I Stand With You: Using Emojis to Study Solidarity in Crisis Events
This work addresses the problem of analyzing social media behavior during crises for researchers and practitioners, but it is incremental as it applies existing methods to new data.
The authors tackled the problem of understanding how emojis express solidarity during crisis events like Hurricane Irma and the Paris attacks by training a recurrent neural network to classify solidarity in text and analyzing emoji diffusion, revealing that emojis are a powerful indicator of sociolinguistic behaviors as crises unfold.
We study how emojis are used to express solidarity in social media in the context of two major crisis events - a natural disaster, Hurricane Irma in 2017 and terrorist attacks that occurred on November 2015 in Paris. 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 and geospatial diffusion of emojis. Our analysis reveals that emojis are a powerful indicator of sociolinguistic behaviors (solidarity) that are exhibited on social media as the crisis events unfold.