TY - GEN
T1 - What makes conversations interesting? Themes, participants and consequences of conversations in online social media
AU - Choudhury, Munmun De
AU - Sundaram, Hari
AU - John, Ajita
AU - Seligmann, Dorée Duncan
PY - 2009
Y1 - 2009
N2 - 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). Copyright is held by the International World Wide Web Conference Committee (IW3C2).
AB - 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). Copyright is held by the International World Wide Web Conference Committee (IW3C2).
KW - Conversations
KW - Interestingness
KW - Social media
KW - Themes
KW - YouTube
UR - http://www.scopus.com/inward/record.url?scp=84865634995&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84865634995&partnerID=8YFLogxK
U2 - 10.1145/1526709.1526754
DO - 10.1145/1526709.1526754
M3 - Conference contribution
AN - SCOPUS:84865634995
SN - 9781605584874
T3 - WWW'09 - Proceedings of the 18th International World Wide Web Conference
SP - 331
EP - 340
BT - WWW'09 - Proceedings of the 18th International World Wide Web Conference
T2 - 18th International World Wide Web Conference, WWW 2009
Y2 - 20 April 2009 through 24 April 2009
ER -