Social Network Blog - y8

“The Structure of the Web,” looks at the evolution of the web as a new medium for communication. Jon Kleinberg and Steve Lawrence, point out that unlike other networks in our past, the web is a virtual network of different content and hyperlinks. This has led the web to be extremely decentralized, yet it still contains a vast degree of self-organization. In this article, Kleinberg and Lawrence have sought out to understand the structure of this powerful and vast virtual network. They conclude that: “A recent study (l) indicates that the Web contains a large, strongly connected core in which every page can reach every other by a path of hyperlinks. This core contains most of the prominent sites on the Web. The remaining pages can be characterized by their relation to the core…” (1849). In their structural breakdown of the Web, the authors identify four major components—core (which is very compact), upstream, downstream and tendril regions. The authors explain, “The shortest path from one page in the core to another involves 16 to 20 links on average, a ‘small world’ situation in which typical distances are very small relative to the overall size of the system” (1849). According to the authors, the structure of the Web is made up of hubs and authorities: “A hub is a page that points to many authorities, whereas an authority is a page that is pointed to by many hubs” (1850). The authors note that this new virtual environment is also altering information flow in the world—the authors believe that the Web will actually bringing individuals together with common interests by enabling and facilitating an easier way to communicate.
Questions:
1. Are there any negative aspects to the structure of the Web described by Kleinberg and Lawrence? Are they overlooking anything?

“Information is getting easier to merge, fuse and draw inferences from. There is money to be made and control to be gained in doing so. And I don’t see much that will stop it” (Tim Finin, Marks article). This quotation is just one of the many alarming excerpts from Paul Marks’ article, “Pentagon sets its sights on social networking websites.” Marks describes a recent movement by the National Security Agency to build extensive, personal profiles of individuals. NSA hopes to tap the Web and fuse social networking analysis with other analyses to find deeper and stronger ways of identifying peoples networks, interests and core groups. Although there are still technical issues at hand (the web is incompatible with other formats), researchers hope to use Resource Description Framework to create a code for each type of data, essentially creating a universal language. There have been many legal issues with this movement, especially post September 11th. However, with websites such as “myspace” having up to 80 million members, there is much concern that this new technology could lead to serious issues, such as ‘automated intelligence profiling’ or ‘miscarriages of justice’. There is much ambivalence and controversy over merging social network analysis with other forms of intelligence, and I think that Jon Callas, chief security officer of PGP gives the best advice out there: “Callas thinks people have to wise up to how much information about themselves they should divulge on public websites. ‘It may sound obvious,’ he says, ‘but being discreet is a big part of maintaining privacy. Time, perhaps, to hit the delete button.’”
Questions:
1. How can we protect our privacy (besides the delete button) against this new technology?
2. Do you think that this new technique is immoral or unethical in any way?

The article, “Spatially Bounded Online Social Networks and Social Capital: The Role of Facebook,” looks at the relationship between the role of facebook and its relationship to social capital formation and maintenance, integration into college life and psychological well-being. The article notes that Facebook was created in early 2004 and has about 7.5million users (it is the 7th most popular site on the Web). There has been a lot of negative press for Facebook recently, altering students of the privacy issues and the possibility of offline and online identity theft. The motivation for this study was: “large numbers of highly embedded users, a unique geographically-bound target audience, high visibility, and widespread public coupled with few academic studies of the site”(2). In a 2005 survey, the results suggested that people seek out Facebook to connect with old friends, to meet new friends, to meet romantic partners and to increase professional networks. The researchers of this study found that the shift of many of these relationships went from offline to online. The authors in the study asked three research questions to a random sample of 800 undergraduate students at Michigan State University. The three research questions were: 1. Who is using Facebook? How are students using Facebook?
What is the relationship between Facebook use and social capital?

Out of the 800 students, a total of 286 completed the survey (35.8%). The measures for this experiment were demographic variables, Facebook usage measures, psychological measures and social capital measures. The three measures of social capital were bridging, bonding and high school capital. (The experiment showed that 94% of students were Facebook members) The results of this experiment showed that: … “there is a positive relationship between certain kinds of Facebook use and the maintenance and creation of social capital…intensive Facebook use is a significant predictor of bonding, bridging and high school social capital”(26). The study acknowledges that although there are some issues with privacy and management on Facebook, that there is a STRONG connection between Facebook users and indicators of social capital: “The Strong linkage between Facebook use and high school connections suggest how online social network help maintain relations as people move from one offline community to another…”(32).
Questions:
1. About two months ago, Facebook created the newsfeed feature. How did that affect your Facebook usage or personal feelings towards the virtual network?

Barry Wellman’s article, “Physical Place and Cyberplace: The Rise of Personalized Networking,” looks at the change in our communities, from solidary groups to individualized networks. The main concerns of the article are: how networks of communities exist in physical places (like neighborhoods and the internet) and how the development of computer-supported community networks affects access to resources. Wellman describes the rise of personalized networking in terms of these variables: broader bandwidth, wireless portability, global connectivity and personalization. Wellman argues that communities transcend the group and the locality via door-to- door interactions, place-to-place interactions, the domestication of communities and the domestication of the internet. Wellman suggests that the rise of networked individualism is due to several factors: person-to-person interactions, the shift from interhousehold networks to interpersonal networks, mobilization and computerization. Wellman concludes by explaining that: “Although physical place continues to be important, cyberspace has become cyberplace, affecting the ways in which people find and maintain community…This is a time for individuals and their networks, not for groups. The all-embracing collectivity has become a fragmented, personalized network. Autonomy, opportunity and uncertainty rule today’s community game…” (247-8).

In Lorne Tepperman’s article, “Deviance as a search process,” Tepperman defines a search process as “a set of steps followed in order to find something that is lost or otherwise hidden from sight” (1). The author identifies two different types of deviance (individual or group). The author’s main goal is to explore the utility of network analysis and the “search metaphor” in analyzing a specific search process. Tepperman labels three important distinguishing features of the deviant search process: “…the secrecy of the search, the importance of the intermediaries and the role of the sought after” (6). The author explains that there are various different strategies to conduct a deviant search—however, if the strategy is conducted in an unsystematic way, it may be extremely expensive and may not ever be completed. The author concludes by stating, “If there is a particular psychological, intellectual or cultural component to developing successful strategies, we should find this revealed by empirical comparisons of people who have and have not succeeded in committing deviant acts” (17).

Chapter 8, “Diffusion Networks,” talks about how interpersonal communication drives the diffusion process by creating a critical mass of adopters. The article mentions several important terms, such as opinion leadership. Opinion leadership is defined as “the degree to which an individual is able informally to influence other individuals’ attitudes or overt behavior in a desired way with relative frequency”(300). This article then begins to evaluate the different models of communication flows that have been identified in the past, such as the hypodermic needle model and the two-step flow model. The distinction between homophily and heterophily is stressed, especially how each group type alters the communication flow. Next, the author looks at the different measuring techniques in evaluating opinion leadership (both monomorphic and polymorphic), such as the sociometric model. The most interesting section of this article is the evaluation of characteristics for a successful opinion leader, which range from external communication, accessibility, SES and innovativeness. The author then asks the question, “Do Opinion Leaders Matter?”(321). The author then analyzes many cluster studies, and applies them to the question within a broader framework. Lastly, the critical mass is discussed in relation to diffusion of innovations. I thought that the case study on the adoption of the
Internet (see figure 8-6 on p. 347) was a great example of the diffusion of an innovation.
Questions:
1.Do you see this theory of diffusion in such “black and white” terms? In other words, do you think that the author over-generalizes this phenomenon?
2.What types of situations would lend themselves to a different speed/ mode/ process of diffusion?
3.How does our social network makeup (i.e. diversity) at Penn affect our diffusion networks?

Ronald S. Burt argues that opinion leaders are “not people at the top of things so much as the people at the edge of things, not leaders within groups so much as brokers between groups”(37). In his article, “The Social Capital of Opinion Leaders,” Burt makes the distinction that opinion leaders are essentially brokers that manage contagion and cohesion. Burt argues, “Opinion leaders as brokers bear a striking resemblance to network entrepreneurs in social capital research” (37). Burt argues that social capital research and the content of diffusion have a complimentary relationship, and when studied together, they create a very strong analogy. Burt explains, “Diffusion research describes how opinion leaders play their role of brokering information between groups, and social capital research describes the benefits that accrue to brokers”(37). Burt continues by identifying the network structure of contagion and the power of equivalence. According to Burt, equivalence has three properties: it equals cohesion, it corrects cohesion and it extends cohesion. Burt then compares opinion leaders to opinion brokers. He explains, “Opinion leaders are people whose conversations make innovations contagious for the people with whom they speak”(46). Burt argues that opinion leaders in the network structure of contagion are essentially opinion brokers who transmit information across social boundaries between status groups. He then evaluates the network structure of social capital.
Questions:
1.Does article agree or disagree with Malcolm Gladwell’s book, “The Tipping Point”?
2.Do you agree with this analogy of an opinion broker? How might one disprove this theory?

RESULTS:
Natasha= 16 cell= 10 IM=3 text= 3
Ali lenobel=8 cell=3 IM=3 text= 2
Mom=7 all cell
Sara= 6 all cell
Nushien= 6 all cell

Part 1

Questions
1.The five people with whom I interacted most often were three of my best girlfriends from college and high school (Natasha, Ali L and Nushien), my mom (Marcia) and my sister (Sara). I spoke to Natasha the most using the cell phone communication medium; however, I also spoke to Natasha the most frequently across all of the new media communication mediums. I instant messaged and text messaged the most frequently with Ali L and Natasha (a total of 3 conversations with both of them). These were the three communication mediums that I used for this study. I am extremely close with all five of these people. Natasha has become my close friend this semester, as many of our mutual friends are traveling abroad. Natasha is also from Europe, where text messaging is a lot more prevelant than it is in the United States. I also spoke to Natasha a lot during the seven days in which I recorded my data, because it was during fall break and were in the midst of making plans to go to New York together. Ali L is my big sister is my sorority, and we speak frequently throughout the year. Again, many of my friends are abroad this semester and I have become even closer with her this year. Most of the conversations I have with these two are based on coordinating making plans with one another or just “chit-chat.” According to Wellman, my relationships could be described as “small services” or “companionship.” I have a very close relationship with my mom, but unfortunately, most of our conversations through mediums of technology are based on small services or emotional aid. When we are face-to-face, however, our relationship can be classified more as “companionship.” My sister Sara and I are also very close, and our conversations would mostly fall into the companionship category. Nushien is my best friend from high school, and she goes to Columbia University. Our conversations are exclusively emotional aid and companionship, unless I am in New York, and we contact each other to make plans.

2.I think that there is a tangible relationship between the strength of the tie and between the medium I used for communication. It is true, however, that I typically write on Nushien’s Facebook wall (my best friend from high school) and look through her posted photographs. And although my findings suggest a relationship primarily based on cell phone usage, I would argue that these results occurred during fall break because I was actually in her geographic vicinity, and we were attempting to make tangible plans to meet up with one another. In these instances, the cell phone is the easiest communication medium.

According to the Ellison, Steinfled and Lampe study on the role of Facebook, the findings suggest that: “there is a positive relationship between certain kinds of Facebook use and the maintenance and creation of social capital…the strong linkage between Facebook use and high school connections suggests how online social networks help maintain relations as people move from one offline community to another. It may facilitate the same when students graduate from college, with alumni keeping their school email addresses and using Facebook to stay in touch with the college community”(p.26, p. 32). At this point in my life, I have stronger relationships with my college friends and family members than with my high school friends, based on proximity and relevance to my life. Primarily, I use like Facebook, Instant messaging and other computer-related mediums to stay in touch with people from my past, although I occasionally use it to touch base with the people I see on an everyday basis (I would say I use text messaging and instant messaging for small services when conducted with people in my everyday community here at Penn).

More importantly, however, that there is a distinct generational difference between the mediums I used for communication. My mom is 61 years old, and my sister is 27 years old. Although there is a large age gap between the two of them, they both belong to generations that were not as exposed the same technology that I was exposed to. My mom and sister are able to use e-mail, text messaging and instant messaging, however, it would not be the first medium that they would turn to when trying to get in touch with me. Both of them are more comfortable with the cell phone as a medium for communication (*I do not have a landline at school; therefore my calls are made solely from my cell phone).

For all five of my most frequent interaction partners, I would say that small services, emotional aid and companionship were the most frequent types of supports exchanged. I am extremely close with my mom and my sister, and have known them for my entire life. I think that duration is a very important variable, as I can trust both of them with any issues that may arise, such as job information, large services or emotional aid. In Barry Wellman and Scot Wortley’s article, “Different Strokes from Different Folks: Community Ties and Social Support,” the authors looks at the relationship between community ties between friends and relatives and supportive resources. The authors look at several different variables to explain the phenomenon of social support. One aspect that I found to be intriguing was the section on kinship. The authors write, “There are cultural, structural pressures and perhaps biological reasons for kin to be supportive. The densely knit structure of most kinship ties intersects with the norm that ‘blood is thicker than water’ to encourage supportive relations among kin” (572). This interpretation of the relationship between community members and type of tie strength is extremely accurate, and is in congruence with my findings. There is an unspoken desire for kin to help one another, and this is seen through the types of support exchanged, the duration of the relationship and the type of relationship. The authors also describe the complex and interesting relationship between siblings and support, which I found relevant to my analysis: “Siblings are similar to friends in providing emotional support and small services. They are more likely (20%) than friends—and less likely than parents and children—to provide large services” (574). These findings echo the type of tie that is a major part of my relationship with my older sister. She is always the first person to help me out in a situation where I need advice, whether it is a fight with a friend or a bad grade on a paper. She is even willing to drop everything to help me find a summer job. However, if it is something that she cannot handle on her own, the issue (a large service) will immediately be deferred to my parents. I use the cell phone as a communication medium most frequently when talking to kin, and especially siblings.

However, I do not defer to my cell phone every time I want to communicate with a close friend. Sometimes, email, instant messaging or text messaging may be more efficient or more appropriate based on timing and location. Unfortunately, the small amount of data that we have collected for this assignment pushes us to make generalizations.

I think that distance plays a large role in my medium of communication. As stated above, some of my closest friends are abroad, making it very difficult for me to speak to them on the phone on a daily basis. For example, my three best friends are in Hong Kong, London and Washington D.C. for the semester. This, clearly, has a large impact on my social interactions and mediums of communication. It also changes who I go to for certain types of support. For example, I do not think that I would necessarily talk to Ali L. or Natasha as much as I do on the cell phone had my friends not gone abroad; however, they became different kinds of support for me this semester. This semester, I speak to my three best friends who are abroad on email or Skype only. This is not ideal, as they are my closest friends, and there is something really intimate about talking to someone who is far away on the telephone. Hearing the voice of someone that you truly miss and are close to is a feeling that can never be replaced by any modern technology.

All of members of my close network were female. I found this to be exceedingly interesting. Just to give you a little context into my life, I do not have very many male friends(excluding my brother and my father) so when I do speak with people of the opposite gender, it is usually through a less intimate form of communication, such as instant messaging or text messaging. I think it is interesting to point out that whenever there is a romantic element involved between a male and female, it almost always is in the medium of text messaging. I am not sure why this is exactly; however I think that this technology has enabled us to be even lazier in the dating world. Wellman and Wortley describe gender as a very distinct social characteristic in determining social support: “Gender is the only personal characteristic that is directly associated with support. Yet gender is in many ways relational: it both reflects and determines social relationships. The involvement of women in providing emotional support to women friends and kin of both sexes is a product of their work as domestic relations specialists…men fix things; women fix relationships and keep households and networks going”(582). Although this does not exactly apply to my findings, it does hold some merit. Essentially, my mom and sister are my two fundamental pillars of support, which is partly due to their gender association with me, amongst other things. I am therefore more likely to use my cell phone, my most intimate medium for communication, to contact them.
Thus far, my results suggest that the role of new media in our social networks has a very large impact on our social relationships and networks. My data suggests that there is a direct correlation with communication medium and tie strength, support, duration, distance, and gender when studying social network analysis. New media is giving us a chance to connect with people all over the world at any time of day, yet my results suggest that I am still in contact with a very intimate, small network on a daily basis. I think that it would have been beneficial for this study if we had analyzed all of our interactions (not just the top five people with whom we interacted most). Although my data suggests a correlation between communication medium and my ties, I am not ready to make the claim that this relationship will exist in on a larger scale. For my purposes, I found that I chose the cell phone as my favored communication medium, especially for support such as emotional aid and small services. I also found that I would prefer the cell phone over email, but that distance plays a large factor in this choice. Gender and age also played a role, and so did the duration of my relationships.

3. I do not think that there was significant data that showed a relationship between my choices to have public or private interactions. I think that it was completely based on circumstance and opportunity. I do not think that this choice had anything to do with the person or the tie strength to that person. I will say, however, that I prefer to have most conversations and interactions with people in the home. I am a very private person, and I find people walking down the streets on their cell phones to be completely obnoxious and unrelated.

In the article entitled, “Social Integration and Health: The Case of the Common Cold,” the authors analyze the concept of social integration and how it related to health. The authors first explain the past theories that have been conducted on the relationships, followed by a prospective study on social network diversity and the susceptibility to the common cold. The authors found that the greater the social diversity in a network, the lesser susceptibility to illness. However, the authors mention that their attempt to isolate the pathways through which social diversity is associated with susceptibility was unsuccessful: “The relation was independent of the number of people in the social network” (1). The authors refer to the number of social roles as “network diversity,” in order to distinguish it from social integration. In this study, the authors asked five specific questions to the respondents regarding the sizes of their networks, the roles within their networks, the diversity of their networks etc. The article refers to several medical definitions of clinical colds in order to alert the reader of the parameters of what they deem to be a “cold.” The control variables of the experiment were age, gender, ethnicity, education, body mass index, season during which the trial was conducted, type of experimental virus and the body’s initial reaction to the antibody. When measuring social networks and susceptibility, the authors found that people in networks with low social network diversity tend to have a greater percentage of colds. The authors examine the possible reasoning behind these findings, such as specific pathways, stress and personality. But the conclusion of their study is clear: “…social isolation constitutes a major risk factor for the development of illness. Volunteers who were relatively socially isolated(1-3 relationships) were 4.2 times more likely to develop illness than those with very diverse social networks(6 or more relationships)…We found that the relation between network diversity and susceptibility to he common cold was independent of network size”(9).
Questions:
1.How would the results of this study be different if this experiment had been conducted at Penn?
2.How would the results been different have been different had the social network measures used been a bit more complex?

The article, “Lack of a close confidant, not depression, predicts further cardiac event after myocardial infarction,” looks at two variables(the role of depression and the lack of social support) and how they affect post MI patients. The study proposed an innovative way in correlating depression and MI: “…the negative influence of depression on outcome after MI may be attributable to pre-existing depression” (518). This hypothesis is quite revolutionary, and the doctors in the study decided to test out their hypothesis on a sample of post MI patients (583 patients) from the UK. During this study, the patients were assessed based on many measures, including demographics, medical history and past psychologically formative experiences. The main results of the experiment are as follows: “We failed to find an association between depression before MI and subsequent mortality or cardiac events, in spite of the high prevalence of depression. We did find that having a close confidant approximately halved the risk of having a subsequent cardiac event, even after controlling for demographic and coronary risk factors, severity of MI, and discharge medication”(521). This study intrigued me quite a bit. I think that looking at the impact of psychosocial variables and a physical ailment/ disease is an extremely important, effective and accurate way to analyze health. It is accepted that there is a large relationship between mental health and physical health, and vice versa. So why don’t we study other health illnesses in this manner? It is so interesting that having a companion keeps one healthier for longer. It really tells you how much of our health is based on our basic and primitive human needs.

In the study conducted by Bearman, Moody and Stovel, the structure of an adolescent romantic and sexual network is observed in order to better understand the spreading of STDs. This specific study, entitled “Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks,” analyzes a pool of 800 adolescents at a high school in the Midwest. The relationships were measured over a period of 18 months, conducted from 1993-5. This article looks at the specific partnership patterns and network structures of these relationships. The article takes a strongly empirical approach to the study, interpreting several modes of disease diffusion. The authors are mostly concerned with each individual actor’s specific “role” in the diffusion process, which is sometimes called the “spanning tree.” The context of the experiment is “Jefferson High,” and the items being measured are the romantic and sexual relationships, in every shape and form. The next measurement that is discussed is partner preference, also known as “attribute-based selection preferences.” I found this section to be the most interesting aspect to the study, as homogeny in these two-person networks is extremely prevalent. The findings of this study are as follows: “The most critical feature in STD epidemiology is the idea of a core, which is associated with cycles in networks. Moody etal.(2003) have demonstrated that very low average degree networks can give rise to densely interconnected cores…In our data, we find that this key-structural feature is largely absent. We have proposed a reason for this absence, specifically a norm against second partnerships. From this norm, combined with basic homophily preferences, we generate networks that are structurally isomorphic to the one we observe empirically. This suggests that in adolescent society—where partner choice is salient for local status—it seems reasonable to think that such a rule operates”(78-9).
Questions:
1. How can we stop (or at least slow down) this diffusion process of diseases across adolescent networks?

The findings for our “Small University Experiment” reflect and reinforce much of what we have studied and read this semester on Stanley Milgram’s “small world” study (1967). In Milgram’s Nebraska study, he found five intermediaries to be the median number of links between the starter and the target. In our study, the mean for Susan Yoon’s group was 3.25 for completed chains, and 1 for incomplete chains. The mean for Antonio Polley’s group was 4.5 for completed chains and 2.33 for incomplete chains. This suggests that Milgram’s hypothesis may not be generalizable to every situation and population, as the degrees separating us is less than 6, on average. Or, this may be skewed or incomplete due to the amount of low response rates.

In his article, “Six Degrees of Lois Weisberg,” Malcolm Gladwell discusses Milgram’s chain letter study with the stockbroker in Omaha, Nebraska. Milgram asserts that five intermediaries on average can connect two people across the world, which is essentially his theory of six degrees of separation. However, it is mentioned that each of these degrees are not necessarily equal (5). I thought that this was very interesting and relevant to our “small world university” study. This theory can be drawn from the evidence that half of the packages in the Milgram study had touched the hands of three men: Jacobs, Jones and Brown. Although in our study, “June C” was the only repeat for the final link, if this study were done on a larger scale, I think that she might have had a larger frequency than the rest of the final links. As Milgram asserts, “It means that a very small number of people are linked to everyone else in a few steps, and the rest of us are linked to the world through those few” (6). Although it is very difficult to conclude the accuracy of the relate-ability of Milgram’s theory to our results, one can surmise that central actors would be clearer to determine in a larger-scale study. As Killworth, McCarty, Bernard and House explain in their article, “The accuracy of small world chains in social networks,” there are many flaws in our analyzing the chains in social network analysis. The authors simply conclude that “…inaccuracy in selection of small world chain intermediaries is predominant…” (95).

I passed my folder (Y8) to a strong tie that majors in BBB (Biological Basis of Behavior). What I find to be so interesting about my chain links is that the first three people in my chain were all female juniors in the college. The fourth person on my chain (the third link) was a male junior in the college. The only person that I knew on my chain was my initial link, and I did not recognize any of the other names in my link. Also, every person in my link was a student in the college.

I initially chose Lauren to be my initial link for several reasons: I trust her, she is a pre-med student and I thought that she would be enthusiastic about participating in the study. Some of my doubts about picking her as an initial link, such as her isolation in her undergraduate program, may have actually contributed to the fact that my folder never reached Antonio Polley. I spoke to Lauren just after she had passed off her folder. She seemed really confident about it, and explained to me that she was sure that the folder would reach our target with ease and speed. I asked her if she had known who to give it to right away, or if she had to deliberate on the decision. Lauren explained that she had to think about it, but eventually concluded that an acquaintance of hers would be a good choice. The problem is, Lauren never conceptually thought about how this folder would get to Antonio. Instead, she thought about her role in my chain (an egocentric point of view) instead of her role in the larger picture. My hypothesis for this experiment was that based on Granovetter and Monge’s theories, Lauren would be a good choice for an initial link in my chain. Even though I had many doubts about choosing a strong tie over a weak tie because of the “bridging” potentials of a weak tie, I still chose a strong tie that was affiliated with the medical school.

After looking at the different links on my chain, I realized that my links were extremely homogeneous to one another. Although Lauren was my only connection to the medical school, my folder ended up circling around a group of sophomores who did not know how to locate Antonio Polley or move up the hierarchal social networks ladder. They became an isolated group, thereby stopping my chain dead in its tracks. The results of my folder’s journey reveal the possibility of communication becoming severed within a network. My folder probably died because it had no logical or obvious next link. I correctly hypothesized that the folder would be passed primarily among undergraduate, female students. I had optimistically hypothesized that 50% of the folders that reached Antonio would be from the three same final links (As in Milgram’s experiment). Unfortunately, because only two of the folders reached Antonio, we cannot make that assessment on the grounds of this experiment.

While an impressive percentage of Susan Yoon’s folders successfully reached her (80%), only 25% of Antonio Polley’s folders reached him successfully. I am by no means surprised by these findings. It is clear that there is a large divide between the undergraduate medical major concentration and with medical school at Penn. Antonio Polley is one of many lab technicians at the Wistar institute, which most members of my group had never heard of before the day we began this study. In fact, Antonio’s group was at a disadvantage from the start. Susan Yoon is a more accessible target in the Education school. Also, there are more females than males in the undergraduate communications major at Penn. Almost everyone in the school of education is a female. As we have read this year, gender plays a large role in social networks. I think that because all ten of the Susan Yoon groups were female, that they had a larger probability of reaching their target than Antonio’s group. Also, Susan is just a more centrally located actor in the social networks web.

It is noteworthy that the uncompleted chains in Susan’s group both disappeared after two links and within a very short amount of time from the start of the study (2 days for y10 and 6 days for y35). Both Y10 and Y35 are seniors, and one gave her folder to a “very weak” tie while the other gave her folder to a “strong” tie. What does this mean?

I think that the two folders that reached Antonio did so because both R45 and G10 are fifth year seniors, and have some connection to the school of education that other students in our class did not have. Or, maybe they have each had extra communication with career services or graduate programs, exposing them to an entire new network of people. I think that the path that G10’s folder took is truly a piece of evidence for the success of Milgram’s theory: It took G10 six different links (fmffmmM) and touched the hands of students, faculty and staff. It also went through the college, the school of medicine and through Wistar. It took ten days for the second link to pass on the folder (I think that after a week it is very surprising that a folder would be passed at all) and it was done so effectively.

The Small University Experiment that we conducted had both similarities and differences to the “Small World University Experiment” conducted by Stevenson, Davidson, Manev and Walsh at Boston College. Firstly, in our experiment were also faced with the problem of low response rates, which can be seen as the unfinished chain links in our study (eight out of eighteen folders didn’t reach the target person and had incomplete links). In the Stevenson etal. study, there was a major and more obvious hierarchy of communication between upper and lower classmen. In our study, although a large percent of student to student transfers were for students in the same year (for Antonio’s group, it was 42.86% and for Susan’s group it was 40%), there were still a significant amount of student to student in lower class transfers for both targets(28.57% and 60%). This shows that there is more inter-class communication in a college university as opposed to a high school environment. This may be for several reasons, but I would hypothesize that high school places larger importance on class distinctions, and this is seen in sports programs with junior varsity and varsity and with academic classes. In my high school experience, the only time that I ever socialized with upper classmen was during sports team practice and language classes, and even in those classes it was obvious which students were in which classes.

The original design of our study is slightly different from the Steveson etal study. In our study, we had two target-people instead of one, each of whom was more difficult to locate than in the Stevenson etal study. Also, our study started out in the hands of juniors and seniors, whereas their study included freshman through seniors. It would have been interesting to include this element in our study, because we were unable to test the hypothesis that freshman are especially isolated from the rest of the classes.

There was a direct correlation between our study and the Stevenson etal. study when it came to older students. Our study shows that the only two students in Antonio’s group that was able to complete the chain were 5th year seniors. This is relevant because they are more likely having a connection with graduate students and faculty than other students. R45 and G10 both passed their folders to sophomores. In the case of R45, the next link was then a senior. In the case of G10, the next link was a sophomore again. I found this pattern in the successful links to be extremely interesting. R45 chose to give her folder to a female sophomore in the fine arts department, whereas G10 gave hers to a male sophomore in the biochemistry department. Both R45 and G10’s final links before reaching Antonio were male students. This supports the gender theory from the Stevenson etal. experiment: “Women relied more on homophilous ties to pass folders compared to men”(6).

The Stevenson etal. Study suggested four hypotheses that were relevant to our class findings. Hypothesis 1, “The longer the time at the university, the more likely a student is to initiate a successful chain of communication to a target”(2), is proven to be true in our experiment. In Antonio Polley’s group, the two students who had completed their chains were both 5th year seniors. Is this just a coincidence or does it prove that age is a significant indicator of communication within a networks? Hypothesis 2 stated, “Small world folders are more likely to be passed within a class than between classes and occupational groups in a university” (2). This hypothesis did not apply to either target person (I am analyzing completed chains). In Antonio’s group, the percentage of student-student transfers in the same year was 40%, and student to student transfers in a lower class was also 40%. In Susan’s group, the student-student transfers in the same year were 44.4%, whereas the student-student transfers in a lower class were 55.4%. Hypothesis 3 stated, “Small world folders will converge on faculty and staff before reaching their target” (3). The results for Susan’s group suggest that every person to give the folder to Susan was either a member of the GSE School or an Administrator. This is completely congruent with Stevenson’s findings—in fact, the two students whose folders did not reach Susan were unable to make the link to the graduate school of education or some other graduate-level person. The data from Antonio’s group is more complex—the two students who were able to reach Antonio broke the barriers by entering either the Immunology department or the Wistar Institute (where Antonio works). However, there was a student who reached the Wistar Institute but did not reach Antonio (g16)—this clearly complicates the data. How did certain folders within the Wistar Institute reach Antonio while others continued to circle the same group of people? Hypothesis 4 states, “Small world folders are more likely to be passed to members of the same sex” (3). The pattern of links for Susan’s group is almost entirely female (there is only one male in the entire chain). This is in congruence with Stevenson’s hypothesis. Essentially, since the entire Susan group was female to start, and the target was female, the chains consistently remained in the female gender. Antonio’s group had a difficult time making the transition from female to male, as all but one person in the initial starting group was female. There was a mixture of when the students in Antonio’s group made the transition to male—some did it initially, whiles other chains did not switch until the very end, or at all. Both people to hand Antonio the folder were male. Overall, our study had some similarities to the Stevenson study, but the differences are also extremely flagrant and relevant.

Link to Part One: http://www.mysocialnetwork.net/blog/481/y8/2006/09/small_university_experiment.html