使用基于AI的社交媒体监控追踪反Vax社交运动

Fahim K. Sufi;Imran Razzak;Ibrahim Khalil
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引用次数: 13

摘要

反Vax社会运动对政府大规模接种疫苗的目标构成了可怕的威胁。此外,通过传播关于新冠肺炎的严重误解和错误信息,抗病毒剂直接和间接地对社会的整体健康和福祉造成损害。此外,反瓦克斯派和亲瓦克斯派之间持续的冲突在最近一段时间造成了巨大的社会冲突。本文提出了一种基于人工智能的解决方案,以道德的方式识别和监控社会群体,如反Vax和亲Vax。所提出的解决方案使用基于人工智能的情绪分析和命名实体识别(NER)为政治学家、社会科学家和政策制定者提供建议,以评估社会群体的影响力和影响。从2021年6月15日至2021年12月31日,拟议的解决方案通过iOS、Android和Windows应用程序部署在一系列平台上,集成了55种不同语言的公开的40 857条与新冠肺炎相关的推特数据。我们的系统表明,在监测期内,与全球新冠肺炎相关帖子的平均负面情绪相比,反Vax和反Vax社会运动发布的负面内容增加了72%和65%。此外,带有“Hoax”关键词的反Vax相关帖子的社会影响最高,转发次数为38849次,负面程度最高(即情绪得分为0.87),最重要的是,社会冲突检测系统揭示了冲突的可能位置。
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Tracking Anti-Vax Social Movement Using AI-Based Social Media Monitoring
Anti-Vax social movement possesses a dire threat to governments’ aim of mass vaccination. Moreover, by propagating serious misconceptions and misinformation about COVID-19, Anti-Vaxxers directly and indirectly cause harm to the overall health and wellbeing of the society. In addition, the ongoing clashes between Anti-Vaxxers and Pro-Vaxxers have created great social conflicts in recent times. This article proposes an artificial intelligence (AI)-based solution to identify and monitor social groups, such as Anti-Vax and Pro-Vax, in ethical manner. The proposed solution uses AI-based sentiment analysis and named entity recognition (NER) to advice political scientist, social scientists, and policy makers to assess the influence and impact of social groups. The proposed solution was deployed via iOS, Android, and Windows App on a range of platforms integrating publicly available 40 857 Twitter data related to COVID-19 in 55 different languages from 15 June 2021 till 31 December 2021. Our system demonstrated that Anti-Vax and Pro-Vax social movements posted 72% and 65% more negative contents compared to average negative sentiments of global COVID-19 related posts during the monitored period. Moreover, Anti-Vax-related posts with “Hoax” keyword were found to have the highest level of social impact with 38 849 retweets and highest level of negativity (i.e., sentiment score of 0.87). We found out that Pro-Vax community engages in social conflict with Anti-Vaxxers referring them as ignorant (i.e., average sentiment score 0.91), stupid (i.e., average sentiment score 0.89), and confused (i.e., average sentiment score 0.88). Most importantly, the social conflict detection system reveals possible locations of conflict.
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2024 Index IEEE Transactions on Technology and Society Vol. 5 Front Cover Table of Contents IEEE Transactions on Technology and Society Publication Information In This Special: Co-Designing Consumer Technology With Society
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