Impact of COVID-19 on Indian politics: analyzing political leaders interactions and sentiments on Twitter

Amidst the persistent COVID-19 pandemic, there has been a profound disruption in political, economic, and social disruption in the entire world. India has emerged as one of the most affected countries by this pandemic globally. The government has taken extensive measures to combat the disease and is disseminating essential information regarding the same on social media, particularly Twitter. Restricted or polarized interactions and diverging opinions among the politicians may hinder the formulation of important policies and measures for managing this crucial situation. This paper, therefore, aims to perform an in-depth investigation on the Twitter activities of Indian political leaders in response to COVID-19. The study presents an analysis of their tweet sentiments and formation of networks during political discussions. The analysis has been done on three different topics pertaining to COVID-19: preventive measures, lockdown, and vaccination separately. Firstly, the communication ties formed between the politicians during discussions on the respective topics are investigated based on network analysis of their mentions and retweets. The communities formed in the interaction networks and the extent of polarization between the communities is then examined. Secondly, sentiment analysis of the tweets have been performed using some well-known machine learning classifiers to identify the sentiment leaning of the politicians and the communities toward the issue. This combined approach of network and sentiment based analysis provides better characterization of political communities and their leanings regarding the pandemic. The findings revealed the presence of polarized communication during retweets while high level of cross-party interactions during mentions. The politicians have been identified to have overall positive response toward preventive measures and vaccination while majority have shown negative sentiments toward lockdown.