Information dissemination in heterogeneous-intent networks.
WebSci '16: ACM Web Science Conference Hannover Germany May, 2016(2016)
摘要
Many qualitative studies of communication practices on social media have recognized that people's motivation for participating in social networks can vary greatly. Some people participate for fame and fortune, while others simply wish to chat with friends. In this paper, we study the implications of such heterogeneous intent for modeling information diffusion in social networks. We experiment with user-level perception of messages, analyze large-scale information cascades, and model information diffusion in heterogeneous-intent networks. We perform carefully designed user studies to establish the relationship between the intent and language style of a message sender. Style of the user appear to adapt their language to achieve different intents. We perform a large-scale data analysis on Twitter message cascades and confirm that message propagation through a network is correlated with historical representations of individuals' intents. Finally, we posit a simple analytical model of information diffusion in social networks that takes heterogeneous intents into account and find that this model is able to explain empirically observed properties of structural virality that are not explained by current models.
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关键词
information dissemination, user modeling, topic modeling, social media
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