%0期刊文章%@ 1438- 8871% I JMIR出版物%V 24卡塔尔世界杯8强波胆分析% N 8% P e38776% T在COVID-19封锁期间在线攻击增加:深度文本挖掘与差中差分析的两阶段研究%徐阿，蔡阿，李宗汉%+中央研究院人文社会科学研究中心地理信息科学中心，台北市南康学术路二段128号，11529,886 2 27898150，rthtsai@gate.sinica.edu.tw %K自然语言处理%K锁定%K在线攻击%K信息监视%K因果关系%K社交媒体%K神经网络%K计算机%K大流行%K COVID-19 %K情绪%K互联网%K情感分析%K推特%K内容分析%K信息病学%D 2022 %7 9.8.2022 %9原始论文%J J医学互联网Res %G英语%X背景:COVID-19大流行在全球范围内引发了严重的公共卫生危机，政策制定者正在利用封锁来控制病毒。然而，威胁社会稳定的攻击性社会行为明显增加。封锁措施可能会对心理健康产生负面影响，导致攻击性情绪增加。发现封锁和攻击性增加之间的关系对于制定适当的政策以解决这些不利的社会影响至关重要。我们将自然语言处理(NLP)技术应用于互联网数据，以调查封锁对社会和情感的影响。目的:本研究旨在了解封锁与攻击性增加之间的关系，利用NLP技术分析了美国推文时空范围内的3种攻击性情绪:愤怒、攻击性语言和仇恨言论。方法:我们对11455名推特用户进行了纵向互联网研究，分析了他们在2019年至2020年发布的1281362条推文中的攻击性情绪。 We selected 3 common aggressive emotions (anger, offensive language, and hate speech) on the internet as the subject of analysis. To detect the emotions in the tweets, we trained a Bidirectional Encoder Representations from Transformers (BERT) model to analyze the percentage of aggressive tweets in every state and every week. Then, we used the difference-in-differences estimation to measure the impact of lockdown status on increasing aggressive tweets. Since most other independent factors that might affect the results, such as seasonal and regional factors, have been ruled out by time and state fixed effects, a significant result in this difference-in-differences analysis can not only indicate a concrete positive correlation but also point to a causal relationship. Results: In the first 6 months of lockdown in 2020, aggression levels in all users increased compared to the same period in 2019. Notably, users under lockdown demonstrated greater levels of aggression than those not under lockdown. Our difference-in-differences estimation discovered a statistically significant positive correlation between lockdown and increased aggression (anger: P=.002, offensive language: P<.001, hate speech: P=.005). It can be inferred from such results that there exist causal relations. Conclusions: Understanding the relationship between lockdown and aggression can help policymakers address the personal and societal impacts of lockdown. Applying NLP technology and using big data on social media can provide crucial and timely information for this effort. %M 35943771 %R 10.2196/38776 %U //www.mybigtv.com/2022/8/e38776 %U https://doi.org/10.2196/38776 %U http://www.ncbi.nlm.nih.gov/pubmed/35943771