Social Network Analysis

Social network analysis has provided researchers in multiple disciplines with interesting insight into social, cultural, and organizational problems. One concept that social network analysis has developed is the "Matthew Effect," which states that the more of anything you have, the more likely you will get more of it. This is particularly true for wealth. Why is this so? Social network analysis has demonstrated that "persons of higher social class have more diverse social networks as well as cohesive ones, whereas persons of lower social class have more geographically local cohesive networks but fewer weak-tie diverse networks that convey a competitive advantage" (Kadushin, 2012, p. 69).

In addition, social network analysis has also shown that hierarchy and authority in workplaces do not always reflect what Charles Kadushin called "management-designed hierarchy" (p. 94). In other words, informal hierarchies spring up that are not always aligned with what the hierarchy looks like on paper. Other studies have shown that well-respected scientists are given more attention than those who are lesser known even when presenting the same material. This "cumulative advantage [that prestigious scientists have] is not only psychological but institutional," Kadushin noted, as large scientific institutions have an easier time winning grant money and other support than less prestigious institutions do (p. 116). In other words, success breeds success because as one advances in terms of financial, cultural, and social capital, one's networks become more multiplex (diverse) and also become more homophilous with other financially, culturally, and socially successful people.

Many medical studies have also been completed using social network analysis as a framework. Do social support and dense networks increase or decrease a person's chance of becoming ill and having bad health? One might think that illnesses can spread faster in dense networks. And while they can—in fact, "in the case of spouses, there is compelling evidence that the health of one member of a dyad can affect the health of the other" (p. 169)—the support people receive from dense networks when sick can often "ameliorate the effects of a disorder once it is experienced" (p. 169).

Lastly, one study in the book that caught my attention as a writing scholar who has done research on citation practices was a study on how "the dynamics of blogging and scientific research appear to be different" (p. 118). Kadushin noted that in professional publications, scientists cited scientists with a rich publication history, but bloggers' rates of citation were not tied to how many previous blogs or articles they had written (p. 118). In other words, scientists' citation and collaborative "patterns . . . did not follow random . . . distributions, but rather [a] power distribution" (p. 115). For bloggers, it was the opposite. Even though the content and quality were similar, better-known scientists had their work cited much more often than lesser-known ones. These studies lead to a discussion of what is "social capital," defined by Kadushin as "resources made available through social relations" (p. 165). How many people an actor knows and "the role of social structure in inhibiting or facilitating the small world phenomenon" (p. 110) have implications for an individual's success or failure. Kadushin does not go much further discussing other studies directly related to writing studies—or even education, for that matter. I feel that given education's roots in the social sciences, this is a missed opportunity for Kadushin to reach out to readers coming from writing studies and education. While I believe this book is still worth the time of Kairos readers, we will have to take this methodology and the examples Kadushin cites and develop our own ways of connecting it to composition research and pedagogical issues.