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事件类型会影响推特上用户互动的演变方式吗?

Does the type of event influence how user interactions evolve on Twitter?

作者信息

del Val Elena, Rebollo Miguel, Botti Vicente

机构信息

Dept. de Sistemas Informáticos y Computación, Universitat Politècnica de València, Valencia, Spain.

出版信息

PLoS One. 2015 May 11;10(5):e0124049. doi: 10.1371/journal.pone.0124049. eCollection 2015.

Abstract

The number of people using on-line social networks as a new way of communication is continually increasing. The messages that a user writes in these networks and his/her interactions with other users leave a digital trace that is recorded. Thanks to this fact and the use of network theory, the analysis of messages, user interactions, and the complex structures that emerge is greatly facilitated. In addition, information generated in on-line social networks is labeled temporarily, which makes it possible to go a step further analyzing the dynamics of the interaction patterns. In this article, we present an analysis of the evolution of user interactions that take place in television, socio-political, conference, and keynote events on Twitter. Interactions have been modeled as networks that are annotated with the time markers. We study changes in the structural properties at both the network level and the node level. As a result of this analysis, we have detected patterns of network evolution and common structural features as well as differences among the events.

摘要

将在线社交网络作为一种新的交流方式的人数在持续增加。用户在这些网络中撰写的信息以及他/她与其他用户的互动会留下被记录的数字痕迹。基于这一事实以及网络理论的应用,对信息、用户互动以及由此产生的复杂结构的分析得到了极大的便利。此外,在线社交网络中生成的信息会被临时标记,这使得进一步分析互动模式的动态变化成为可能。在本文中,我们对推特上电视、社会政治、会议和主题演讲活动中发生的用户互动演变进行了分析。互动已被建模为带有时间标记注释的网络。我们研究了网络层面和节点层面结构属性的变化。通过这一分析,我们检测到了网络演变模式、共同的结构特征以及不同活动之间的差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbc2/4427504/04fc11db2967/pone.0124049.g001.jpg

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