susan. The second fact is interesting in that 3 out of 8 completed chains in the Susan group were handed first to faculty and then proceeded to Susan strictly through faculty. This is very similar to the Stevenson study in which 88% of the time, a faculty member, grad student or staff member who received the folder was able to complete the chain to the administator. However, in my case (with Antonio) I was the only one in my group to pass it to a faculty member and my chain died after that faculty member. Thus, there are no guarantees that passing it to a faculty member will necessarily be more likely to lead to a completed chain.

This data seems to suggest that the most likely reason for the major difference in completion rate had to do with the characteristics of the target. Unlike the Stevenson study, our study involved reaching a facutly member or staff member rather than just an administator. Thus it makes sense that our average chain lengths were longer than their 1.25, considering that administration is typically more central to the university as a whole. In our case Susan (a faculty member) seemed much easier to reach than Antonio (a staff person). While the sample size is very small, the data show that faculty members, students, and staff people were all represented as the final link when the target was a faculty member, yet only students represented the final link when the target was a staff person. A possible explanation is that faculty (being more presitigious) have a much higher in-degree than staff people and are much better known throughout the university community. This would make sense considering faculty teach (and thus have contact with students) and work together in departments that are often interconnected (which gives them contact with staff and faculty). Staff members on the other hand (like Antonio) are much more likely to only be connected to those in their department, and further only with students who specifically work in their department. This explanation is very convincing and plausible considering that Antonio has actually been here one more year than Susan, and common sense would dictate that he'd be able to make more contacts within an extra year. Clearly though, in this case affiliation of the target seems to be a much more important determinant of success than the amount of time the target has been a part of the community.

My personal data makes much more sense when I consider the fact that affiliation of the target is so important. I figured that passing my folder straight to a faculty member would make it much more likely for the chain to reach Antonio, than first passing it to a person of any other affiliation. However, my chain literally stopped after Diana (despite the fact that I thought the chain would only take a week and a half and go through four links!). Unforutnately, I was left with a dearth of information, considering that the postcard Diana sent in was not postmarked and thus, I have no idea as to when she got around to doing the task. However, assuming that she is trustworthy and didn't just leave the folder in a pile and forget for a few weeks (which is a possibility), it seems that once she passed it on the next respondent was either just very lazy or indifferent or just completely clueless about where to turn next to find a relatively isolated staff person. This was not the case at all in Susan's group where once the folder reached a faculty member it reached the target 75% of the time and there was only one case like mine where the chain stopped after the first exchange. Furthermore, unlike the classic Milgrim studies only one of the penultimate alters was responsible for delivering more than 1 folder to the target (June C. who only delivered 2). Together all of these data suggest very convincingly that I was completely wrong, and that affiliation has a major impact not only on the length of the chains but also on whether or not they were completed. No matter the characteristics of who you pass it to, it seems much easier to reach a typical faculty member than a typical staff member.

Another interesting finding is that while the completion rate of Antonio's group was very comparable to Stevenson's data (25% completion for Antonio vs. 27% in the Stevenson study), a much higher percentage of folders made it to Susan (80%) than we see in any of the literature. The highest completion rate we see in Stevenson's literature review is that of Lundberg, who found that 57% of folders reached the target in an organizational study with most studies in the larger society averaging between 20 and 30% completion. Furthermore, Stevenson predicted that only 50% would reach the target, with the target working in the same building as many of the participants! Thus, it's very surprising that so many people were able to reach Susan in a university community of more than 20,000. This is very hard to explain, even if I am correct in asserting that her affiliation as a faculty member leads to a much greater chance of the folder reaching her. A possible reason for this is that there was some very close connections between the departments of many of the starting students and the Graduate School of Education. Unlike Stevenson's study our folders were not handed out to starting participants at random and instead we had a large proportion of our starting participants sharing the same department and school (in fact only one participant was not a communication major and all were in the school of arts and sciences). Thus, due to our starting characteristics the study may have been biased considering that comm students, staff, and faculty are much more likely to have connections at the school of education (which houses many undergraduate classes and likely shares some common study interests with the communication deparment) than they are to a medical institute that is not as closely related to the department and that many students and faculty have never even entered. Another potential bias that differs from Stevenson's study is that the students in this class who started the chains, already knew the basic structure and "tricks" to these studies, and were furthermore probably more motivated to follow up with their first contact than a random student would be. I, personally was not as interested in making sure to remind my contact to complete the task as I wanted to see what would happen naturally and if the folder could really progress on its own. Clearly, in my example my folder seemed to follow the same dead-end path as most of the folders in the Stevenson study. An interesting follow-up to this study would be to ask how many people in each group communicated with their 2nd alter in order to remind them about this project or check on the status of the folder. Then we could see if this bias has a major effect or not. In any case something must be accounting for this tremendously high success rate with Susan Yoon and these seem to be the most likely causes based on my prior experiences and the data.

Furthermore, in the Antonio group we see that the two chains that were completed were started by 5th year students. Stevenson's study showed that while there was a clear isolation effect for freshmen in the sample, seniors starting the chain were less likely to complete it than juniors and sophomores, and most chains that were passed from student to student went to upper-classmen before reaching the target. Our data don't seem to match up, especially considering that these two participants not only passed down (which nobody in the Stevenson survey did) but both passed it down first to sophomores! In one of the chains three sophomores were involved before the folder reached an upper-classman. Even though we can expect that 5th year students may pass down (considering most kids graduate in 4) it is very intriguing that they passed so much lower and furthermore that it worked. We also see in the Susan group that more students passed the folder on to younger students than those in their same year and none passed it higher! Perhaps again this is due to the bias that most of the class consists of seniors and juniors and hence it's much harder to pass it higher. However, the fact that more people passed it lower and we had a better overall success rate than the Stevenson study really challenges the notion that upper-classmen are more involved in these transfers and more vital to their final success than under-classmen.

Finally, it's important to point out what this study says about tie strength and who we trust and expect will be able to best help us with this task. As I stated in part 1, Granovetter would say that it's important to utilize weak ties because they are the best outlets to diverse resources and social circles. Burt however, would note that while structural holes are important, trust is also very key in asking for help in an endeavor. In my case, I was hoping that trust would win out over a weak tie, and unfortunately with no postmark on the postcard I received, I have no way of knowing if Diana was actually trustworthy or if the next alter simply was clueless. When considering all of the data it seemed that most people also preferred to hand off the folder first to a moderate-very strong tie (13 of a possible 16). Six of these chains were completed (with two data points outstanding) while only 2 delivered first to very weak or weak ties were completed. This is evidence that strong ties can be very helpful in beginning a task like this and are usually quite trustworthy in helping you out. An important potential weakness with this result is that in much of the literature there is simply a dichotomy of strong and weak rather than a gradual five-point scale. With a scale like this, it's very hard to distinguish what a "weak tie" is in the Granovetter sense and thus we see that simple categories can have a major impact on our interpretations of data. Regardless though, this shows that there is some ambiguity about the best way to go about choosing a second alter and for that matter choosing the next person at any part of the chain.

In conclusion, the take home point from our University experiment seems to be that target characteristics really do matter. While our sample size was very small and clearly biased in many ways, these data offer some very intriguing results that are worthy of further investigation.

Part 1: http://www.mysocialnetwork.net/blog/481/r32/2006/09/small_university_part_ia_big_d.html

This week's readings focus on health topics as they relate to some of our previous findings about social networks. All were researched based and prescriptive in nature in that they seem to give the social keys to preventing some of these serious health problems. While these studies are informative ,the research procedures sometimes have questionable ethics. As we see in many research fields it's hard to know where to draw the line. In any case though, this week's readings are another good example of how our studies are relevant to real-world phenomena.

The study by Cohen and Brissette explored the idea of how social relations and network patterns can influence your probability of getting a cold. They provide a brief but integrative history of different theories of social integration which is really helpful in that it gives the reader a great lens through which to view their current findings. The debate in the literature about whether or not numerous social roles is positive or negative was particularly interesting and has a lot of relevance to our lives as busy Penn students. While it has been disproved that this is harmful (according to the paper) I would be interested and seeing if there is a line where taking on too many social roles becomes more stressful than helpful. I would have liked to seen this explored more because stress caused by having too many social roles could potentially have negative health consequences (as opposed to a single stressor which they described in the article). In this case though their study seemed to show that social diversity (not size) was the key to being less susceptible to the cold virus. It served to bolster the findings we've seen through Granovetter and Burt that social diversity is integral to a successful life (whether that means getting a job or staying healthy). On the other hand this seems to be another example of why the size of an alter's network is not as useful in our studies of social networks because it doesn't seem to effect our lives much. Rather than doing phone book studies, this study implies we need more qualitative measurements of who we know and what groups we belong to. Furthermore, while the study hypothesizes why diversity might specifically reduce health problems (e.g. changes in hormone levels, more social controls) it finds no support and thus much more really needs to be explored to explain why exactly we see this effect.

While this study was very thorough and set strict and objective measures, (e.g. staying further than 3 feet away from others, measuring mucus rather than self-reports) I feel that the ethics of this survey are questionable. While they did mention that the subjects were in relatively good health, it's very questionable whether it's ok to purposely infest viruses in a human being (even for research's sake). It's interesting what the researchers found, but with so many questions and holes left in the research it's hard to justify that this study was ethical and thus neccesary. This particular design allowed it to be much more controlled, but it's still very troubling to ever purposely infect people and I think the study should have brought up this concern and justified it better in the write-up. Also, while the study was definitely burdensome I think it was very smart to take objective measures of the mucus. As we saw in Hampton's paper patients can get bored and frustrated with a simple name generator and obviously this is much more intense and has the potential to lead to much more self-reporting error (which is a questionable measure to begin with).

The Dickens et al article, on the other hand deals more with the importance of strong ties to health rather than pure number or diversity of ties. It shows that heart attack patients who have at least one close confidant are much less likely to have further heart complications afterwards. Again we are left with the fact that we're not sure how the social facts connect to the physical health but the study was strong and well carried out, and is thus pretty convincing that a relationship exists. I think that despite the self-report style of many of the questions, this study did a great job in collecting accurate information and including in the "confidant" measure the ratings of frequency and important matters (rather than just frequency which we've see isn't always a great measure). This study is also interesting in that compared to the Cohen study it seems to suggest that a different social relationship is more critical for a different (and seemingly more serious) health concern. In fact, it makes no mention of social diversity and instead just says that having people that are close is much better than just having a lot of people in your life. It's very hard to understand both cases considering we don't know the connection between social and physical elements, but taken together these studies seem to imply that both a diverse set of ties and at least one close confidant are the most effective social measures in remaining healthy and happy. Thus, you need Granovetter's weak ties and McPherson's warm fuzzy hugs in order to be in the best social position that leads to the least isolation and the highest sense of self-worth. Furthermore, it's important to note that while the study does seem a bit unpleasant to carry out and the subject matter is often morbid, I felt that this study was carried out in a perfectly ethical way. While it's obvious that no one will purposely put a research subject in cardiac arrest, I feel that there's no harm in obtaining information from those who have experienced it already, as a way to possibly help others in the future. In any case, the argument about ethics can go on forever but I think it's very important to consider in these health studies (which are much different than the methods we've looked at over the semester).

And now to the fun one...STD's in the midwest! The Bearman et al. article appropriately titled "Chains of Affection" studies sexual networks among adolescents to try and find patterns in their sexual behavior and find a better method to prevent the rapid spread of STD's. They found that in opposition to the established opinion (that a "core" is responsible for the spread of these diseases and the majority of sexual acitivity) that sexual relations occur more in a spanning tree relationships, which connects very many people with very little redundancy between each, in a long but fragile network. They also found an interesting rule in teenager's choice of partners which seemed to be a prohibition against dating an ex-girlfriend's new boyfriend's ex-girfriend (and vice versa). This rule was a very creative step on the behalf of the researchers. By finding the significance of this rule (even without explaining why it occurs) we get a much more complete picture of what's actually happening in these findings and a very helpful tool in designing interventions. Furthermore, I think it was impressive and creative how they were able to attain anonymity and still get good results on a very sensitive subject. I have a feeling this really helped improve the accuracy of the results. The study was also very strong because it gave a clear, yet easy way to intervene and fix the problem. In many studies we've seen researchers prescribe very vague or basic outlines on how to help and most often call for more research into the topic. While this study was not perfect (e.g. it's not completely generalizable) it was very comprehensive, made a lot of sense and very clear in its final message. The only question left is whether or not the solution is economically feasible and will really work. This needs to be tested further and one must consider that the quality of the education can't deteriorate simply because it's being emphasized en masse rather than with specific groups. In any case whether it works or not, it brings up a very good point and something that's important for anyone planning an intervention to consider. Thus, not only is does it catch your eye, but it also provides useful information that was carefully and creatively obtained.

Questions:

1. Considering the nature and seriousness of the heart attack vs. the flu can you argue that having close confidants is more important to better health than diversity? What are some arguments behind your position and what are some possible oppositional arguments?
2. How important is it to consider ethics in these research studies? Do you think it's ok to ever infect someone with a virus (no matter how easy it may be to cure in that day and age) for the sake of research? Why or why not?
3. Do you think there is an upper limit on how many social roles you can fill before becoming more overwhelmed then self-fulfilled? Also do you think that quality of the "social roles" in anyway affects whether you're happier or more stressed or do you think it's all about pure number? Please explain.

1. The 5 people I interacted with the most often were Jenna, Alex, my mother, a tie between Max and Don and then my dad. Jenna is my girlfriend of a little over a year and we have a very close relationship. We often use new media to communicate with each other and talk to each other throughout the day every day. Thus it’s not surprising that I used new media to communicate with her nearly 4 times as much as I did anyone else. I would consider her my best friend and I give and receive many types of services from her (from companionship to emotional support to small services etc.). Alex is the programming vice president at University Television (an organization which I am the president of). We’ve been working in this voluntary organization for over 2 years now and have developed a fairly close and trusting relationship (though one that’s mainly limited to organizations affairs). I usually speak to him every day either by phone or e-mail. Thirdly, my mom and I have a very close relationship and typically communicate on the phone once or twice a day. We rarely use online media and rarely spoke via cell phone when I lived at home but over the past three years we’ve kept up a pretty steady pattern. She’s a very caring mother who can help me out with almost anything (especially small/medium services and support). Max is the Operations Director at the television station and someone I talk to a lot to deal with technical issues at the station. I typically talk to him via e-mail but also use the phone for more pressing matters. Finally my dad and I also have a very close relationship and typically talk on the phone once a day. Often I don’t get to talk with him as much as my mom because of the nature of our schedules, but many of our conversations are of fairly long length and I tend to discuss a lot of important matters with him. He’s very insightful and gives me a lot of advice and emotional support. I also spoke with Don a lot over the phone that week who is the business director at the television station. Typically, I don’t communicate with him as much but this week in particular there were some pressing issues that needed to be dealt with. In regard to specific media I talked most on my cell phone to Jenna, Mom, Dad, Max, and then Alex in that order. As far as SMS I only sent two messages. One was to Jon who is one of my best friends and lives right down the hall from me (which is why he didn’t show up too much in this diary). He’s a fraternity brother of mine and a very strong tie. The other was to Will who is a producer of a show at the television station. With e-mail the people I contacted most were Diana, Don, Seth, Xiaoxia, and Alex in that order. Diana is my boss at work and we typically correspond about work related matter over e-mail. Seth and Xiaoxia are co-workers of mine under Diana and hence we also correspond a lot on e-mail over work related matters. With instant messaging my I talked most to Jenna, Elise, and Rachel K. in that order. Elise is my sister who attends Penn. I typically talk to her over IM and once in a while on the phone if we’re making plans. We’re not super close but we’re close and we keep in contact every week (although some weeks more than others). Rachel K. is a good friend of mine from a Jewish organization we’re both a part of and typically we talk online and give each other companionship. Finally, I included facebook message as one of the media I used because while I rarely use these messages I did message one person this particular week. Her name was Sheri and she is also a friend of mine from the name Jewish organization as Rachel. We’re not as close but I messaged her in response to a message she had sent me.

2. My data seemed to show many patterns in how I use new media. Most noticeable is the fact that I only corresponded with one of my strongest ties via e-mail. This e-mail was in fact a one liner that could have easily been a text message or instant message if I felt like it. This seems to show that I mainly use e-mail as an organizational/class tool and rarely (if ever) use it for support or personal reasons. This hypothesis seems to go against some of the data in the literature. For example, in Hampton’s “Sociability and Social Structure in the Age of the Internet” article, we see that 79% of internet users use the internet to e-mail family and that a large proportion do so for advice and emotional support. While I may not use e-mail for this support, I clearly do seem to get this support from my strong ties (most notably my parents and my girlfriend). This is completely consistent with Smith-Lovin’s findings that important matters are discussed most typically with a spouse/partner (in this case I exchanged the most emotional support with my girlfriend). Also it seems to fit with Wellman’s “Different Strokes for Different Folks” in which he claims that the parent/child relationship seems to be the most broadly supportive of all types. This is further shown in my data by the fact that my parents offered three different kinds of support over this period (emotional aid, companionship, and financial aid) and although it is a bit rare to report high companionship ratings with parents, all of the other data seem to support existing hypotheses.
I feel that in my case I generally prefer the phone to online communication when discussing important matters and/or when contacting my strong ties. Perhaps my e-mail data are inconsistent due to the fact that I am part of many organizations and I often see e-mail more as a burden or a way to get things done, rather than something used for personal issues. Considering the data in the Hampton paper is from 2001 I wonder if now that e-mail has become the standard in organizations and schools, it will be used less and less as a means of obtaining support and advice from strong ties. Perhaps we’re just too overflowed with it that once we get all of our work done we just want to get away from it. In any case I think this is something that needs to be examined closely considering how rapidly e-mail has been adapted (even if my data is a mere anomaly). Furthermore, I think the fact that I spoke with my parents solely via mobile phone is an interesting finding. Considering they are the two people I talk to the most, who are farthest away from me, my data seem to show that I’m more likely to use a mobile phone than any other medium when communicating with those who are far away. A possible explanation for this is that I’m very close with my parents and find a conversation more personal and endearing when I can hear a voice on the other end. Perhaps by actually speaking with them it makes it seem that they’re “closer” and not just somewhere off in the distance. I wonder if this factors into many college students’ media use choices when talking to their parents (considering that many students have little physical interaction with family while actually at college).
Despite this intriguing possibility I tend to think that in my personal experience I just seem to prefer the phone when speaking with close ties regardless of distance. This is evident in the fact that the phone was my most preferred medium for my most frequent contact (Jenna) who lives only .25 miles away and who I see everyday. Also the fact that I preferred e-mail for weak ties who lived moderately far away from me seems to suggest that there’s no direct tie between medium use and physical distance, and instead this relationship is moderated by strength of tie. This is another interesting topic that needs further exploration because I hypothesize that with the rise of cell phones it has become much easier to talk with our strong ties that live further away. Whereas, a few years ago e-mail was the easiest and cheapest way to stay in touch, the rise of “free long-distance” cell phones has seemed to give us another easy way to contact distant close ties and a more personal one at that.
At the same time I found that while many of my close ties were maintained via the phone, instant messaging and e-mail tended to reinforce some of the stronger ties I already had. After all I only used IM with ties rated moderate or stronger and I supplemented some of my stronger ties with e-mail as well. This all seems to go along with the findings from Baym that strong online communications often supplement telephone and face-to-face interactions (which tend to be slightly higher rated in quality). Also in accordance with those findings I seemed to use instant messenger far less than e-mail. Although I used both media for significant interactions involving advice and emotional support, it’s hard to say overall which one contained more “significant” interactions as this is very hard to define. In my case, IM was used much more (proportionally) for personal support and enjoyment, whereas e-mail was usually more organization or school-oriented (in terms of type of support). As that study pointed out though, these patterns may be based on the fact that I’m a college student and they might not generalize to the real world. For instance, when I was younger I used IM much more frequently and for much more socially significant interactions than e-mail. Again, we see here that context seems to play a major role in determining these specific interactions.
Another interesting finding in my data is that I only spoke on instant messenger to females and that they are all close to myself in age (within 2-3 years). In fact, while I rarely use IM, I seem to use it most to talk to females and very rarely talk to male friends (unless I need some quick information). When this is combined with the fact that all of the people I spoke with online were strong ties and provided much emotional support in general, this seems to show that at least in my case, I often turn to females for support through this medium. The fact that I use females for support is quite consistent with Wellman’s data that women are much more likely to provide emotional support than men in the sense that “women express, males repress” (pg. 576). I think it’s interesting to consider that in my relationships with females online I’m much more likely to receive emotional support than with males (where the conversation is often very bland). In this particular week I did tend to also give and receive a lot of emotional support among males (though this was typically over phone or e-mail). However, other than my dad I rarely receive emotional support from any other males through new media. This week just happened to be an exception because there were some tough issues I needed to deal with at the television station. In general though these discussions about the station are more political than emotional, which is consistent with McPherson’s observation that males tend to discuss political issues with other males and that voluntary organizations are very often gender segregated.
As far as my interactions with those more than a few years older than me, I found that besides my parents I tended to prefer e-mail as a medium. In fact, I only found 2 other instances in which I interacted with people over 30 in my sample and these were both because I needed quick information on something (and hence chose the phone over e-mail). I think this reflects the fact that most people I know over 30 have jobs and check their e-mail quite regularly at work. Furthermore, I think that when speaking with older adults who are not strong ties, it’s much more comfortable to use e-mail, where you are able think through your responses and edit as you go. While this remains to be studied, I’m curious as to whether or not this trend is apparent among many college students, who presumably are less comfortable with adults and want to make a good impression while avoiding embarrassment. This would seem to be consistent with the idea that age homophily is very likely outside of confiding relationships (in which the embarrassment factor would likely no longer matter). However, this is still speculation and needs to be legitimately studied.
Finally, I saw very little distinction between duration of relationship and communication media chosen. My raw data might seem to indicate this, but when you exclude my parents from the mix, it’s very difficult to find any relationship. Instead, I feel that other variables such as tie strength, age, and gender were much more important in determining the medium I used. Also, I found it interesting that I rarely used facebook to communicate with anyone. I messaged one person about club related info but other than that I didn’t use the site to communicate with anyone. I wonder if this is normal, considering what an impact it has had on the college-age market. Considering the results of the Ellison article on facebook, my guess would be that typical college kids would communicate through facebook (via message, wall posting etc.) more than once a week, especially with old high school friends. The fact that I don’t keep in very good touch with my high school friends may be a major reason that this number was so low, as well as the fact that I relatively rarely use facebook (no more than 5 min/day on average).

3. As far as where most of these interactions took place, I had trouble distinguishing characteristics of ties that I was more likely to speak to at home vs. public places. For most of my strong ties, there seemed to be a fairly even split between the two locales. One pretty large difference that I did notice was that I spoke with Jenna 26 times at home vs. 14 times when not at home. This may result from the fact that I often talk to her for short periods of time online (using instant messenger) and this is typically always from home. At first, I predicted that I would be more likely to discuss important matters/receive emotional support at home (where I would have more privacy) but this turned out not to be the case. In fact, my I received pretty much the same types of support from Jenna no matter where I was or what medium I was using. As far as my parents are concerned, I spoke with my mom 5 times at home and 5 times elsewhere and with my dad 3 times at home and 5 times elsewhere. As far as the other people I talked to most over this period there were a few differences apparent but not many (Alex: 8 at home, 4 elsewhere, Max: 5 at home, 4 elsewhere, Don: 6 at home, 3 elsewhere). These results seem to show that I talk most to the same people regardless of my physical location. I did trend towards talking to the members of my organization more at home, but that could very well stem from the fact that I’m more likely to communicate with them later at night and on the weekends (considering it’s easier to reach college students at these times). This would be consistent with the fact that I spoke with Jenna more at home as well.
Another possibility as to why I seemed to have communicated more with these people from home is because as Wellman points out in “Physical Place and Cyber Space”, the rise of technologies and shift to place-to-place communities, have made men’s community ties become “tucked away in the home” (pg. 235). While this is a possibility, I have a hard time believing this explanation and in my own case and feel that my position as a college student really influences my results. My schedule is very erratic and there are some days that I’m home for a while and some days that I’m barely home at all. Also, considering that I can always communicate with others (via cell phone, e-mail, etc.) almost anywhere on campus, it’s not surprising that the characteristics of the people I talked to at home vs. in public spaces were pretty randomly distributed. If I were older and had a normal schedule of work and then home, I feel that I might see some big differences in my diary. In any case, the point seems pretty clear that the portability of new media means that we can maintain our contacts/ties anywhere at almost anytime. This may make it much easier to maintain weak ties/contacts considering that in many cases all of your ties can be reached virtually instantaneously. It is quite consistent with Hampton’s observation that new media give us ways to overcome the barriers of local tie formation. Thus, as a substitute for interacting solely in public places, new media give us a chance to reach people all over the world no matter where we are. We can be much more selective in who we talk to and how we get our social needs, and as my data show we can even be fairly selective in public places (e.g. by talking on a cell phone while walking down the street or doing e-mail in the Annenberg library). Thus, certain types of contacts are no longer reserved for just the home or just public spaces. Our social networks can be large and flowing with weak ties and we can decide who we want to talk to anywhere and at anytime.

So after a week off from the blogosphere, I'm back in action. This week's readings talked about the very popular topic of tipping points and diffusion of innovations. They also explored the search process in trying to find a certain network member or enclave in ambiguous circumstances (e.g. when trying to find information that's not publicly available such as where pot dealers live). These topics seem to be "hot" as Freeman would describe social network analysis in his article on social networks in cartoons. With numerous articles by Gladwell and the popular media it was interesting to get an academic overview on this topic. It is also very interesting in that it relates to real organization and has many implications for how and why organizations function the way they do. I think this week's perspective may help ease some fears about whether or not the study of social networks is really important in understanding the world.

The first reading (Tepperman) discussed the idea that there are many ways to conduct searches for deviance and that each involves a tradeoff. For example a breadth-first search (which follows every lead in sequential order as they arrive) is less efficient than a depth-first search (which follows the most recent lead until we arrive at a dead end). Furthermore, a heuristic search is more efficient than a blind search but also introduces the problem of searcher evaluation into the formula (which is not always accurate). This debate reminded me very much of the ones we encountered when reading about network measures. In that week the Hampton article on name generators seemed to imply that you can't get perfect data without burdening participants yet you can take some shortcuts to find a happy medium. As we discovered in that week, often the method used for a study is very context dependent and this seems to be exactly what Tepperman says in his article. The search process used to find deviance obviously is dependent on who's searching, their existing knowledge of the community and its network structures, and the restraining costs and factors. Furthermore, this article seemed to connect with the others from this week in making connections to tie strength and density in "closed" networks. They showed in this example that rural networks based on strong ties and kin are typically much more densely connected and thus deviant behavior is harder to detect (since it is harder to publicly promote a deviant cause amongst people who all know each other and accept certain norms). This falls much in line with Fischer's article "To Dwell Among Friends" where we saw that kinship ties predominate in less urban areas and we are more likely to find nonkin weaker ties in cities. Thus, it is easier to find a deviant behavior in these more open sparsely connected networks where deviance is more likely to be publicly noticed and/or accepted. In total I was not very satisfied with this article. I feel that it did a poor job of incorporating empirical data with theory and only provided a little data at the end of the work. I also found the descriptions of things like breadth-first searches rather brief and often hard to grasp. The differences weren't made distinctly clear with examples and it was hard to completely understand all of the theory the author was bringing into this argument. While I do understand the position this article takes and agree that choosing effective searches depends on the context of the situation, I feel that the specificities of these deviance search models were not well supported and often difficult to understand.

The Rogers article seemed to be an overview of the entire course so far. It incorporated ideas from tie strength, community, homophily, size and more and many of the theories we've studied thus far showed up in this paper. The goal of this paper seemed to be threefold in explaining opinion leaders, communication network structure, and this idea of a critical mass after which an object tips. This article did a great job of incorporating real world observations (e.g. the ya ya sisterhood, Paul Revere, the Cholera well in London) with the various theories we have seen in this class (e.g. Granovetter and his theory about the strength of weak ties). We saw in a much clearer way how social networking and structure are quite significant in our world whether we're rousing support for wars or stopping wide-scale disease epidemics. The point seems to be that when we take a step back and look at how we're all connected with each other we can have a much clearer picture of why things happen the way they do and then find ways to fix bad situations. Overall, this article was very thorough in explaining the concepts and how they were measured as is shown for example by the explanations of such items as the measurement of opinion leadership (e.g. sociometric measures, key informants etc.). Personally, I feel that while this text is a lot to take in at once, overall it has been the best article we've read at incorporating all the parts of social networks into one whole that makes sense and is well explained. It seems that it'd be helpful and easy to follow even for those who aren't social network experts like us :). The only thing I would have liked to see explored more was the connection of critical mass and opinion leadership to the internet. Considering the last few weeks I think it's important to consider how the internet effects all of these things in addition to social networks. I wonder if it's easier to spread a word of mouth idea over the internet or whether it requires actual interpersonal contact with people you can actually see and trust. Furthermore, I wonder if something as innovative as the internet effects the entire structure we see outlined here (see quesiton below).

Finally, the Burt article took an interesting stand on the diffusion of innovations. It showed that within a closed network equivalence determined contagion while in the bigger system of all networks cohesion determined contagion. Thus he argues that opinion leaders are not necessarily at the top of an organization but are instead more on the fringes. He seems to say that a president or organizational head is most effective when he/she can bridge the gap between his/her organization and others so that new ideas can flow in. In this way they accumulate power in a sort of tertius type of way because they directly control the flow of information. I found this article to be very well supported and thorough as well. The use of an anecdote and connection back to it at the end of the article made it very easy to follow and attracted my attention right away. It also showed a clear connection to the real world that took place between very respected professionals in our society and thus seems that much more powerful (the anecdote about Welsh). Not surprisingly this article relates very much to the structural holes/weak ties arguments that we saw in week 3 with the Burt and Granovetter articles. However, I think this article did a much better job of incorporating theory with results than these previous papers and like the Rogers article made the key points in a clear and concise manner. The implications of this article are striking and very relevant (particularly to people who are very involved in organizations). It seems to suggest that the way for an organization to benefit the most is to have the leadership put much of their effort into forming cohesive ties with outsiders and then simply disseminate the new information to those in the organization (and let the information spread itself). This is an interesting take on things and from my personal experience seems to make organizations run the most smoothly.

Questions:
1. What role does the internet play for opinion leaders and word-of-mouth epidemics? Typically information would come from the media and then flow from opinion leaders downwards. Does the internet change this structure or does it just reinforce this structure with the only change being that the internet is the medium of information exchange in both cases (i.e. from mass to opinion leaders and then from opinion leaders to the public).

2. Do you think organizations run the most smoothly when the upper management is mainly concerned with forging social relationships with others or with mainly focusing on internal affairs? How much help do numerous social ties really provide in the institutionalized world and are they as important as Burt seems to imply?

The title of my entry is a really good question. All of the readings from this week were centered around the theme of whether or not the internet makes us more or less social and how it affects our networks as a whole. As with radio, television, and the telephone before it new technologies clearly play a major role in shaping our lives and how we socialize. However the readings make clear that the internet seems like something much bigger to many people and that it's best to stay on the side of caution when evaluating whether the net fundamentally changes our social networks or not.
The Kronholz article shows an example of how a real-life experiment can get way out of hand and seems to support the idea that the internet is fundamentally different. While short, it was very engaging and seemed to imply that the internet has a major effect on how we can network. I think the article used good examples in showing the diversity of people who e-mailed her and made it clear just how connected the internet makes us. It reminds me of the Milgrim findings about the small world (albeit being not really planned or organized) in the fact that it generates a a critical question and promotes much further study. However, while the study is clearly general interest and not academic it is disappointing that this experiment can't really teach us too much about actual social networks. I think the important thing in the study is that it's both shocking and leads us to believe that with the internet it's possible to expand our networks greatly and broadcast information to the world. Also being a real-life observation of a simple high school experiment this observation seems very realisitc and something that could reliably happen if anyone of us sent a chain, unlike the often artificiality of a planned experiment. The only question I'd have is "Would this experiment hold up in 2006 with so many people so averse to SPAM and chain letters?" Part of the problem with the internet is that it has changed things so quickly that it's hard to track, just as we talked about when we discussed appropriate network measures and how networks constantly change.

The Wellman article seemed to expand on his earlier readings about Communities and Tie Strength. Again he employed the idea that community means something different than just living close together and effectively explained that the internet is simply another communication media in helping us expand our growing far-reaching communities. Wellman's analysis is strong in that it realizes that most of the debate around this issue comes from pundits rather than scholarly research and that research is needed in order to draw real conclusions. Similar to the other readings (and even more so) Wellman recognized that the internet is just another factor affecting social relationships and cautioned that it didn't fundamentally change anything. He even argues that internet based relationships can be just as strong/multiplex/diverse as face-to-face relationships. For example, he draws from his earlier East Toronto study on tie strength to show that in real life we get different things from different strong ties and this very much parallels the environment on the internet (in response to critics who think strong ties over the net aren't possible). His analysis was very similar to that of Hampton who took the argument one step further in thoroughly explaining how the internet could be an important tool in fixing many of the community problems we've faced in the past (because of its relative ease and speed in reinforcing relationships with those close by). His article is very strong and thorough in its review of the literature and empirical studies (like Netville). It was particularly convincing considering that he cited studies from both sides of the argument and showed why those going against his hypothesis were weaker and harder to prove. While both of these papers make good use of evidence it is disappointing and quite apparent from Wellman that many conclusions drawn are based on anecdotes. While I think Hampton did a good job of incorporating new data into the review I think much more research and time is needed to see if we can make some more legitimate observations about how the internet effects communities.

The other two articles (Baym and Mesch) seemed to take a slightly different stance in arguing that online relationships were not as intimate or close as in-person interactions. They both concurred with the previous articles that the internet was one part of a diverse range of media used to contact our alters, yet weren't convinced that the internet could be helpful in promoting new strong ties and reintegrating community. The Baym study is interesting because it shows many of the issues we discussed last week. As argued in the Zwijze-Konning article diaries use showed a better picture of total load of significant relationships and gave a representative sample of many relationships as they took place yet could only be done on a smaller sample size. Also as argued in last week's reading the survey could incorporate a larger sample size (due probably to its efficiency) but had to rely on memory of the last important interaction which as the article showed wasn't always easy to remember. This article seems to have a strong finding in the fact that with both of these different network measures they found the same results pertaining to what types of internet tools students used to socialize. However, it is a bit disappointing that they didn't compare the results from the two studies more in their analysis, because one is still left unsure of whether or not these methods taken together provide similar and generalizable results. I think the article does do a good job though in making it clear (like Wellman) that the internet is still new and much more actual research needs to be done. Again it's clear that this author feels any alarm about the internet is unwarranted (although he doesn't seem to show it being able to really help us significantly). The Mesch article also seemed to show that it was hard to have strong ties through the internet though they framed this through the lens of meeting people on the internet. They show that solely internet communities take longer to develop and are much harder to develop (considering they're not as multiplex). This seems a bit contradictary to Wellman who seems to argue that internet communities are just as multiplex. In any case I don't think the main conclusions of the papers are completely contradictory considering that Mesch mainly studies purely online relationships and people who meet online rather than in person. Yet the fact that there is a difference may show some type of cultural difference that'd be interesting to investigate (considering the sample of this study). In general I found this paper to be sound in its methods and conclusions and strong in that in brought in many different theories and empirical studies in explaining the rationale for the research.

Questions:
1. Do you agree with these articles that the internet is just another way we maintain ties or do you think it decreases socialization (based on your experience)? Consider how people use facebook and im'ing and explain why or why not?
2. Is it possible to have close ties solely on the internet or is there something special about face-to-face interaction that needs to be present in some capacity? Furthermore is there a certain amount of face-to-face interaction needed for a strong tie? Explain

This week's readings show just how difficult it is to find a satisfying, standard measuring tool in social research experiments and how different situations call for varying measures. We see that each measure has important strengths and flaws and that in an experiment the smallest changes in wording and context can greatly affect the outcome.

The Konning et. al work was the most comprehensive in terms the different methods of data collection that can be employed. Rather than looking at a specific strategy or generator it gave an explanation of the strengths, weaknesses and methods surrouding sociometric surveys, diaries, observations, etc. This paper served as a sort of guide to the general issues behind social network research (like the Monge reading was to networking terms) and is strong in that it is very organized and extensive. The continuous example of the office setting was very useful in helping to make each of the research methods concrete and it also made it easier to understand how these methods compared to one another in a real world setting. Besdies the attention it gave to each individual type of research tool, it also was very strong in that it reviewed reserach in comparisons between some of the various methods. Like the article I was rather disappointed in the limited between-method comparisons and it seems that there needs to be more of these if we are to determine exactly what methods are best for which contexts. Finally, I think this article made a very important conclusion in that there's a tradeoff between generalizibility and capturing all network characterisitcs and showing which methods correspond with which end of this spectrum. This seems to be a critical component in determining how these methods are assessed in the future and it's very questionable as to which is more important to satisfy, as well as whether or not it's possible to satisfy both with one tool.

The Marin and Hampton paper was much more specific in looking at name generators and how to improve their accuracy. Overall the paper was very comprehensive and prescribed shortcut generators to use as well as the rationales behind them. One issue I have however is the idea that the MGRI provides a "perfect" measure of network size (pg. 2). First off, the readings by Hill & Dunbar and Killworth seemed to show that measures predicting network size are very unreliable and hard to match up at all (yet alone perfectly). Furthermore, I feel that the paper didn't connect this total network size issue back to the research in a clear way and these types of organizational issues make it harder to grip the paper's message as a whole. However, despite this I feel that the paper did serve it's purpose in recommending practical shortcuts and the rationale was very convincing. It also clearly showed that there are advantages and disadvantages to each alternative (e.g. MMG is better at showing number of alters in a particular role, MGRI is better at determining proportion of ties within each role relationship). Finally, I found it interesting that the authors chose to limit the names to 6 for each generator. The rationale and data are clear as to why they chose this number however, I wonder if restricting this compromises a lot of important data. For example I would think according to Gladwell's argument, different types of people (i.e. connectors) would list different amounts of people for each role. Though the six names may be pracitcal it also can greatly restrict the differences we see between people and generalizability of the results and I feel it might be important to reconsider this, considering literature such as Granovetter's and Wellman's (East York Study) on tie strength.

The final two papers looked at generators that differed from the standard use of name generators. Both look more at the social capital contacts can provide in terms of resources and access to information. Specifically the Lin et. al paper looks at position in the occupational structure and shows a clear difference in the way that men and women attain success (men through social capital and women through human capital). This of course brings up the question of whether or not this difference is clearly societally imposed or if there are real differences between men and women (as we saw in Wellman's community piece) that affect their social networks. I think this paper's greatest strength is that it looks at a different culture than most of the studies we've examined so far and adds much validity to the idea that these network trends (like the difference between men and women) are universal rather than just present in a certain type of society. Furthermore, I think this paper is strong in incorporating preceding theoretical and empirical tested ideas into the validation of the model. For example, the connection between Granovetter's weak ties and the fact that name generators tend not to show us this, considers others' research in the field and influences the final model because it makes sure that the model at least has the opportunity to show the effects of prior research. Thus, the model doesn't necessarily blindly agree with prior research but uses it as a guide so that when the model is used, its results can give us further insight into the validity of these theories and past studies. This makes the position generator a very robust and useful measure for social network research. The only issue I had with this paper was that it didn't seem to note clearly the disadvantages of the generator and I think these are important to consider when using any type of measure.

Finally, the Gaag paper is also very comprehensive in it's description of measurement issues and how they were resolved as well as the measures they used to test out the resource generator. This paper claims that it is the happy medium between the name generator and the position generator in that it takes the beneficial parts of each tool and combines them into one. The article is very thorough in its descriptions to the point that it is exhaustive, however these are all important issues to consider when first introducing a measuremement tool. Interestingly, the results from using this generator seem to validate many of the patterns we've seen in this course such as "weak ties are better for finding jobs" and "strong ties are better for social support and discussing important matters." The fact that this type of paper shows this, illustrates the important fact that research on measures not only helps standardize a measure for use in different experiments, but also is useful in adding credence to prior theories and empirical results. Thus, as with the Lin paper it's clear that these types of experiments aren't only necessary but can also help reinforce some of the more interesting topics and ideas we've explored in studying social networks.

Questions:
1. How do you explain the apparent discrepancy between the fact that the Lin paper claims men have more access to social capital and articles like Wellman's claim that women are the main players in maintaining social networks?
2. Do you think it's more important to study specific issues that aren't generalizable or many broad issues that are generalizable? Why? Furthermore, do you think this tradeoff actually exists or is it possible to have a practical study that does both very well?

This week's readings again varied much in style including some aggregate reviews as well as empirical studies and general interest readings. The variety clearly shows that these concepts of controlling information flow (betweenness), getting messages passed on efficiently (closeness) and being involved and active (degree) are very relevant to our daily life and taken together the readings make it much easier to see how the theory fits reality. The Freeman and Wasserman articles seemed to have a lot in common and both stressed that all proposed measures of centrality are important to consider separately rather than together. While admittedly the mathematical formulas were over my head, I feel that Freeman's review was much more clearly laid out and by drawing out the graphs one could get a much better image of what he was trying to describe. Also I feel that it was much better focused than the Wasserman article, which used lots of data but didn't thoroughly explain much of it leaving the reader confused in a mess of numbers and measures. I'm confused as to why he decided to combine prestige and centrality in the same chapter if he reasons that they should be considered separately anyway. In this way it reminded me very much of the Monge article from week 2, which can be a general guideline but is not useful in understanding whole concepts alone.

The Valente study was very intriguing to me, especially in it's contradiciton to the result of last week's Pearson article. While Pearson claimed that smoking was the only action determined more by homophily, Valente showed that popularity and social pressure seemed to be the main driving force behind smoking. This seems to indicate that there is a lot of variation based on demographics (which was the major difference between these studies). Also it brought up the important paradox of popularity, in which popular people seem to adopt social norms, yet also lead the way. Based on the other readings of the week this makes sense because being popular (and central) you'd have the most access to others and the most influence on others in your social network (sort of like being the center of the star graph). Thus, you would play a sort of dual role in the relational spectrum and this seems to be what popularity is in everyday life. I think this article was very strong in that it was very precise about its methods and also recognized that it's hard to generalize. While this is usually a sign of weakness in a study I feel that with this article it's not a major issue because it prompts so many questions and adds to the literature some important ethnic data. The Moutappa et al. article was also very strong in this regard and even better in the sense that it compared ethnic differences within the sample (e.g to show Asians are more often victimized) as well as comparing gender and friend behaviors. This study, (like the Valente study) also seemed to show a large social impact on risky behaviors in contrast to pure homophily. The study was also very strong in its presentation of background material and made it clear (through the results) which theory their findings supported (social cognitive over dominance). Again it's not the most generalizable but still quite informative and provides a nice addition to prior established theory.

Finally, I found the Krebs article the most interesting because it was able to bring together all of the other readings in analyzing a pertinent world issue. This article was fascinating in that it showed how the ring leader (Mohammed Atta) was so important because of his centrality and his ability to move messages between so many rather separate parties. This relates to Granovetter and Burt once again in the way that Atta is acting like a structural hole. However, in this case it's for so many different groups and we see this idea on a more macro level. This article makes one realize that structures of networks can be extremely important because it seems to say that while many people can have an idea, having people who are central and well-connected is the most important piece in actually doing something on a large scale. Unfortunately, in this case it was the worst terrorist attack in American history, but this idea can apply to many organizations throughout everyone's life. While these may not all be covert the general idea still seems to hold true in my experience with groups. So while this may not be the most academic or rigorous paper it's very strong in conjunction with the other readings and prescribes an important solution that's in line with both theory and empirical evidence.

Questions:
1. How important is it to have these central/popular people leading overt organizations? Do you think it is more important for a leader to be central or intelligent (If they can't be both)? Why?
2. Comparing last week and this week do you think homophily is the main determinant of behavior in groups or social pressures, or do you think it's impossible to say one is more important than the other? Explain.

1) I think that these core changes in discussion networks are caused by an amalgam of different societal changes that have slowly been occurring over the last half century. As Wellman noted in “The Community Question” we have never really “lost” community but instead the definition continues to change with time. In our Western societies we have seen broad scale changes through industrialization and institutions that give us things our ancestors would have loved. Institutions like free public schools and health care as well as a relatively stable political climate have made life so much easier for us, and as Wellman claims “the insecurities of members of Western societies largely come from physical and emotional stresses in their personal lives and social relations” (pg. 35). Thus, rather than working in communities to merely survive and/or activate major change, we have enough comforts in our society such that we don’t need to depend on others as much. Furthermore, as new technologies, businesses, and organizations pop up all over the place, it is hard for us to know where exactly to place our trust. As Putnam claimed in the interview, people have not only begun to trust government less and less since 1966, but over the last 30-40 years trust in general has been declining. Consequently, it seems that people would naturally look to smaller groups who they know they can trust, rather than be lost in a world of endless information that’s both confusing and threatening. Burt clearly makes this point is his article when he argues, “In a perfectly competitive arena, you can trust the system to make a fair return on your investments. In the imperfectly competitive arena you have only your personal contacts.” (pg. 72). This is a model that I think we see in everyday life. In our imperfect competitive market we see people trying to accumulate as many weak ties as they can, because as Granovetter shows these are what leads to more information and better jobs. This seems to go hand in hand with the observation in the interview that people are members of many groups nowadays but spend less and less time with each group. Since the interviewees also claimed that there is a direct connection between how much we connect with a group and our intimate ties, it makes perfect sense that we feel less connected to others outside our family. The overarching societal structure and its continuous changes and increasingly competitive nature have turned us more inwards than ever before.
2) It’s no wonder then that studies such as Wellman’s “Different Strokes from Different Folks” paint a picture where almost all major resources and information are exchanged between kin. He notes that kin (especially in a parent/child relationship) provide emotional support, small services, large services, and financial aid whereas friends provide just companionship and some support/services (pgs. 573-574). These internal strong ties give humans most of the resources they need in both crises and in the struggles of daily life and serve as all-purpose confidants. As McPherson et al. point out, spouses are probably the most critical in providing all of these major services and support. In studies like Kalmijn it’s clear that as people begin living together and depending on each, other the size of their personal networks severely decrease. (pg. 247). Yet, while the warm fuzzy hugs may be nice, they have a clear cost of limiting people’s resources. If people only trust their immediate kin and fail to branch out they only have access to information within a limited network (as shown by Granovetter and Burt). Without many structural holes it is infinitely harder to learn important new things about the world and other’s lifestyles and make ties outside the usual “comfort zone.” While it may not always be easy to leave this comfort zone, it gives individuals access to diverse viewpoints and this is critical to the smooth functioning of our society. If we limit ourselves to people who have our own views and participate in increasingly homophilous networks, social psychological studies show that we will become more polarized in our beliefs. More polarization leads to an increasingly divided society, much like the one we’re seeing today in our own political arena. If we don’t branch out and learn about others our very societal structure is in grave danger because it’s very hard if not impossible to live in a society that clashes on everything and continually disagrees with each other, rather than working together to find real solutions to societal issues. As Putnam suggests, without strong personal networks we have weaker governments, and this leads to failures to respond to major catastrophes (such as Katrina). On a more micro level this shift has a major impact in the fact that with smaller networks we put ourselves more at risk of having no one to turn to if/when we lose a crucial contact. It’s alarming that 42% of people in Texas, Louisiana, and Arkansas have no one to turn to with which to discuss important matters. Without strong personal ties outside of the home (like the kind Bott describes in households with segregated conjugal roles) people are in essence left to fend for themselves in the case of divorce or death. With a 50% divorce rate and a continuing number of people who have no one to talk to about important matters, this tradeoff between having strong wider networks with less individual support from each person and small networks with all types of support coming from few individuals is crucial to balance if we want to live in harmony.