The past two decades have witnessed many social protests which gathered mass movement and support from social media platforms. In the proposed study, we examine the role of languages and influencers in determining the genuineness of social media support in a social movement context. We take theoretical support from the social influence theory to develop our conceptual model. We have obtained tweets using hashtags such as #FarmersProtest related to the farmers’ movement in India and employed Twitter API to filter tweets from September 2020 to 2021. To measure the genuineness of social media support, we plan to develop a machine learning-based approach using LDA. Further analysis can reveal valuable insights into how social media supports social movements like the farmers’ protest. This research in progress study can significantly contribute to IS research and offer practical implications for relevant stakeholders in managing social movements.
Rao, Kunal and Dixit, Gaurav, "Genuineness of Social media Support: Role of languages and influencers in the Case of Farmers’ Protest in India" (2022). PACIS 2022 Proceedings. 248.
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