id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_fo2sjxybtvhovo3ljrsijpt4pi	Emilio Ferrara	Quantifying the effect of sentiment on information diffusion in social media	2015	15	.pdf	application/pdf	6553	737	51	information diffusion, to understand: (i) whether positive conversations spread Keywords Computational social science, Social networks, Social media, Sentiment analysis, How to cite this article Ferrara and Yang (2015), Quantifying the effect of sentiment on information diffusion in social media. which sentiment drives information diffusion in online social media. Sentiment analysis was proven an effective tool to analyze social media streams, especially Figure 2 shows the effect of content sentiment on the information diffusion, as function of tweets polarity scores: Fig. 2A shows the average number of Figure 5 Evolution of positive and negative sentiment for different types of Twitter conversations. social media content plays with respect to the diffusion of such information. highlighted once again how central social media are in the timely diffusion of information, Quantifying the effect of sentiment on information diffusion in social media Quantifying the effect of sentiment on information diffusion in social media	./cache/work_fo2sjxybtvhovo3ljrsijpt4pi.pdf	./txt/work_fo2sjxybtvhovo3ljrsijpt4pi.txt