追踪社交媒体上的和平拖拉机-XAI对2021年红堡骚乱的分析
Tracking Peaceful Tractors on Social Media -- XAI-enabled analysis of Red Fort Riots 2021
摘要：
2021年1月26日，印度目睹了一场全国性的尴尬，这场尴尬来自于最不受期待的人口统计-农民。全国人民惊恐地看着一群伪爱国主义的农民冲进首都德里，破坏了民族自豪感-红堡。事件发生后的调查显示，存在一个社交媒体线索，导致这样的事件。因此，将这条线索存档以进行社交媒体分析变得至关重要和必要-不仅要了解分散在线索中的面包屑，还要可视化错误信息和假新闻在这一事件中所扮演的角色。在本文中，我们提出了tractor 2 twitter数据集，其中包含在此事件之前，期间和之后发布的大约0.05万条推文。此外，我们使用可解释的AI ML模型对我们的数据集进行基准测试，将每条推文分类为三个类别之一-虚假信息，错误信息和意见。
英文摘要：
On 26 January 2021, India witnessed a national embarrassment from the demographic least expected from - farmers. People across the nation watched in horror as a pseudo-patriotic mob of farmers stormed capital Delhi and vandalized the national pride- Red Fort. Investigations that followed the event revealed the existence of a social media trail that led to the likes of such an event. Consequently, it became essential and necessary to archive this trail for social media analysis - not only to understand the bread-crumbs that are dispersed across the trail but also to visualize the role played by misinformation and fake news in this event. In this paper, we propose the tractor2twitter dataset which contains around 0.05 million tweets that were posted before, during, and after this event. Also, we benchmark our dataset with an Explainable AI ML model for classification of each tweet into either of the three categories - disinformation, misinformation, and opinion.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
