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As one of the largest social networking sites in the world, Facebook holds a great potential for promoting health. In this exploratory study, we analyzed 1352 messages posted to an active Facebook diabetes group to identify the characteristics of the group. The results revealed that the group was international in nature. Users overcame language barriers to communicate with people with similar conditions. Users' interactions were structured around information, emotion, and community building. They exchanged medical and lifestyle information, and highly valued their peers' personal experiences, opinions, and advice. They also demonstrated a positive attitude toward the reality of living with diabetes and generously provided encouragements and affirmations to one another. Great efforts were made to maintain the proper operation of the community by the administrator and a group of core members. As a result, the group was shaped as a social network where peer users share social support, cultivate companionship, and exert social influence. Based on the results, we discussed future directions for research of health communities in a highly connected world.

This study employs content and network analysis techniques to explore the predictors of opinion leadership in a political activism network on Twitter. The results demonstrate the feasibility of using user-generated content to measure user characteristics. The characteristics were analyzed to predict users’ performance in the network. According to the results, Twitter users with higher connectivity and issue involvement are better at influencing information flow on Twitter. User connectivity was measured by betweenness centrality, and issue involvement was measured by a user’s geographic proximity to a given event and the contribution of engaging tweets. In addition, the results show that tweets by organizations had greater influence than those by individual users.

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