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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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Nonprofits use social media to pursue a broad range of mission-related outcomes. Given the centrality of user connections and social networks on these sites, attaining these outcomes is contingent on first generating a stock of online social capital through investing in online relationships. Yet little is known empirically about this process. To better understand the return on social media, this study develops empirical measures of four key dimensions of social media-based social capital centering on the nature of nonprofits' network positions and stakeholder ties. The study then tests a series of hypotheses relating the increase in social capital to different types of stakeholder engagement tactics. Using Twitter data on 198 community foundations, the study finds that content with multiple communication cues and inter-sectoral stakeholder targeting predict higher levels of social capital; communicative and stakeholder diversity thus appear to play a key role in the successful organizational use of social media.