Tracking Peaceful Tractors on Social Media -- XAI-enabled analysis of Red Fort Riots 2021
This work addresses the need for archiving and analyzing social media trails to understand misinformation in specific events like the Red Fort Riots, but it is incremental as it applies existing methods to new data.
The paper tackles the problem of analyzing social media data related to the 2021 Red Fort Riots by creating the tractor2twitter dataset of about 0.05 million tweets and benchmarking it with an Explainable AI model to classify tweets into disinformation, misinformation, or opinion categories.
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.