id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cord-227156-uy4dykhg	Albanese, Federico	Predicting Shifting Individuals Using Text Mining and Graph Machine Learning on Twitter	2020-08-24		.txt	text/plain	4943	213	45	This is also consistent with the fact that the model trained with network features gets a better AU C than the model trained with the texts of user tweets in all datasets. Some other works are focused in political analysis and the interaction between users, as for instance the one of Aruguete et al., which described how Twitter users frame political events by sharing content exclusively with likeminded users forming two well-defined communities [12] .	cache/cord-227156-uy4dykhg.txt	txt/cord-227156-uy4dykhg.txt
