Abstract
We study how emojis are used to express solidarity on social media in the context of three major crisis events - a natural disaster, Hurricane Irma in 2017; terrorist attacks that occurred in November 2015 in Paris; and the Charlottesville protests in August 2017. Using annotated corpora, we first train a recurrent neural network model to classify expressions of solidarity in text. Next, we use these expressions of solidarity to characterize human behavior in online social networks, through the temporal diffusion of emojis, and their sentiment scores. Our analysis reveals that emojis are a powerful indicator of sociolinguistic behaviors (solidarity) that are exhibited on social media as the crisis events unfold. The findings from this article could help advance research on the pragmatic dimensions of emojis, which have been understudied in extant literature.
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Santhanam, S., Srinivasan, V., Mahajan, K., Shaikh, S. (2021). Towards Understanding How Emojis Express Solidarity in Crisis Events. In: Ahram, T.Z., Karwowski, W., Kalra, J. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2021. Lecture Notes in Networks and Systems, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-030-80624-8_17
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