Investigating formation of Collective Identity driving the Black Lives Matter movement during COVID-19 Emergent Research Forum (ERF)

Focusing on the recent Black Lives Matter (BLM) movement associated with the death of George Floyd during the COVID-19 pandemic, we seek to identify the shared collective identity of online and offline participants. Specifically, we collect hashtags associated with the movement and use sentiment analysis to investigate the individual emotions that underpin their involvement during the COVID-19 pandemic. The link between online activism and offline protests is modelled in our study. Users' beliefs serve as factors that direct actions (emotions) resulting in significant outcomes (protests) and are moderated by collective identity of the people participating in the protests. We use natural language processing ( NLP) to test for the presence of the identified factors in our tweet corpus of 8 weeks of data (from 05/2020 to 10/2020) from twitter that involves discussions around the #BLM.