不断增长的 Reddit 线程网络的结构与动态

Diletta Goglia, Davide Vega
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引用次数: 0

摘要

数百万人使用在线社交网络来加强其归属感,例如,通过提供和征求反馈意见作为一种社会认可和自我认可的形式。在表达这种反馈意见时,人们经常会看到信仰和观点上的分歧。对这种互动进行建模和分析,对于理解人们在表达和讨论自己的价值观时面对不同意见所产生的社会现象至关重要。在这项工作中,我们研究了一个 Reddit 社区,在这个社区中,人们参与对某些行为进行评判或被评判,因为它是研究用户如何在网上表达评判的一个有价值的来源。我们将该社区的线程建模为随时间增长的复杂用户互动网络,并分析了其结构特性的演变。这是因为它们的全局聚类系数极小,平均最短路径长度随时间增长。这些特性揭示了用户是如何在线程中进行讨论的,即主要是与另一个用户进行讨论,而且往往是通过单条消息进行讨论。通过分析分歧和互惠在此类会话中的作用,我们进一步证实了这一结果。我们还表明,Reddit 线程的演化是由两个以不同速度增长的子图所控制的。我们发现,在所研究的社区中,这种速度的差异要高于其他社区,这是因为用户指南强制规定了特定的用户交互。最后,我们从社会判断理论出发,对所获得的用户行为结果进行了解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structure and dynamics of growing networks of Reddit threads
Millions of people use online social networks to reinforce their sense of belonging, for example by giving and asking for feedback as a form of social validation and self-recognition. It is common to observe disagreement among people beliefs and points of view when expressing this feedback. Modeling and analyzing such interactions is crucial to understand social phenomena that happen when people face different opinions while expressing and discussing their values. In this work, we study a Reddit community in which people participate to judge or be judged with respect to some behavior, as it represents a valuable source to study how users express judgments online. We model threads of this community as complex networks of user interactions growing in time, and we analyze the evolution of their structural properties. We show that the evolution of Reddit networks differ from other real social networks, despite falling in the same category. This happens because their global clustering coefficient is extremely small and the average shortest path length increases over time. Such properties reveal how users discuss in threads, i.e. with mostly one other user and often by a single message. We strengthen such result by analyzing the role that disagreement and reciprocity play in such conversations. We also show that Reddit thread's evolution over time is governed by two subgraphs growing at different speeds. We discover that, in the studied community, the difference of such speed is higher than in other communities because of the user guidelines enforcing specific user interactions. Finally, we interpret the obtained results on user behavior drawing back to Social Judgment Theory.
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