%0期刊文章%@ 1438-8871 %I JMIR出版物%V 22%卡塔尔世界杯8强波胆分析 N 12% P e22609 %T在阿拉伯地区与covid -19相关的推文中检测仇恨言论:深度学习和主题建模方法%A Alshalan,Raghad %A Al-Khalifa,Hend %A Alsaeed,Duaa %A Al-Baity,Heyam %A Alshalan,Shahad %+沙特国王大学，利雅得11451，沙特阿拉伯利雅得，966 504426816，hend.alkhalifa@gmail.com %K COVID-19 %K冠状病毒%K推特%K仇恨言论%K社交网络分析%K社交媒体%K公共卫生%K大流行%K深度学习%K非负矩阵分解%K NMF %K卷积神经网络%K CNN %D 2020 %7 8.12.2020 %9原创论文%J J Med互联网Res %G英语%X背景:社交媒体平台的大规模需要一个自动检测仇恨言论的解决方案。这些自动解决方案将有助于减少手动分析内容的需要。大多数先前的文献都将仇恨言论检测问题描述为使用经典机器学习方法或最近使用深度学习方法的监督文本分类任务。然而，与已发表的关于英语文本的工作相比，在阿拉伯网络空间调查这一问题的工作仍然有限。目的:本研究旨在识别阿拉伯地区推特用户发布的与COVID-19大流行相关的仇恨言论，并发现包含仇恨言论的推文中讨论的主要问题。方法:我们使用了自2020年1月27日开始的ArCOV-19数据集，这是一个持续收集的与COVID-19有关的阿拉伯语推文。使用预训练的卷积神经网络(CNN)模型分析推文中的仇恨言论;每条推文都有0到1分，1分是最可恶的推文。 We also used nonnegative matrix factorization to discover the main issues and topics discussed in hate tweets. Results: The analysis of hate speech in Twitter data in the Arab region identified that the number of non–hate tweets greatly exceeded the number of hate tweets, where the percentage of hate tweets among COVID-19 related tweets was 3.2% (11,743/547,554). The analysis also revealed that the majority of hate tweets (8385/11,743, 71.4%) contained a low level of hate based on the score provided by the CNN. This study identified Saudi Arabia as the Arab country from which the most COVID-19 hate tweets originated during the pandemic. Furthermore, we showed that the largest number of hate tweets appeared during the time period of March 1-30, 2020, representing 51.9% of all hate tweets (6095/11,743). Contrary to what was anticipated, in the Arab region, it was found that the spread of COVID-19–related hate speech on Twitter was weakly related with the dissemination of the pandemic based on the Pearson correlation coefficient (r=0.1982, P=.50). The study also identified the commonly discussed topics in hate tweets during the pandemic. Analysis of the 7 extracted topics showed that 6 of the 7 identified topics were related to hate speech against China and Iran. Arab users also discussed topics related to political conflicts in the Arab region during the COVID-19 pandemic. Conclusions: The COVID-19 pandemic poses serious public health challenges to nations worldwide. During the COVID-19 pandemic, frequent use of social media can contribute to the spread of hate speech. Hate speech on the web can have a negative impact on society, and hate speech may have a direct correlation with real hate crimes, which increases the threat associated with being targeted by hate speech and abusive language. This study is the first to analyze hate speech in the context of Arabic COVID-19–related tweets in the Arab region. %M 33207310 %R 10.2196/22609 %U //www.mybigtv.com/2020/12/e22609/ %U https://doi.org/10.2196/22609 %U http://www.ncbi.nlm.nih.gov/pubmed/33207310