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.

A growing number of hyper-partisan alternative media outlets have sprung up online to challenge mainstream journalism. However, research on news sharing in this particular media environment is lacking. Based on the virality of sixteen partisan outlets’ coverage of immigration and using the latest computational linguistic algorithm, the present study probes how hyper-partisan news sharing is related to source transparency, content styles, and moral framing. The study finds that the most shared articles reveal author names, but not necessarily other types of author information. The study uncovers a salient link between moral frames and virality. In particular, audiences are more sensitive to moral frames that emphasize authority/respect, fairness/reciprocity, and harm/care.

Online news users interact with news on digital platforms in different ways. Some take advantage of the technical affordances that allow sharing, liking and commenting, while others do not. Based on a national survey of the Australian adult online news users, this study explores online news users’ different modes of interaction on digital platforms: non-interaction, signalling interaction, and expressive interaction. This study demonstrates that different types of online news users are largely determined by a combination of structural influences and individual factors related to the uptake, reception, and dissemination of news. This study contributes to the growing body of literature on news engagement by exploring the concept of interaction as a more specific term to describe online news behaviours, and identifies different types of news users connected to, rather than disembodied from, their practice. In doing so, this article advances the understanding of news consumption behaviour and its implications for engaging news audiences in the digital age.