Given the fact that in a context of crises, people are concerned with their safety, among other things, partisan response toward policies and public leaders is an intriguing topic. This article examines the extent to which partisanship pertains to the time of the Covid-19 pandemic. We employ natural language processing (NLP) and social network analysis (SNA) on Twitter data to analyse public responses toward prominent political leaders, namely, Indonesian President Joko Widodo (Jokowi) and Jakarta Governor Anies Baswedan (Anies), in handling the crisis of the Covid-19 pandemic in Indonesia. We then put the social media analysis in a framework of political partisanship. Our sentiment analysis through NLP across time and categories found that supports and demands towards the two public figures indicate positive and negative partisanship that replicates previous electoral supports. Similarly, our SNA indicates a high polarization rate among the accounts connected with the two leaders in response to the crisis. Extended analysis of the accounts who are at the epicentres of the sentiment conversations, either positive or negative about Jokowi and Anies, reveals that there are connections with their past political support. Though we find negative partisan responses for both leaders, a type of hard-core partisanship has been leveraged for Jokowi but not for Anies. We conclude that electoral polarization contributes to the extent to which partisanship responses circulate in a context of crisis.