Time Reveals All Wounds: Modeling Temporal Characteristics of Cyberbullying
Time Reveals All Wounds: Modeling Temporal Characteristics of Cyberbullying
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时间揭示所有伤口：模拟网络欺凌的时间特征
DOI：
10.1609/icwsm.v12i1.15046
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Vivek K. Singh
中科院分区：
文献类型：
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作者：
Devin Soni;Vivek K. Singh
网络欺凌是一个严重限制不同个人使用在线互动空间的严重社会技术问题。新出现的文献将网络欺凌定义为一种持续的暂时现象，而不是一次性事件。然而，到目前为止，还没有做什么计算工作来模拟在线会话中网络欺凌的时间动态。在这项工作中，我们将评论行为的时间动力学建模为点过程，并在Instagram媒体会话的人群标签网络欺凌数据集上进行验证。我们定义了几个时间特征来模拟网络欺凌和常规媒体会话之间的区别特征。我们发现，我们的方法能够成功地识别网络欺凌和常规媒体会话之间的显著差异，并在网络欺凌检测方面提供性能提升。这为在使用时间建模来检测和减少网络欺凌的发生方面开展更细微的工作铺平了道路。
Cyberbullying is a critical socio-technical problem that seriously limits the use of online interaction spaces by different individuals. Emerging literature identifies cyberbullying as a continuous temporal phenomena rather than one-off incidents. However, as of yet, little computational work has been done to model the temporal dynamics of cyberbullying in online sessions. In this work, we model the temporal dynamics of commenting behavior as point processes and validate it over a crowd-labeled cyberbullying data-set of Instagram media sessions. We define several temporal features to model the distinguishing characteristics between cyberbullying and regular media sessions. We find that our approach is successfully able to identify significant differences between cyberbullying and regular media sessions, and provide a performance increase in cyberbullying detection. This paves the way for more nuanced work on the use of temporal modeling to detect and mitigate the occurrence of cyberbullying.