The most recent issue of Human Communication Research has some really interesting articles. One of them is from David Huffaker, titled “Dimensions of Leadership and Social Influence in Online Communities.”

Abstract:

The purpose of this article is to examine the communication behaviors of online leaders, or those who influence other members of online communities in triggering message replies, sparking conversation, and diffusing language. It relies on 632,622 messages from 33,450 participants across 16 discussion groups from Google Groups that took place over a 2-year period. It utilizes automated text analysis, social network analysis, and hierarchical linear modeling to uncover the language and social behavior of online leaders. The findings show that online leaders influence others through high communication activity, credibility, network centrality, and the use of affective, assertive, and linguistic diversity in their online messages.

Watch Nosh Contractor‘s keynote speech at the VIVO conference on scientific collaboration. The talk is titled “Using Web Science to Understand and Enable Research Networks”

A new report out from the Royal Society for the encouragement of Arts, Manufactures and Commerce (RSA) discusses the benefits of using a social network approach to community regeneration (via @barrywellman)

From the authors:

Traditional approaches to community regeneration which define communities in solely geographic terms have severe limitations. They often failed to deliver on key social capital improvements such as improving trust between residents or fostering a greater sense of belonging.
In this report we argue for a new approach to community regeneration, based on an understanding of the importance of social networks, such an approach has the potential to bring about significant improvements in efforts to combat isolation and to support the development of resilient and empowered communities

Following on their work on the spread of health patterns (obesity and smoking) through social networks, Christakis and Fowler have published a new piece using social network analysis to track the spread of flu. By tracking flu among those nominated as friends (who have been shown to be more central than random individuals), public health systems may be better able to respond to outbreaks quickly. See the article here.

In a special online symposium published in July 2010, the Journal of Social Structure presents a gallery of social network visualizations. In introducing the symposium, JoSS Editor James W. Moody writes,

“For me, good network images help build our intuition about all those things that make networks special: the ability to see local detail embedded in macro structures, to distinguish intuitively those at the heart of a social system from those at the periphery, or to make clear the unstated schisms that divide social life. It is this ability to provide a richly contextualized micro-macro view that can span multiple dimensions that makes network visualizations worth the space.”

The gallery of 11 peer-reviewed visualizations includes a variety of visual approaches and networks, including those mapping political lobbying coalitions, Facebook friends, global trade, and in a visualization by ANN member and doctoral candidate Katya Ognyanova, the sharing of news topics among U.S. news media outlets. As Katya explains, “The research presented here proposes an exploration of inter-media agenda-setting. One of the big questions in the field is whether proliferation of channels and information overload have fragmented news content, rendering the idea of a consistent mainstream media agenda obsolete…The research demonstrates that mainstream media outlets not only have overlapping agendas at a given point in time, but also exhibit patterns of shared coverage that persist over time.”

For more on Katya’s visualization and the complete online symposium, go to: http://www.cmu.edu/joss/content/issues/vizsymposium.html

Damon Centola of MIT published an article in the first September issue of Science entitled “The Spread of Behavior in an Online Social Experiment.” In it, he suggests that tightly clustered networks have more of an impact on health than weak ties. To see an article about his work, go to this link.

Or check out the full article on the journal’s website.