Hashtags Are (Not) Judgemental: The Untold Story of Lok Sabha Elections 2019

Hashtags in online social media have become a way for users to build communities around topics, promote opinions, and categorize messages. In the political context, hashtags on Twitter are used by users to campaign for their parties, spread news, or to get followers and get a general idea by following a discussion built around a hashtag. In the past, researchers have studied certain types and specific properties of hashtags by utilizing a lot of data collected around hashtags. In this pa-per, we perform a large-scale empirical analysis of elections using only the hashtags shared on Twitter during the 2019 Lok Sabha elections in India. We study the trends and events unfolded on the ground, the latent topics to uncover representative hashtags and semantic similarity to discover sentiments during elections. We collect over 24 million hashtags to perform extensive experiments to find the trending hashtags, and cross-reference them with the tweets in our data set to list down notable events. We also use semantic similarity based techniques to find related hashtags and latent topics among the hashtags.

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