The phenomenon of social TV is gaining importance in both industry and research. TV broadcasters are increasingly adopting social TV strategies both on first and second screen to increase the viewers' online engagement. The research done so far suggests quite simple models of the phenomenon, identifying and studying separately the effects of different variables on online engagement. This research represents one of the first attempts to develop a better research model. We analyzed a large dataset related to a popular Italian TV show using social strategies to engage viewers on Twitter. Through hierarchical linear regression models we studied the relationships among social strategies, TV contents, viewership, time and different kinds of viewers' online behavior. We demonstrate that (i) different factors play different roles in affecting the viewers' online engagement and (ii) the phenomenon can be better explained if we look at different kinds of online behavior that represent online engagement, such as posting original comments, sharing or replying to them. Despite some limitations, we think that this work's findings may be important for researchers to develop a holistic research model of social TV, and for practitioners to realize how to balance the factors affecting the viewers' online engagement in an effective way.
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