What Makes Conversations Interesting? Themes, Participants and Consequences of Conversations in Online Social Media

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Abstract

Rich media social networks promote not only creation and consumption of media, but also communication about the posted media item. What causes a conversation to be interesting, that prompts a user to participate in the discussion on a posted video? We conjecture that people participate in conversations when they find the conversation theme interesting, see comments by people whom they are familiar with, or observe an engaging dialogue between two or more people (absorbing back and forth exchange of comments). Importantly, a conversation that is interesting must be consequential – i.e. it must impact the social network itself. Our framework has three parts. First, we detect conversational themes using a mixture model approach. Second, we determine interestingness of participants and interestingness of conversations based on a random walk model. Third, we measure the consequence of a conversation by measuring how interestingness affects the following three variables – participation in related themes, participant cohesiveness and theme diffusion. We have conducted extensive experiments using a dataset from the popular video sharing site, YouTube. Our results show that our method of interestingness maximizes the mutual information, and is significantly better (twice as large) than three other baseline methods (number of comments, number of new participants and PageRank based assessment). create (e.g. upload photo on Flickr), and consume media (e.g. watch a video on YouTube). These websites also allow for significant communication between the users – such as comments by one user on a media uploaded by another. These comments reveal a rich dialogue structure (user A comments on the upload, user B comments on the upload, A comments in response to B’s comment, B responds to A’s comment etc.) between users, where the discussion is often about themes unrelated to the original video. Example of a conversation from YouTube [1] is shown in Figure 1. In this paper, the sequence of comments on a media object is referred to as a conversation. Note the theme of the conversation is latent and depends on the content of the conversation. The fundamental idea explored in this paper is that analysis of communication activity is crucial to understanding repeated visits to a rich media social networking site. People return to a video post that they have already seen and post further comments (say in YouTube) in response to the communication activity, rather than to watch the video again. Thus it is the content of the communication activity itself that the people want to read (or see, if the response to a video post is another video, as is possible in the case of YouTube). Furthermore, these rich media sites have notification mechanisms that alert users of new comments on a video post / image upload promoting this communication activity.