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Incremental communication patterns in online social groups
Knowledge and Information Systems ( IF 2.7 ) Pub Date : 2021-03-26 , DOI: 10.1007/s10115-021-01552-w
Andrea Michienzi , Barbara Guidi , Laura Ricci , Andrea De Salve

In the last decades, temporal networks played a key role in modelling, understanding, and analysing the properties of dynamic systems where individuals and events vary in time. Of paramount importance is the representation and the analysis of Social Media, in particular Social Networks and Online Communities, through temporal networks, due to their intrinsic dynamism (social ties, online/offline status, users’ interactions, etc..). The identification of recurrent patterns in Online Communities, and in detail in Online Social Groups, is an important challenge which can reveal information concerning the structure of the social network, but also patterns of interactions, trending topics, and so on. Different works have already investigated the pattern detection in several scenarios by focusing mainly on identifying the occurrences of fixed and well known motifs (mostly, triads) or more flexible subgraphs. In this paper, we present the concept on the Incremental Communication Patterns, which is something in-between motifs, from which they inherit the meaningfulness of the identified structure, and subgraph, from which they inherit the possibility to be extended as needed. We formally define the Incremental Communication Patterns and exploit them to investigate the interaction patterns occurring in a real dataset consisting of 17 Online Social Groups taken from the list of Facebook groups. The results regarding our experimental analysis uncover interesting aspects of interactions patterns occurring in social groups and reveal that Incremental Communication Patterns are able to capture roles of the users within the groups.



中文翻译:

在线社交群体中的增量式沟通方式

在过去的几十年中,时间网络在建模,理解和分析动态系统的特性方面发挥了关键作用,在动态系统中,个人和事件随时间变化。最重要的是,由于时态网络的内在动力(社会纽带,在线/离线状态,用户互动等),通过时态网络对社交媒体,特别是社交网络和在线社区进行表示和分析。识别在线社区中经常出现的模式,以及在线社交团体中的详细信息,是一项重要的挑战,它可以揭示有关社交网络结构的信息,还可以揭示交互的模式,趋势主题等。不同的工作已经通过集中于确定固定和众所周知的图案(主要是三合会)或更灵活的子图的出现,在几种情况下研究了模式检测。在本文中,我们介绍了增量沟通模式的概念,它是介于主题之间的某种东西,它们从中继承了所识别结构的意义,在子图中,他们继承了根据需要扩展的可能性。我们正式定义了增量式沟通模式,并利用它们来研究在真实数据集中出现的交互模式,该数据集由来自Facebook群组列表的17个在线社交群组组成。

更新日期:2021-03-26
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