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Group dynamics in discussing incidental topics over online social networks

机译:通过在线社交网络讨论偶然话题的小组动力

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The groups discussing incidental popular topics over online social networks have recently become a research focus. By analyzing some fundamental relationships in these groups, we find that the traditional models are not suitable for describing the group dynamics of incidental topics. In this article we analyze the dynamics of online groups discussing incidental popular topics and present a new model for predicting the dynamic sizes of incidental topic groups. We discover that the dynamic sizes of incidental topic groups follow a heavy-tailed distribution. Based on this finding, we develop an adaptive parametric method for predicting the dynamics of this type of group. The model presented in the article is validated using actual data from LiveJournal and Sohu blogs. The empirical results show that the model can effectively predict the dynamic characteristics of incidental topic groups over both short and long timescales, and outperforms the SIR model. We conclude by offering two strategies for promoting the group popularity of incidental topics.
机译:通过在线社交网络讨论偶然的热门话题的小组最近已成为研究重点。通过分析这些小组中的一些基本关系,我们发现传统模型不适合描述偶然主题的小组动态。在本文中,我们分析了讨论偶然性热门话题的在线群体的动态,并提出了一种预测偶然性话题群体动态规模的新模型。我们发现,偶然主题组的动态大小遵循着重尾分布。基于此发现,我们开发了一种自适应参数方法来预测此类群体的动态。本文中提供的模型已使用LiveJournal和Sohu博客中的实际数据进行了验证。实证结果表明,该模型可以有效地预测短时和长时事件的偶然主题群的动态特征,并且优于SIR模型。最后,我们提供了两种策略来促进偶然主题在团体中的流行。

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