Finding Fake News Websites in the Wild
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arXiv
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| Format: | Preprint |
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2024
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| author | Araujo, Leandro Couto, Joao M. M. Nery, Luiz Felipe Rodrigues, Isadora C. Almeida, Jussara M. Reis, Julio C. S. Benevenuto, Fabricio |
| author_facet | Araujo, Leandro Couto, Joao M. M. Nery, Luiz Felipe Rodrigues, Isadora C. Almeida, Jussara M. Reis, Julio C. S. Benevenuto, Fabricio |
| contents | The battle against the spread of misinformation on the Internet is a daunting task faced by modern society. Fake news content is primarily distributed through digital platforms, with websites dedicated to producing and disseminating such content playing a pivotal role in this complex ecosystem. Therefore, these websites are of great interest to misinformation researchers. However, obtaining a comprehensive list of websites labeled as producers and/or spreaders of misinformation can be challenging, particularly in developing countries. In this study, we propose a novel methodology for identifying websites responsible for creating and disseminating misinformation content, which are closely linked to users who share confirmed instances of fake news on social media. We validate our approach on Twitter by examining various execution modes and contexts. Our findings demonstrate the effectiveness of the proposed methodology in identifying misinformation websites, which can aid in gaining a better understanding of this phenomenon and enabling competent entities to tackle the problem in various areas of society. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_07159 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Finding Fake News Websites in the Wild Araujo, Leandro Couto, Joao M. M. Nery, Luiz Felipe Rodrigues, Isadora C. Almeida, Jussara M. Reis, Julio C. S. Benevenuto, Fabricio Computers and Society Social and Information Networks The battle against the spread of misinformation on the Internet is a daunting task faced by modern society. Fake news content is primarily distributed through digital platforms, with websites dedicated to producing and disseminating such content playing a pivotal role in this complex ecosystem. Therefore, these websites are of great interest to misinformation researchers. However, obtaining a comprehensive list of websites labeled as producers and/or spreaders of misinformation can be challenging, particularly in developing countries. In this study, we propose a novel methodology for identifying websites responsible for creating and disseminating misinformation content, which are closely linked to users who share confirmed instances of fake news on social media. We validate our approach on Twitter by examining various execution modes and contexts. Our findings demonstrate the effectiveness of the proposed methodology in identifying misinformation websites, which can aid in gaining a better understanding of this phenomenon and enabling competent entities to tackle the problem in various areas of society. |
| title | Finding Fake News Websites in the Wild |
| topic | Computers and Society Social and Information Networks |
| url | https://arxiv.org/abs/2407.07159 |