Social Information Processing in News Aggregation
IEEE Internet Computing
Deconstructing interaction dynamics in knowledge sharing communities
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
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In this paper we study what effects sentiment have on the temporal dynamics of user interaction and content generation in a knowledge sharing setting. We try to identify how sentiment influences interaction dynamics in terms of answer arrival, user ratings arrival, community agreement and content popularity. Our study suggests that "Negativity Bias" triggers more community attention and consequently more content contribution. Our findings provide insight into how users interact in online knowledge sharing communities, and helpful for improving existing systems.