Abstract

During unexpected social events, information extracted from social media content posted by the people could play a crucial role in understanding the public opinion about the event. In this study, a mixed method procedure, which combines automated and human-based methods, is proposed to mine information from tweets to understand people's thoughts toward an unexpected turn of events. The proposed framework was applied on tweets posted regarding the police shooting to disperse protesters during the anti-Sterlite protests on May 22, 2018, at Thoothukudi in the Indian state of Tamil Nadu. The tweets were analyzed in two ways: (i) sentiment classification with automated computational methods and (ii) qualitatively examining the context of the expressed sentiments. In the case of anti-Sterlite protests, people expressed mixed emotions toward the protests for the closure of the Sterlite plant. A large negative sentiment toward the police shooting could be gleaned from the tweets. Analyzing tweets by the proposed method provides clear insights regarding the incident, which in turn will aid in planning an emergency response.

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