Automatic Online Fake News Detection Combining Content and Social Signals
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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FRUCT
2018-05-01
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| Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| Subjects: | |
| Online Access: | https://fruct.org/publications/fruct22/files/Ved.pdf
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| _version_ | 1828308788194574336 |
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| author | Marco L. Della Vedova Eugenio Tacchini Stefano Moret Gabriele Ballarin Massimo DiPierro Luca de Alfaro |
| author_facet | Marco L. Della Vedova Eugenio Tacchini Stefano Moret Gabriele Ballarin Massimo DiPierro Luca de Alfaro |
| author_sort | Marco L. Della Vedova |
| collection | DOAJ |
| description | 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%. |
| first_indexed | 2024-04-13T15:18:37Z |
| format | Article |
| id | doaj.art-2305c5e42c26463da7afa2cb8cbab015 |
| institution | Directory Open Access Journal |
| issn | 2305-7254 2343-0737 |
| language | English |
| last_indexed | 2024-04-13T15:18:37Z |
| publishDate | 2018-05-01 |
| publisher | FRUCT |
| record_format | Article |
| series | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| spelling | doaj.art-2305c5e42c26463da7afa2cb8cbab0152022-12-22T02:41:46ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372018-05-014262227227910.23919/FRUCT.2018.8468301Automatic Online Fake News Detection Combining Content and Social SignalsMarco L. Della Vedova0Eugenio Tacchini1Stefano Moret2Gabriele Ballarin3Massimo DiPierro4Luca de Alfaro5Università Cattolica, Brescia, ItalyUniversità Cattolica, Brescia, ItalyÉcole Poly technique Fédérale, Lausanne, SwitzerlandIndependent researcher, Padova, ItalyDePaul University, Chicago, USADepartment of Computer Science UC Santa, Cruz, CA, USAThe 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%.https://fruct.org/publications/fruct22/files/Ved.pdf fake newsautomatic hoax detectionsocial networksmachine learning |
| spellingShingle | Marco L. Della Vedova Eugenio Tacchini Stefano Moret Gabriele Ballarin Massimo DiPierro Luca de Alfaro Automatic Online Fake News Detection Combining Content and Social Signals Proceedings of the XXth Conference of Open Innovations Association FRUCT fake news automatic hoax detection social networks machine learning |
| title | Automatic Online Fake News Detection Combining Content and Social Signals |
| title_full | Automatic Online Fake News Detection Combining Content and Social Signals |
| title_fullStr | Automatic Online Fake News Detection Combining Content and Social Signals |
| title_full_unstemmed | Automatic Online Fake News Detection Combining Content and Social Signals |
| title_short | Automatic Online Fake News Detection Combining Content and Social Signals |
| title_sort | automatic online fake news detection combining content and social signals |
| topic | fake news automatic hoax detection social networks machine learning |
| url | https://fruct.org/publications/fruct22/files/Ved.pdf
|
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