Individual popularity and activity in online social systems
arXiv:0911.2176 · doi:10.1016/j.physa.2009.11.007
Abstract
We propose a stochastic model of web user behaviors in online social systems, and study the influence of attraction kernel on statistical property of user or item occurrence. Combining the different growth patterns of new entities and attraction patterns of old ones, different heavy-tailed distributions for popularity and activity which have been observed in real life, can be obtained. From a broader perspective, we explore the underlying principle governing the statistical feature of individual popularity and activity in online social systems and point out the potential simple mechanism underlying the complex dynamics of the systems.
7 pages, 7 figures, 1 table, accepted for publication in Physica A
References in corpus (12)
- Robust dynamic classes revealed by measuring the response function of a social system
- Novelty and Collective Attention
- Collaborative Tagging and Semiotic Dynamics
- Structure and Time-Evolution of an Internet Dating Community
- Role of Activity in Human Dynamics
- Evolution of a large online social network
- Vocabulary growth in collaborative tagging systems
- Attractiveness and activity in Internet communities
- Folksonomies and clustering in the collaborative system CiteULike
- Empirical analysis on a keyword-based semantic system
- Predicting the popularity of online content
- Characterizing Video Responses in Social Networks