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Modeling Evolutionary Dynamics of Lurking in Social Networks

机译:在社交网络中潜伏的进化动力学建模

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Lurking is a complex user-behavioral phenomenon that occurs in all large-scale online communities and social networks. It generally refers to the behavior characterizing users that benefit from the information produced by others in the community without actively contributing back to the production of social content. The amount and evolution of lurkers may strongly affect an online social environment, therefore understanding the lurking dynamics and identifying strategies to curb this trend are relevant problems. In this regard, we introduce the Lurking Game, i.e., a model for analyzing the transitions from a lurking to a non-lurking (i.e., active) user role, and vice versa, in terms of evolutionary game theory. We evaluate the proposed Lurking Game by arranging agents on complex networks and analyzing the system evolution, seeking relations between the network topology and the final equilibrium of the game. Results suggest that the Lurking Game is suitable to model the lurking dynamics, showing how the adoption of rewarding mechanisms combined with the modeling of hypothetical heterogeneity of users' interests may lead users in an online community towards a cooperative behavior.
机译:潜伏是一种复杂的用户行为现象,它发生在所有大规模的在线社区和社交网络中。它通常是指表征用户的行为,这些用户从社区中其他人产生的信息中受益,而没有积极贡献于社交内容的产生。潜伏者的数量和演变可能会严重影响在线社交环境,因此了解潜伏者动态并确定遏制这种趋势的策略是相关的问题。在这方面,我们介绍了潜伏游戏,即一种用于分析从潜伏用户角色到非潜伏(即活动用户)角色的模型,反之亦然。我们通过在复杂的网络上安排代理并分析系统演化,寻找网络拓扑结构与游戏的最终平衡之间的关系,来评估拟议的潜伏游戏。结果表明,潜伏游戏适合于对潜伏动力学进行建模,表明采用奖励机制并结合用户兴趣的假设异质性建模如何引导在线社区中的用户走向合作行为。

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