论文标题
通过贝叶斯趋势分析评估Covid-19对网络欺凌的影响
Evaluating the Impact of COVID-19 on Cyberbullying through Bayesian Trend Analysis
论文作者
论文摘要
Covid-19的影响已经从个人和全球健康到我们的社会生活超越。在数字存在方面，据推测，在大流行期间，网络欺凌行为显着增加。在本文中，我们研究了近来的网络欺凌和报告的假设是否有所增加。为了评估猜测，我们收集了与网络欺凌相关的公共推文（n = 454,046），在2020年1月1日至2020年6月7日之间发布。简单的视觉频繁分析忽略了串行纠正，并且没有描述此类变更点。为了解决相关性和相对较少的时间点，提出了通过自回归泊松模型对收集的数据提出对趋势的贝叶斯估计。我们表明，本文中详细介绍的这种新的贝叶斯方法可以清楚地表明自2020年3月中旬以来与网络欺凌相关的推文的上升趋势。但是，该证据本身并不表示网络欺凌的上升，但显示了危机与个人讨论的危机相关。我们的工作强调了网络欺凌的关键问题，以及全球危机如何影响社交媒体滥用，并提供了一个趋势分析模型，可以将其用于社交媒体数据分析。
COVID-19's impact has surpassed from personal and global health to our social life. In terms of digital presence, it is speculated that during pandemic, there has been a significant rise in cyberbullying. In this paper, we have examined the hypothesis of whether cyberbullying and reporting of such incidents have increased in recent times. To evaluate the speculations, we collected cyberbullying related public tweets (N=454,046) posted between January 1st, 2020 -- June 7th, 2020. A simple visual frequentist analysis ignores serial correlation and does not depict changepoints as such. To address correlation and a relatively small number of time points, Bayesian estimation of the trends is proposed for the collected data via an autoregressive Poisson model. We show that this new Bayesian method detailed in this paper can clearly show the upward trend on cyberbullying-related tweets since mid-March 2020. However, this evidence itself does not signify a rise in cyberbullying but shows a correlation of the crisis with the discussion of such incidents by individuals. Our work emphasizes a critical issue of cyberbullying and how a global crisis impacts social media abuse and provides a trend analysis model that can be utilized for social media data analysis in general.
