Khyati Mahajan


2020

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Studying The Effect of Emotional and Moral Language on Information Contagion during the Charlottesville Event
Khyati Mahajan | Samira Shaikh
Proceedings of the The Fourth Widening Natural Language Processing Workshop

We highlight the contribution of emotional and moral language towards information contagion online. We find that retweet count on Twitter is significantly predicted by the use of negative emotions with negative moral language. We find that a tweet is less likely to be retweeted (hence less engagement and less potential for contagion) when it has emotional language expressed as anger along with a specific type of moral language, known as authority-vice. Conversely, when sadness is expressed with authority-vice, the tweet is more likely to be retweeted. Our findings indicate how emotional and moral language can interact in predicting information contagion.

2019

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Emoji Usage Across Platforms: A Case Study for the Charlottesville Event
Khyati Mahajan | Samira Shaikh
Proceedings of the 2019 Workshop on Widening NLP

We study emoji usage patterns across two social media platforms, one of them considered a fringe community called Gab, and the other Twitter. We find that Gab tends to comparatively use more emotionally charged emoji, but also seems more apathetic towards the violence during the event, while Twitter takes a more empathetic approach to the event.
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