Tracking Peaceful Tractors on Social Media -- XAI-enabled analysis of Red Fort Riots 2021

TL;DR

This paper introduces a new dataset of 50,000 tweets related to the Red Fort Riots 2021 and applies an Explainable AI model to classify tweets into disinformation, misinformation, or opinion, aiding social media analysis of the event.

Contribution

It presents the tractor2twitter dataset and benchmarks an XAI-enabled classification model for analyzing social media content related to the riots.

Findings

The dataset contains 50,000 tweets from different time periods.

The XAI model effectively classifies tweets into three categories.

Insights into misinformation spread during the event.

Abstract

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.