The proliferation and rapid diffusion of fake news on the Internet highlight the need of automatic hoax detection systems. In the context of social networks, machine learning (ML) methods can be used for this purpose. Fake news detection strategies are traditionally either based on content analysis (i.e. analyzing the content of the news) or - more recently - on social context models, such as mapping the news' diffusion pattern. In this paper, we first propose a novel ML fake news detection method which, by combining news content and social context features, outperforms existing methods in the literature, increasing their already high accuracy by up to 4.8%. Second, we implement our method within a Facebook Messenger chatbot and validate it with a real-world application, obtaining a fake news detection accuracy of 81.7%.

Della Vedova, M. L., Tacchini, E., Moret, S., Ballarin, G., Di Pierro, M., De Alfaro, L., Automatic Online Fake News Detection Combining Content and Social Signals, Paper, in 2018 22nd Conference of Open Innovations Association (FRUCT), (Jyvaskyla, Finland, 15-18 May 2018), IEEE, New York 2018: 272-279. 10.23919/FRUCT.2018.8468301 [http://hdl.handle.net/10807/126527]

Automatic Online Fake News Detection Combining Content and Social Signals

Della Vedova, Marco Luigi
;
Tacchini, Eugenio;
2018

Abstract

The proliferation and rapid diffusion of fake news on the Internet highlight the need of automatic hoax detection systems. In the context of social networks, machine learning (ML) methods can be used for this purpose. Fake news detection strategies are traditionally either based on content analysis (i.e. analyzing the content of the news) or - more recently - on social context models, such as mapping the news' diffusion pattern. In this paper, we first propose a novel ML fake news detection method which, by combining news content and social context features, outperforms existing methods in the literature, increasing their already high accuracy by up to 4.8%. Second, we implement our method within a Facebook Messenger chatbot and validate it with a real-world application, obtaining a fake news detection accuracy of 81.7%.
2018
Inglese
2018 22nd Conference of Open Innovations Association (FRUCT)
2018 22nd Conference of Open Innovations Association (FRUCT)
Jyvaskyla, Finland
Paper
15-mag-2018
18-mag-2018
978-952-68653-4-8
IEEE
Della Vedova, M. L., Tacchini, E., Moret, S., Ballarin, G., Di Pierro, M., De Alfaro, L., Automatic Online Fake News Detection Combining Content and Social Signals, Paper, in 2018 22nd Conference of Open Innovations Association (FRUCT), (Jyvaskyla, Finland, 15-18 May 2018), IEEE, New York 2018: 272-279. 10.23919/FRUCT.2018.8468301 [http://hdl.handle.net/10807/126527]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/126527
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