Abstract
Social media has become a tool to spread false information with the help of its large complex network. The consequences of such misinformation could be very severe. The paper uses the Twitter conversations about the scrapping of Article 370 in India to differentiate the spreaders of fake news from the general spreaders. Various features were used for comparison such as bot usage, patterns and emotions in tweets posted by bots, heterogeneity among the spreaders, and geographic as well as demographic characteristics. The bots were found to be relatively more indulged in spreading fake tweets by conversing more through replies. The tweets related to bots engaged in spreading fake news are more emotionally loaded especially with anger, disgust and trust than tweets posted by any other bots. The people living outside India played a major role in the dissemination of fake news on Article 370. The social connections as well as demographic features do not distinguish the fake news spreaders on the platform, although the fewer number of older people were found among the fake news spreaders. This may help in automating the detection of fake news spreaders.
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Singh, M., Kaur, R., Iyengar, S.R.S. (2020). Multidimensional Analysis of Fake News Spreaders on Twitter. In: Chellappan, S., Choo, KK.R., Phan, N. (eds) Computational Data and Social Networks. CSoNet 2020. Lecture Notes in Computer Science(), vol 12575. Springer, Cham. https://doi.org/10.1007/978-3-030-66046-8_29
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