id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-156676-wes5my9e	Masud, Sarah	Hate is the New Infodemic: A Topic-aware Modeling of Hate Speech Diffusion on Twitter	2020-10-09		.txt	text/plain	8724	520	59	For predicting the initiation of hate speech for any given hashtag, we propose multiple feature-rich models, with the best performing one achieving a macro F1 score of 0.65. For both detecting and predicting the spread of hate speech over short tweets, the knowledge of context is likely to play a decisive role Present work: Based on the findings of the existing literature and the analysis we presented above, here we attempt to model the dynamics of hate speech spread on Twitter. 1) We formalize the dynamics of hate generation and retweet spread on Twitter subsuming, the activity history of each user and signals propagated by the localized structural properties of the information network of Twit-ter induced by follower connections as well as global endogenous and exogenous signals (events happening inside and outside of Twitter) (See Section III). Features representing hateful behavior encoded within the given tweet as well as the activity history of the users further help RETINA to achieve a macro F1-score of 0.85, significantly outperforming several state-of-the-art retweet prediction models.	./cache/cord-156676-wes5my9e.txt	./txt/cord-156676-wes5my9e.txt