id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-126250-r65q535f	Zavarrone, Emma	CO.ME.T.A. -- covid-19 media textual analysis. A dashboard for media monitoring	2020-04-16		.txt	text/plain	1784	97	46	The dashboard merges together four methods: text mining, sentiment analysis, textual network analysis and latent topic models. The dashboard mixes four methods: text mining, sentiment analysis, textual network analysis and latent topic models. Figure 2 shows the dashboard's flowchart: (1) Content extraction and corpus pre-processing; (2) Sentiment analysis and descriptive study of texts: most frequent words and co-occurrence network analysis; (3) Application of a model to extract and identify the latent topics within the contents collected; (4) Plot network to represent each topic and semantic relationships between the extracted topics and terms. In the topic network it is possible to identify how the term "outbreak" links different topics related to semantic dimensions of economic, health and mediatic spheres. An implementation on the dashboard of a sentiment analysis on Twitter text from the community could give a description of the public feedback to news, giving indications to media to provide a better communication in crisis situations.	./cache/cord-126250-r65q535f.txt	./txt/cord-126250-r65q535f.txt