What makes conversations interesting?: themes, participants and consequences of conversations in online social media

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: characterizing themes, characterizing participants for determining interestingness and measures of consequences of a conversation deemed to be interesting. 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 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).

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning

  J. Computer Applications
  J.4 SOCIAL AND BEHAVIORAL SCIENCES
      Subjects: Sociology

General Terms:
Algorithms, Experimentation, Human Factors, Verification

Keywords:
conversations, interestingness, social media, themes, youtube