Social Network Blog - g44

Although I complained about collecting the sample and how much work it would be, upon reviewing the data I almost wished that I had more in so that I could draw more conclusions. Though it is understood that external validity is particularly weak in this study, due to the fact that a convenience sample was used, there are other possible areas for measurement error. For example while conducting the survey I read the entire document and marked the answers on it myself, whereas with others I simply handed them the survey and kept my fingers crossed. While reviewing the surveys I noticed some error with regards to marking incorrect levels of education as well as some error in the name generator portion (in marking incorrect or nonsensical associations between ties.) A more important threat would be the threat to construct validity in this study. It is discussed at length in the McPherson and Smith-Lovin study how participants vary in interpretation of the GSS question. When participants are asked with whom they discuss “important matters”, the vague term “important matters” is interpreted in many different ways due to idiosyncratic differences among participants on what topics are deemed important. This question generally gets responses indicative of the participant’s general social climate rather than specific instances and conversations recalled. Therefore, when asked what matters are considered important respondents tend to give a wide array of answers from the mundane to politics and current events. The people who are reported usually reflect core network ties, thus this question more reflects with whom the respondent discusses things on a regular basis rather than “important matters” per say.

This assignment is quite interesting in that it connects the operationalization of social capital (position generator, name generator) to demographic characteristics and the strength of ties (through media usage information). In recalling the McPherson Smith-Lovin piece I was quite sure that I would find that those who participated would have network sizes around 2, with a considerable (~30%) amount of people reporting having no one with whom they discuss important matters. I also hypothesized in terms of social support that women would have more of a “satellite dish with 200 channels” as alluded to in the Freeman piece. The “Cathy” comic strip most accurately details this idea where women tend to have large networks of specialized ties. This means that rather than having a few ties that range in the types of social support they provide one would have many ties specializing in one type of support. Both of these hypotheses were proven wrong by my surprising network findings. On average, people reported having 3.05 ties with whom they discussed important matters. The younger group had a surprising 3.5 ties on average with whom they discussed these matters while the older group had 2.6 ties on average. Only 2 (10% of) respondents reported not having anyone with whom they discussed important matters and interestingly these two males were both 21 year old seniors in college who share an apartment. In terms of the women providing more ties on average with more specialized support, it was difficult to discern from the results the type of support exchanged, however women tended to have more ties at 3.5 compared to men with 2.6 ties. This is odd since the differential between the older and younger group had the same exact split. This means that for my sample, an older woman tends to have a larger network size than an older man and that a younger man theoretically has a larger number of ties than and older woman. Generally however, women tend to have larger networks in my sample. There is not much evidence for the Freeman satellite hypothesis in my findings, for it appears that people like Cathy in the comic strip are just outliers. Women’s networks however do appear to be mostly composed of kin in the older age group and of non-kin in the younger age group. Younger women are more likely to maintain multiple numbers of both kin and non-kin ties, while older women have almost completely kin ties composing their networks.

The Wellman piece also details the elements important to social support. In this piece he discussed structural and positional resources and how they can be sources for social support. For example, my best friend and I are both structurally equivalent within the Penn student body as well as structurally equivalent within the hierarchy of the Penn Women’s Track team. According to Wellman, the sociological belief that “collective” phenomena affect interpersonal behavior could account for the wide array of supportive services we offer one another. This is evidenced in our frequency of contact through many different media (in person 30/30 days on IM 30/30 days on mobile 30/30 days).This leads right into a discussion of the position generator and its usefulness in this study. For analysis purposes I will describe the positions in terms of prestige (high, medium, and low.) The interesting differences observed from this analysis would be the difference in social capital between the old and the young. Though 60% of my sample (12/20) knew at least one person with high occupational prestige, 8 out of the 12 (67%) who knew someone on this level were from the older demographic. Not surprisingly, the older demographic in this study tends to be better educated (only 2 participants never had any collegiate training) with more range, extensity, and upper reachability in their contacts.

Nan Lin reasons that since social capital refers to the resources embedded in social structures, that the position generator provides a good way to understand access to such resources. The fact that this measurement is content-free is both an advantage and a disadvantage. According to Granovetter, weak and bridging ties allow us the ability to access diverse resources and take advantage of new opportunities; however, there is also data (Wellman) suggesting the strong ties are more empathetic and more conducive to support exchanges. This ambiguity detracts from a true understanding of social capital. The position generator may allude to the resources in the social structure; however it is inadequate in its description of the mobilization of these resources. For example, my mother reported knowing a person of every position on the list; however, I cannot recall any sizable opportunities she was rewarded over others for having such extensity. Then when we examine her name generator results, the entirety of her network is kin (more specifically her 4 sisters whom she contacts regularly.) These results are conflicting in that although it may appear as though she would have a range of ties listed (reflecting the range of social support of which she has access,) the only ties listed are those of kin suggesting that when one thinks of social support only strong ties are elicited. Perhaps the position generator is more indicative of the resources mobilized/initiated by one’s stressor network.

The idea proposed by Kazin that community has disintegrated into a “mass of atomistic and alienated individuals” is not supported in my findings, as both men and women appear to be kin-keepers. The only two atomized individuals ironically lived under the same roof, which casts doubt on how atomized they truly are. There is evidence that over time networks tend to be dominated by more kin and smaller on average. While the older demographic tended to have more extensive ties, consistently kin are listed as those with whom “important matters” are discussed. The effects of new media on relationships is also apparent in my findings as the older group tend to discuss important matters with those close in physicality (land lines, and in person contact favored) while the younger group slightly favors new media to maintain contact (Email, IM). None of those sampled in the older group reported using IM while in the younger group that mode of media was more commonly used. Perhaps SMS messaging could be included next time in order to see further difference between the demographics. My favorite part of the Kazin article on community is as follows:

“Individuals’ bonds to one another are the essence of society. Our day-to-day lives are preoccupied with people, seeking approval, providing affection, exchanging gossip, falling in love, soliciting advice, giving opinions, soothing anger, teaching manners, providing aid, making impressions, keeping in touch-or worrying about why we are not doing these things. By doing all these things we create community.”

To me, this is the essence of our Network Measures assignment. We are analyzing all different levels of personal community. The position generator gives a general idea of the heterogeneity of our personal networks while the name generator is an even more in depth view of our general social environment. Media usage shows accessibility to contacts and the name generator graph shows closeness and density of ties. If this study were conducted on a large scale in a small community (given that participation and completion were high,) one would be able to discern clusters, hubs (prominent people in the community), and also be able to view community hierarchies by prestige. It is interesting to view in my data that only in networks of large geographical difference are there strangers in the network. For example, my friend Mawuse has one roommate from college (O.B.) listed while his other kin ties are strangers to this contact. This is also visible in my best friend Catrina’s network where two of her friends from high school are strangers to me. These forbidden triads do in fact exist due to lack of resources and motivation to resolve the intransitivity. Other, more local networks like that of my friend Katie’s (one of the largest networks observed in my sample) are dense, closely knit circles where each contact at least knows one another.

I almost wish that we had read these articles earlier in the semester since the ghetto has been made a commodity marketed and packaged by mainstream culture, rather than seen as a place that needs resources, not a microscope. Social isolation is hardly ever pointed to as a major contributing factor to the state of the ghetto today. Many times the government and private organizations think that simply lack of resources is what keeps people in the ghetto, when in fact mental prison is the real cause of the immobility of this class. In the media fueled glamorization of the ghetto I feel that people drift further and further away from the reality of what ghetto living entails. Those of other classes see rappers like Nelly and 50 Cent rapping about the ghetto and suddenly a glimmery picture in their minds is formed of an edgy place with naked dancing women, rappers with chains, and rhythmic music. The reality of the ghetto is a place where those with limited or no resources raised kids who in turn have limited resources and no social reach, a breeding ground for ignorance, desperation, and crime. Those in the ghetto tend to have no contacts outside of their immediate local area. This isolation is just as instrumental in the contributing to the emiseration of the ghetto as the lack of resources.

The Fernandez and Harris piece so eloquently delineates the amendments that need to be made to the social isolation theory in order for it to hold water. Perhaps the most important and interesting point made was that those in the ghetto have no access to those who are part of the “mainstream.” Those considered mainstream have stable employment and are not on public assistance. The fact that most ties in the ghetto are inbred means that the few close ties help by people are characterized by suspicion and multiplexity. It is interesting to see in the results, especially among poor females that tend to have the have the smallest networks. While women tended to be most often nonworking poor I was floored by the suggestion that their status as nonworking has much more to do with their isolation than the effects of poverty. When I thought about it, this makes sense. Most of those different from ourselves we meet at school or work, therefore, for those who do not have a job their networks seem are truly confined by the bounds of the neighborhood. According to Fernandez and Harris, the non working as a whole report less friends and more close kin ties. Those who work have significantly bigger vaster networks.

Question:

What type of programs could be implemented to combat the social isolation of the poor?

The second article by Marsden and Hurlbert is interesting because I completely thought that their findings on social isolation would completely support the Fernandez and Harris piece. Marseden and Hurlbert found no association between tie strength and mobility outcomes or access to social resources. That way it would appear as though there is no connection between the immobility of those in the ghetto vs. others. All the data presented on the structure and density of these networks suddenly pales in comparison to this data which suggests that there is particular pattern showing that more weak or strong ties affect one’s job obtaining ability. This leads me to wonder, if the findings of this study is in fact true, then what can be done to help those in without? Is it more of a luck of the draw thing than a systematic network mobilization? The finding that the effects of social measures are outcome specific was also a let down from my point of view. I was hoping for data specifically relating to the have-nots instead of the sample selected for this study.

Question:

If there is no association between tie strength and mobility of outcomes/ access to positions, look at your answer to question one and explain how your approach would now differ in response to the disparity in the ghettos.

http://www.mysocialnetwork.net/blog/mt-tb.cgi/240

I anticipated this project’s outcome for so long and on that dreary Thursday before Thanksgiving it was quite anticlimactic to find that I was let down by my network! I was completely confident that my folder was one of the two which had reached the target. Briefly I will discuss whether my hypotheses were supported in the results, I’ll offer some theories for why my seemingly perfect path deviated (or died rather), and then the class results will be examined and compared to the Stevenson et al. results.

I originally hypothesized that in selecting a weaker interracial tie versus a closer more homophilous tie, that social distance would be more efficiently bridged. This hypothesis was inspired by the Korte and Milgram study on "Acquaintance Networks Between Racial Groups" as well as the Granovetter study exploring the "Strength of Weak Ties." I also hypothesized that since I had more multiplexity with this tie as well as higher frequency and duration of contact with this tie per week that I would have more control over the process, and she would be more motivated to direct the folder to her next link. This is supported by the McPherson et. al study entitled, "Homophily in Social Networks." In having this added multiplexity in the tie I thought I would also have the increased ability to inquire about the whereabouts of the folder and a better ability to ensure that it reached the target. My tertiary hypothesis was that the chain would only cross affiliations one time and that it would be at the time of delivery to the target. Though my folder did not reach the target, it is still interesting to examine the characteristics of each link. This hypothesis was mostly based in the Korte and Milgram study of “Acquaintance Networks Between Racial Groups.”

H1: A Weaker tie can span more social distance and network distance therefore it is the idea first link.

After reading the McPherson et al piece discussing Homophily in Social Networks as well as the Granovetter piece, I was convinced that in order to bridge the social distance that exists between me and the target that a weaker tie would be ideal. McPherson’s argument that homophily limits people’s social worlds was evidenced when I took a step back and examined the make up of my close ties. Each time I asked a close tie for help either they went blank (“What’s Wistar?) or they had no clue who their next link would be. Jim, my other choice for a pass off person had connection with the “science world” here at Penn; however had contact with no one from Wistar.

H2: Multiplexity will increase likelihood of successful path.

My second hypothesis hinged on the idea of multiplexity. The McPherson et. al piece lead me to believe that due to the high multiplexity characteristic of my tie with Erica that she would be motivated to reciprocate my actions. Since we are roughly structurally equivalent in our Track network, the same gender, participate in the same event (throws), and have value homophily I thought that these characteristics made Erica a clear choice for hand-off. I was also relying on the fact that aspects like duration of tie, and frequency of contact would influence the path of my folder.

H3: The folder will only cross affiliations one time from Student to Staff.

Though the Korte and Milgram Study particularly examined the travel of folders to targets of a different race, I think in our small world, rather than race being the “obstacle” per say, bridging affiliations would be the “obstacle” in this case. As observed in the Korte and Milgram study, the most successful chains only crossed races at the target and similarly I thought my chain would only cross affiliations at the target.

Theories for My Chain Attrition:

While I thought I was covering all bases by selecting a tie where there exists multiplexity in the relationship as well as enough social distance for our networks to largely not overlap (weak tie), I thought that there was no way for failure. Unfortunately my chain died after the third link. This puzzled me at first since I remember Erica saying that the woman she handed it off to (Priya) knew someone working in the same lab as Antonio! I mean since we aren’t spanning the country or anything like the Milgram study I thought that 3-4 ties would suffice. If six links can theoretically connect me to anyone in the world, then shouldn’t 3-4 links connect me to anyone on PENN’s 7 block campus? One would think that in such a small geographic area social distance can be easily traveled, however this is not true. As Milgram suggests in his “Small World Problem” piece, communication is dictated less by physical distance and more by social distance. In my case the concentric circles separating my network from Antonio Polley’s proved too difficult to navigate. According to the information I received from Erica (my first link) my chain was one link from completion nearly two weeks before the folders were to be returned. My chain was to travel this path:

Charli-Erica-Priya-“Student Working in Lab”-Antonio

Unfortunately it died after the third link. Perhaps I overestimated the motivation of busy students to pass a folder with no urgent message on to a target. I also perhaps overestimated my links knowledge of her social network. Being that Erica didn’t have a grade depending on the completion of this chain, I’m quite sure that she didn’t give her network as much painstaking thought as I did. As for Priya, the third link, evidenced in the fact that it took her 11 days to ever pass on the folder, as well as the fact that she sent back postcard Roster #10 instead of #3 and dropped it in the inter-collegiate mail system; I’m quite sure that there was little attention paid to instructions or her network structure. Not much careful network visualization was done by this point in the chain and from Priya’s actions it seemed as though this was an inconvenient task.

It seems that the careful thought given to my link was not a proxy for chain success. According to the Killworth study exploring path accuracy and next choice accuracy, nearly 80% of paths deviate from the conceptual most efficient path (this is a high rate of error) and nearly half (48%) of links have next choice accuracy with respect to one’s network. This could be the basis for errors in my chain, and I’m sure that the less thought and time given to the task the higher the rate of error for next choice accuracy. Rather than conceptualizing my chain as a simple 5 person link, I should’ve viewed it with more depth. The five links after all represent 5 discrete social structures.

Class Results:

In examining the class results aggregated, I believe that there are a few trends that were supported in the readings as well as a few trends which are a bit more difficult to conceptualize. It appears that one group; the Susan Yoon group had much more success in relation to the Antonio Polley group. This suggests that the GSE is much closer in social distance to undergraduates than the SM. The mean number of intermediate links was longer for the Yoon group at 4.5 compared to Polley’s 3.25. The percentage of group success was higher at 80% (Yoon) compared to 25% in the Polley group. These startling differences in success rate speak more to the network accessibility of the GSE in comparison to that of the SM. The difference between 4.5 social structures between the participant and target and 3.25 social structures of difference are considerable. When reviewing the literature on past small world studies, a 25% and 80% success rate are particularly impressive. Perhaps this speaks to PENN student networks being systematically better at traversing social distance (when confined to a campus network)?

There is also an interaction with gender which is well documented in both group’s results. The Yoon group had 87.5% of completed chains’ final transfers sharing the gender, while 100% shared gender with their final link (competed chains) in the Polley group. Milgram suggests that certain types of communication are conditioned by sex roles. His Kansas study similarly found that participants were 3 times as likely to pass folders onto those of the same sex. Perhaps this tendency is ingrained in us from childhood. The Killworth study suggests that children are more likely to delete a cross-sex friendship than add one. Therefore there is evidence of conditioning to be gender segregated thus less likely to solve intransitivity across genders. Whether these effects are attributed to nature or nurture is inconclusive, but as children mature, it is also observed that social communication activity is relegated to same sex cliques in adolescents. Even in adulthood (when kin are separated from the mix) many tend to have networks mostly homophilous in terms of sex. This could explain the prevalence of same sex links in our class results.

There was also a marked time difference in terms of mean time between transfers. Since 80% of the Yoon groups’ folders arrived to target I thought it would be meaningful to explore any differences here. At first I thought that the time it takes to navigated social distance is proportional to the network structures separating the link and target. Since the mean number of intermediary links was 3.25 for the Yoon group perhaps this suggests that more time would be needed to traverse and additional network (since Polley’s mean intermediate tie is 4.25). I couldn’t have been more wrong! It is completely puzzling that the Yoon group has a success rate of 80% but it took on average longer to travel, while the Polley group has a success rate of 25% and it took only 4.45 days on average for completed chains to get to the target. The Yoon group has an abnormally high success rate since most literature predicts (or has shown) success rates between 13-33%.

Possible causes for failure in the Polley group could be attributed to the percentage of transfers to people in the same school. Completed chains only passed of the folder to those in the same school 55.5% of the time while incomplete chains passed the folder to those in the same school 71.43% of the time. McPherson would contend that by passing off the folder to a homophilous tie, that the structure of that tie’s network would resemble one’s own. Therefore the reach of that links network wouldn’t be enough to close the social gap between the participant and the target. Since weak ties have access to more diverse information and have different social circles it is much more likely that they could reach the target and bridge the gap. It is interesting to note that for the two successful Polley chains, the chains stayed in the SAS until crossing over to a different school at the target. This provides more evidence that schools at PENN are similar to the race obstacle in the Korte study.

While passing the folder on to a homophilous tie in the Polley group was a detriment, in the Yoon group, 75% of final transfers were within the same school and nearly 40% shared affiliation. Perhaps these findings suggest that the further the social distance between a tie and target, the more one should utilize their bridging social capital through weak ties. When there is less social distance traveled mobilizing homophilous networks works remarkably well.

In comparing our class SW study to the Stevenson study I find that there are several major differences which likely contribute to the differing success rates between results. The first major difference would be the fact that the sampling was randomly dispersed among all four classes of undergraduates. Due to the nature of our class there are only junior and seniors enrolled so our results reflect the trend that students tend to be more engaged with campus networks as they age. Secondly we also were given more difficult to reach targets as opposed an obvious target. The Stevenson study selected the dean of management due to the fact that he was located in a physically accessible and high traffic area. The exact opposite was Dr. Hampton’s goal in selecting esoteric targets that seemed at first like a needle in a haystack here at PENN. The sample size of the Stevenson study is also more than 3 times the size of ours, which has an effect on the interpretation of our statistics. For example, in the Yoon group only two people did not complete the chain therefore the statistics describing incomplete chains are skewed due to low failure rate. The overall success rate for our study between both groups is 56% compared to the 27% success rate of the Stevenson study. There are also idiosyncratic differences in the results like the fact that no student ever passed a folder to a student in a lower year. This was not at all true in our study as at times up to 40% of participants passed the folder to those in a lower year. The mean intermediate links in the Stevenson study is 1.25 and this is in stark comparison to our means of 4.5 and 3.25. Since the target was high profile and easily accessible this difference in chain lengths between groups is understandable. I was however surprised at the low completion rate for these same reasons. I wonder if theses students were graded on this project? If not, problems with motivation could explain some of these results as well.

The Dickinson et al article definitely surprised me in that the evidence truly suggests that there could be some serious psychological effect associated with the lack of companionship. This article lends more credence to “the power of suggestion” and the highly communicable nature of the human species as well. Though the authors do point to the possibility that confounding factors could explain their findings however I am still very surprised at the observable findings of this study.

The Bearman, Moody and Stovel piece explores the structure of adolescent sexual networks. Based on the premise of epidemiological research, the Bearman et al. paper seeks to further understand how STIs travel throughout a network. Rather than assuming random mixing of individuals, this study attempts to get at true patterns in exposure which leads to the diffusion of disease. The idea of hubs in a sexual network is profoundly important for its implications on controlling infection STIs from spreading most efficiently. Rather than once again presenting evidence supporting the bridging process, the spinning tree takes into account the length of relationships as well as their cycles.

Question:

What other advantages are apparent in the spinning tree approach?

The Cohen and Brissette article was interesting in that it examined those with more diverse social networks vs. those who had more homophilous networks. It tended to be the case that with more diversity in one’s social network there is a decrease chance of catching cold. The article also explains how community and group membership plays a role in illness as well. Positive affective states are hypothesized to create greater immune function. Biologically this makes sense since when one is under stress or strain the immune system functions less effectively due to decreased functionality of the brain. This has interesting implications for those who feel alienated and powerless. This reminds me of the articles of last week focusing on the negative social affects of gaming etc.

Question:

After reading the Cohen and Brissette piece, do you think that perhaps gaming should be considered a health hazard?

1) Cat-7-teammate, friend
2) Joey-5-brother
3) Mommy-4-Parent
4) Victor-3-Acquaintence
5) Tina-3- teammate, friend, classmate

2) When examining the relationship between the medium of communication used and the strength of the tie, I find myself very surprised in the fact that the bulk of my exchanges were with weak ties that I ranked with a closeness score of 3. More specifically Victor, a weak tie, ranked in the top five in terms of numbers of exchanges with me over the 7 day period (3, 2 email, 1 cell phone). This is a perfect example of my attempts to mobilize network resources in the forms of advice, and knowledge in order to give me a competitive “edge” in my final round of interviews with my favorite prospective employer. There are several other weak ties that I contacted over the 7 day period in hopes of giving myself a competitive advantage in the final round and they are as follows: Julie, Barbara, and Susan. Though the frequency of contact only measured 1 for each of these weak ties, the content of the exchange definitely benefited my presentation on 11/8. The Granovetter article discussing the strength of weak ties is useful in understanding this exchange evident in my data between 11/6 and 11/8 (and even a bit thereafter.) In these weak ties reciprocating my request for assistance (by passing along valuable network data), the importance of inter-group relationships or bridging ties is shown. As Granovetter suggests the removal of a weak tie from my social network would be devastating both in terms of diversity of information I could receive, and the speed of is transmission. The most common medium used for these ties is definitely email due to the fact that in the business arena of today, email is the fastest way to get someone to follow-up. Perhaps email was used more often when I sought career help since there is an almost unlimited ability to revised, reword, and polish the message before it is viewed. The element of complete control makes email my most popular medium for mobilizing social capital among weak ties.

Those scoring a 2 in closeness are relegated to family and teammates. Most of those ranked moderately close are my teammates. My Grandmother and Uncle were the only familial ties with moderate strength, and there are two random guys I used to date in this category. Generally the cell phone was the medium of choice for this group. Although there are several exceptions where SMS was used, SMS primarily was used for urgent messages. This contrasts with the Ling article which directly allude to the uselessness of certain conversations and interactions initiated via SMS. In my data SMS messages were primarily used to communicate last minute changes to plans as well as urgent information. For example the SMS received from an intermediate tie, Steph, was specifically relaying information about a practice cancellation. The cell phone medium is used among intermediate ties usually when the information needed to be relayed is too complex to be adequately explained via email. Since most of my intermediate ties are linked to the Penn Women’s Track listserv, the information exchanged with me on the cell phone was usually highly specific.

Close ties generally used IM and cell phone as their medium of choice. My brother and mother almost exclusively used the cell phone in order to initiate any business whether it be travel reservations for Thanksgiving or news on family matters. The cell phone is most useful for kinship ties since intonation, emotion, and other semantic indicators are better picked up on via phone. As described by Putnam, close ties or central nodes within a network are characterized by emotional intensity and intimacy. Cell phones have the largest bandwidth of all new media, therefore it makes sense that cell phone would be the medium of choice between my kin and I. Email was only used to verify information previously exchanged via phone. In the case of my best friend, Cat, with who I shared 7 exchanges over the 7 days, IM dominated our exchanges. Since Cat and I have a relationship characterized by a lot of multiplexity, and a lot of time spent together in person, the IM is mostly used between us to exchange useless messages and random thoughts. We typically talk everyday several times on IM. The data does not quite accurately reflect the usual frequency with which we talk via since this particular week was an interviewing week for me. Conversations between the two of us also typically had no clear beginning and ending. Our conversations were more sporadic and informal with no clear beginning or ending.

The relationship between the medium and type of support exchanged is quite interesting. Cat, my best friend at Penn, is actually the person with whom I conversed with the most over the 7 days of observation. Cat offered the largest range of support, though typically we conversed using one medium, IM. She provided Emotional aid, Companionship, Organizational information, and small services. This is most likely due to the fact that our relationship is steeped in multiplexity. We live in the same building; we’re on the same team, and have the same major. Surprisingly most of the support she offered was initiated through IM. Rather than contacting me via phone just before a night out on the town, she would IM me to see if I was ready rather than call. It’s interesting that the medium which rivals SMS in terms of bandwidth delivered the most varying types of social support to me in this observational study. This seems to contradict the Mesh argument that new relationships and weak ties are best maintained online. Since Cat is my best friend in the whole entire world, this just goes to show that IM can serve as an interesting way of communicating with strong ties as well. The fact that IM does not directly interfere with activities conducted simultaneously like watching TV, talking on the phone or even doing hair, adds a unique advantage to IM. IM tends to accommodates those who multitask, like myself. Nie would argue that because Cat and I regularly interact using the Internet that the quality of our interaction is inevitably inferior when compared to face to face contact, and I would disagree. Many of our IM conversations feature commentary on events that we experienced copresently, but that we were unable to be comment upon at the time. Restrictions imposed on us by general rules of social grace, make some of our conversations inappropriate in real time, therefore, IM is the perfect setting to share, or “gossip” off the record.

In terms of Job information, the medium of choice tended to be email due to the infinite control and framing possible with every message exchanged. Victor offered his expertise in order to better prepare me for my final round of interviews, and of the 3 exchanges, two were conducted via email while only one conversation was held via cell phone. Generally job and organizational support was exchanged via email as reflected in my data. The use of email has everything to do with control, and the usefulness of a referencing file for pertinent information. A gross simplification of my data would suggest the IM is primarily for companionship (late nights of homework), while email is primarily used for exchanging job information and small services. Cell phone use cannot be categorized in terms of the types of support exchanged. Almost every category of support was exchanged via cell phone in my data. The fact that cell phone usage cannot be nailed to one type of support exchanged perhaps is an explanation to the popularity of cell phones. In addition to their defiance of the constraints imposed by place, any type of support can be solicited moment by moment. For example, from my data, on 11/9 after speaking with my brother via cell phone (exchanging emotional support), I spoke with Haijing about a class project, and shortly thereafter I spoke with my boss about objectives for the week at work.

Though there’s no clear relationship between the how long I’ve known a tie and the medium which is used, I think the medium used is more a function of the support exchanged, and the most effective manner of conveying information and tone. There is also trend where the further away a contact is in terms of mileage, the more likely they are to initiate an exchange via cell phone. Perhaps the increased bandwidth via cell phone is preferable to SMS, email and IM. These results could also be skewed by my preference for cell phone based communication, rather than by characteristics of the medium used. My brother for example is the furthest away from me (560 miles) and he only contacts me via cell phone!

3) By far, the most popular place for me to exchange support with nodes in my network is from the comforts of my own apartment. Good ole’ home! There are a few interactions which took place in the street, but generally they were short in duration. This is quite interesting in that, although I have a mobile phone, very rarely do I use it in public or semi-public places. I treat my cell phone like a land line, and I am generally available for interactions with copresents in real time (rather than suspended in virtual conversations via mobile.) This perhaps contradicts concerns posed by Goldenberger and Ling. The idea that those in the urban environment are disconnect and unavailable to copresents through their use of cell phones perhaps is a little exaggerated. Good old civil inattention pretty much contributes to much of disconnected urbanism. The fact that the vast majority of my interactions occurred from my home, (regardless of medium) does seem to support the theory that communication and community activity is becoming more privatized. The private realm is where I can wear the hat of business woman, concerned sister, daughter, group member, discus thrower, and best friend all while wearing my pjs. This suggests that privacy is at odds with usage of new media. Although the Okabe article alludes to the popularity and privacy associated with SMS messaging, for those of us who do not like SMS and who do not subscribe to this service, privacy equates physically going home.

To conclude, I was very surprised by how few new media exchanges I experienced over the 7 days of observation. Perhaps the low number in part has to do with the fact that my observations were conducted during a week where I had 2 exams and a final round interview.

In examining the structure of opinion leadership, the Tarde article really forced me to think about the role of homophily and heterophily in the search process and the diffusion of information. Since Burt structurally positions opinion leaders as those bridging nonredundant ties and straddling the edges of many circles, it is difficult to understand how these opinion “brokers” are granted access into multiple groups that are heterogenous enough to have nonredundant ties. Tarde suggests that greater social participation and accessibility afford opinion leaders more diverse social circles, however I’m not quite convinced that precious information from these circles will be diffused simply on account of co-membership in an organization. It has been my experience that it takes more than simple membership but rather a deep bond with an organization before one can capitalize on coveted information and connections possessed by group members.

Question:

How are opinion brokers structurally similar enough with those in different clusters to relate to and influence group members, while simultaneously heterogenous enough to integrate into several other social circles?

Perhaps there are marked differences in diffusion of informational flow vs. a purposeful search for information. When in search mode for example, the Curtis and Lambert piece spoke to the importance of social cognitive mapping. Apparently when one is seeking a specific type of assistance the better developed this “map” is, the more likely one is to find the resources desired. Diffusion differs in that is usually a natural process of information flow. It’s more a case of chance and good timing than strategic goal attainment.

I was also interested in the Curtis and Lambert discussion of social acceptability of deviant intentions and the likelihood of these intentions converting into actions. Usually in highly homophilous networks where deviant actions are not well tolerated, intentions are the only form of social deviance that can survive, however, the more developed one’s social cognitive map, the more likely he or she will be linked to targets in covert circles who can turn deviant intentions into actions! The element of scope is another important element of this article further complicating matters. When speaking of deviance it can be on an individual level versus a community level. There are instances where deviance is the norm, therefore, these highly homophilous networks aid in a search for performing deviant acts. Bridging ties are especially important in covert network analysis since the less knowledge one has of her social cognitive map, the less likely she is to be successful.

Burt’s assertion that contagion stems from equivalence was quite and interesting since many people tend to think of opinion leaders as those central to a group as opposed to those who have the most heterogenous strong ties to mutiple groups. The fact that structural similarity breeds influence has quite significant implications for public health campaigns and other socially relevant messages targeted at changing the behaviors of the masses. As shown through the research in the Tarde article, when opinion leaders were sent to promote natural birth there was an 85% increase in adoption of vaginal birth delivery compared to no significant results of an audit campaign. This shows that perhaps the most effective and monetarily attractive method of changing behavior in a group is through targeting the message to opinion leaders.

Question:

Describe how HIV education campaigns and Anti-smoking initiatives could benefit from a shift in strategy to winning over opinion leaders.

A soon as I finished the second paragraph of the Marks article I went directly to Facebook and erased my personal information from the prying eyes of the NSA! The thought that the government is actively funding research in order to “connect the dots” between my purchasing behavior, my online community associations, interests, contacts, and phone records make me wonder if there is such a thing as privacy in America today. Once again we find ourselves trading freedom for safety. But, before the rant, I believe it is interesting to examine the ways in which social network data is being manipulated by the NSA in order to gain understanding of individuals through network associations and community membership online. I believe it was during the week centered around Measurement that the question was posed, “What would we ever do with all this data once it is collected? Who would care?” and to that question, the Marks article points directly to Big Brother. RDF tagging makes navigating through the chaos of the web more logical and manageable. With this data the NSA can piece by piece profile your life from your property records to the color jeans you fancy.

The Kleinberg, Lawrence paper suggests that the highly decentralized web environment has naturally grown over the years in distinct structured manners. The structure observed in my estimation has developed as a result of homophily. Like being attracted to like is in essence how hyperlinks work. Communities are ascertained by the presence of cohesion (indicated by the interlinking of web pages within a group to one another), and by the interactions between hubs and authorities. Not so surprisingly, content similarities and structurally distinguishable communities tend to coincide among web pages.

Question:

Which method of recognizing coherent community structures would be most useful to the NSA?

Can you think of an additional way to demarcate communities on the web?

I enjoyed Wellman’s discussion of “glocalization.” The idea that one can access the globe instantaneously and while also being connected locally is interesting in its implications to privacy. In light of recent 20/20 reports detailing adolescent risky behaviors online as well as adult predators and their arrests, I wonder why people expose their most personal selves online when the Internet is almost the most public place that exists! It is almost counterintuitive that in knowing that the eyes of the world can see your every move online, that one would still tend to disclose damning information about herself online? Wellman’s article suggests that people have a good idea of the sociophysical places in which their messages will be observed and I tend to disagree due to these blunders that are captured with more and more frequency where people tend to treat the Internet as the most private of places rather than the most public.

Question:

What is it about the Internet that makes people oblivious to the sociophysical places where their portrayals and messages will be seen?

Lastly, the Ellison et al. piece was interesting because it shows that the facebook is used by students to strengthen offline ties more so than initiate new ties. I even find that to be true here at Penn. Many times I have found myself in a conversation on whether another PENN student and I are “facebook friends.” This conversation usually comes up after considerable interaction rather than on a first meeting. The fact that Facebook enables students to better maintain bridging social ties (which are important in obtaining diverse information) clearly sheds light on the positives associated with Facebook membership; but at what risk? Students in the study reported including relationship status, cell phone numbers, residences and classes online! The false assumption that the Facebook is a closed network contributes to student’s feeling at liberty to “let loose” online. As stated in the Marks piece, just think of everything about you online being stapled to your resume. I bet you’ll be a little more careful then!

I felt like I had déjà vu this week as I was reading and taking notes. The word that kept popping up was multiplexity. Although theorists of the field hypothesized anything from the Internet “achieving what highways did not, in bringing people together,” to the internet completely atomizing us and further privatizing public and parochial space. The Kronholz article is amazing in that it is a clear demonstration of the ability and proclivity of online users to exchange social support and favors with complete complete strangers. This harkens to the section in the Wellman article discussing generalized reciprocity. According to Wellman, the more one feels like part of a community the more likely she is to contribute and help others. Apparently this is part of building one’s identity online through deeds since other characteristics are downplayed by the nature of the medium. The idea that a chain letter could generate 160,478 responses from 189 countries and all 50 states is incredible. The way this message traveled just shows the reach of IT and the proclivity towards reciprocity, even when in response to a chain letter of all things. I was completely surprised by the success of this girl’s chain letter since I know that when I receive chain letters I don’t even open them. They are automatically spammed out of my mailbox! Although I found the Wellman spin on the issue of reciprocity among strangers interesting, I’m not sure that group attachment is what can be pointed to in explaining reciprocity among complete strangers. From some of our other readings it became clear that many IT users don’t view the technology as a completely different world, but rather an extension to real-time interactions. I’m not even sure that his argument that helping others promotes self esteem would cover the findings of the Kronholz article! This is a unique phenomenon because in real-time, people are very apprehensive about interacting, and exchanging anything (sometimes even a glances) with strangers.
What “group” would IT users identify with, if any at all? What are some other reasons or theoretical constructs that could explain reciprocity among strangers online?
Question:
IT, What Has it Done to Us?!!?!
And now the milieu of articles discussing, multiplex relations: The Baym article very clearly shows that college students use the internet as much as the telephone and perceived as high in quality (though slightly lower than face-to-face interaction.) I particularly enjoyed the part which drew attention to the fallacy many researchers in the past examined Internet use by looking at heavy vs. light use etc. This belief parallels the direct effects model of media consumption which hasn’t been supported for a number of years! Ultimately Baym’s research shows that IT based communication both supplements offline activity and current relationships, while taking on a unique social quality in cultivating weak ties.

Dr. Hampton’s article points to the tendency for ties made online to migrate offline and vice versa. Since the Internet has limited bandwidth, as one begins to fancy a weak tie met online, she begins to cultivate that media through other media like phone, and perhaps eventually face to face. The most interesting aspect of the Hampton argument is by far his recommendation that IT could become central to reviving public participation and interactions.

Question:

Do you truly think that IT can reverse this overwhelming trend? If so what is your theoretical basis for believing this?

The Gustavo Mesch study was very interesting in that it studies Israeli youth as opposed to American youth. It was refreshing to see a study that didn’t sample American youth. Finally, rather than postulating about the effect of IT on social networks we can actually see some results from a different culture. I was surprised by the fact that when asked where the respondents had met their first friend that 12% replied online. Out of a considerably large sample (987) 12% reported having met their first friend online. Also a higher percentage of males than females reported having online friends. In terms of multiplexity, the study showed that friends met face to face first seemed to last longer than other relationships. Why is this?

Question:

Why aren’t durations of relationships comparable when the tie is met online instead of met face-to-face first? Is multiplexity create relationships that last longer, but only when initiated face to face? Why does multiplexity only work on one direction in this sense?

The process of evalulating and developing the theory behind and the measurement of social capital is in its early stages . This weeks readings proved challenging due to the nature of operationalizing social capital. It is interesting that network analysis is used in two vastly different processes, namely the communication audit process as described and evaluated by Zwijze and Jong; while also being used in evaluating social capital in the Van Der Gaang and Snijders piece. Rather than creating measures that specifically fit for each of these scenarios it seems as though researchers have mostly just reached for the available and assigned different constructs to the same measure. This at its core is problematic, therefore, I was glad to see some analysis of effectiveness on the part of Zwijze et al. and Van Der Gaang et al.

Zwijze and Jong attack the quite complex issue of isolating auditing techniques to evaluate their strengths, weaknesses and advantages. Network analysis is great for mapping communication structures, tracking density, frequency of interaction and measures such as these, yet network analysis alone doesn't achieve the goals of a communcation audit. Assessing the quality of communication cannot be adequately understood through analysis of patterns of communication and ties etc. Though sociometric questioning can be posed through interview, free recall, specifc time period recall etc, validity questions come to the fore partially from self report and in part due to the fact that participants may be motivated to skew their responses in order to protect their network of ties (as to not be exposed) or in order to appear more conncected than they really are. Being that communication audits are ceterainly conducted by the company in question (or hired contractors) people are very careful about the information they disclose and its implications. I particularly liked EECO analysis and the Diary approach since they more allude to the quality, style, distortion and effectiveness of communication. In fact I believe that it is essential that in addition tonetwork anaylsis and sociometric questioning that ECCO analysis or Diary studies be examined since people are notoritously bad at recalling their social networks in a given time frame.

The Martin and Hampton paper was great in that it took a closer look at current methods of conducting network analysis and showed that there is a marked difference in reliability and validty when multiple name generators are used. While the single name generators of "discuss" and "socializing" were close for some measures, they did not accurately discribe network characteristics. I liked the MGRI method for the simple fact that it maximizes construct validity. Without construct validity it isn't clear exactly what has been measured, or what the results actually mean. The only question I have is whether the exchange approach to questioning fully encompass the idea of social support? In my opinion only one aspect is covered sufficiently and that is instrumental aid Ironically the "discuss" and "socializes" question (which are questions hinting at emotional aid and companionship) were the single name generators. Perhaps more questions should be targeted at the emotional and companionship aspects of social support.

Question:

What is a good possible question for a MGRI which alludes to social support and companionship?

Should there be more questions focusing on this aspect of network analysis? Why or Why not?

By far, my favorite article this week was the piece on social capital for the simple fact that it further confused and complicated my understanding of how to measure social capital. In fact, I even found it difficult to think of better alternatives to operationalizing social capital and really showing the returns on social capital. The idea of capital revolves around returns and being able to isolate the effects in a compelling manner. Although many agree that there is such thing as power inherent to structural position, it is notoriously hard to make causal claims. The most talked about example would be job placement and the mobilization of network contacts to be place in a position, but the troubling construct of human capital makes it almost impossible to definitively point to obtaining a job as the mobilization of social capital as opposed to the effects of human capital. This is also ehtically problematic as well. How do individuals access these resources? More troubling though is how do we assign network characteristics meaning or ranking in terms of social capital? The Var Der Gaang article similarly pointed to the necessity of having multiple measures in order to assess social capital. The most interesting and problematic thing about the Van Der Gaang piece was the idea of a generalized social capital measure for nations. How would we make sense of, assign value to and analyze the social networks of a nation? Is this even possible? What in fact are the resources being mobilized and how can they be measured? These are all question that come to mind when reading about social capital.

Question:

What do you think are the best indicators to use of social capital? Can we ever isolate social capital from other tyoes of capital?

DO you think it is possible to have a general social capital measure for the US? How long would this take?

The process of evalulating and developing the theory behind and the measurement of social capital is in its early stages . This weeks readings proved challenging due to the nature of operationalizing social capital. It is interesting that network analysis is used in two vastly different processes, namely the communication audit process as described and evaluated by Zwijze and Jong; while also being used in evaluating social capital in the Van Der Gaang and Snijders piece. Rather than creating measures that specifically fit for each of these scenarios it seems as though researchers have mostly just reached for the available and assigned different constructs to the same measure. This at its core is problematic, therefore, I was glad to see some analysis of effectiveness on the part of Zwijze et al. and Van Der Gaang et al.

Zwijze and Jong attack the quite complex issue of isolating auditing techniques to evaluate their strengths, weaknesses and advantages. Network analysis is great for mapping communication structures, tracking density, frequency of interaction and measures such as these, yet network analysis alone doesn't achieve the goals of a communcation audit. Assessing the quality of communication cannot be adequately understood through analysis of patterns of communication and ties etc. Though sociometric questioning can be posed through interview, free recall, specifc time period recall etc, validity questions come to the fore partially from self report and in part due to the fact that participants may be motivated to skew their responses in order to protect their network of ties (as to not be exposed) or in order to appear more conncected than they really are. Being that communication audits are ceterainly conducted by the company in question (or hired contractors) people are very careful about the information they disclose and its implications. I particularly liked EECO analysis and the Diary approach since they more allude to the quality, style, distortion and effectiveness of communication. In fact I believe that it is essential that in addition tonetwork anaylsis and sociometric questioning that ECCO analysis or Diary studies be examined since people are notoritously bad at recalling their social networks in a given time frame.

The Martin and Hampton paper was great in that it took a closer look at current methods of conducting network analysis and showed that there is a marked difference in reliability and validty when multiple name generators are used. While the single name generators of "discuss" and "socializing" were close for some measures, they did not accurately discribe network characteristics. I liked the MGRI method for the simple fact that it maximizes construct validity. Without construct validity it isn't clear exactly what has been measured, or what the results actually mean. The only question I have is whether the exchange approach to questioning fully encompass the idea of social support? In my opinion only one aspect is covered sufficiently and that is instrumental aid Ironically the "discuss" and "socializes" question (which are questions hinting at emotional aid and companionship) were the single name generators. Perhaps more questions should be targeted at the emotional and companionship aspects of social support.

Question:

What is a good possible question for a MGRI which alludes to social support and companionship?

Should there be more questions focusing on this aspect of network analysis? Why or Why not?

By far, my favorite article this week was the piece on social capital for the simple fact that it further confused and complicated my understanding of how to measure social capital. In fact, I even found it difficult to think of better alternatives to operationalizing social capital and really showing the returns on social capital. The idea of capital revolves around returns and being able to isolate the effects in a compelling manner. Although many agree that there is such thing as power inherent to structural position, it is notoriously hard to make causal claims. The most talked about example would be job placement and the mobilization of network contacts to be place in a position, but the troubling construct of human capital makes it almost impossible to definitively point to obtaining a job as the mobilization of social capital as opposed to the effects of human capital. This is also ehtically problematic as well. How do individuals access these resources? More troubling though is how do we assign network characteristics meaning or ranking in terms of social capital? The Var Der Gaang article similarly pointed to the necessity of having multiple measures in order to assess social capital. The most interesting and problematic thing about the Van Der Gaang piece was the idea of a generalized social capital measure for nations. How would we make sense of, assign value to and analyze the social networks of a nation? Is this even possible? What in fact are the resources being mobilized and how can they be measured? These are all question that come to mind when reading about social capital.

Question:

What do you think are the best indicators to use of social capital? Can we ever isolate social capital from other tyoes of capital?

DO you think it is possible to have a general social capital measure for the US? How long would this take?