From user comments to on-line conversations

Authors:
Chunyan Wang;Mao Ye;Bernardo A. Huberman
Affiliations:
Stanford University, Stanford, CA, USA;HP Labs, Palo Alto, CA, USA;HP Labs, Palo Alto, CA, USA
Venue:
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2012

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Abstract

We present an analysis of user conversations in on-line social media and their evolution over time. We propose a dynamic model that predicts the growth dynamics and structural properties of conversation threads. The model reconciles the differing observations that have been reported in existing studies. By separating artificial factors from user behavior, we show that there are actually underlying rules in common for on-line conversations in different social media websites. Results of our model are supported by empirical measurements throughout a number of different social media websites.