Characterizing Political Fake News in Twitter by its metadata

Published in SUBMITTED, 2017

Recommended citation: Amador, J. & Molina-Solana, M. (2017), "Characterizing Political Fake News in Twitter by its metadata", SUBMITTED to Big Data .

Can we identify fake news by its meta-data?

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Recommended citation: Amador, J. & Molina-Solana, M. (2017), "Characterizing Political Fake News in Twitter by its metadata", Submitted to Big Data.

Abstract: This work describes our initial study towards characterizing political fake news in Tweets by its meta-data. In particular, we focus on more than 1.5M tweets collected on the day of the election of Donald Trump as 45th president of the United States of America. We use the meta-data embedded within those tweets in order to look for differences between tweets containing fake news and other types of tweets. Specifically, we perform our analysis by considering only tweets that went viral and studying proxies for users’ exposure to the tweets, by characterizing accounts spreading fake news and by analysing political polarization in the content of the tweet. We found relevant patterns on the distribution of followers, the number of URLs on tweets, and the verification of the users.

BibTeX: @article{Amador2017, author = {Julio Amador and Miguel Molina-Solana}, title = {Characterizing Political Fake News in Twitter by its metadata}, journal = {Big Data}, year = {2017}, volume = {submitted}, pages = {}, doi = {} }