Fake News Detection on Social Media: A Systematic Survey
| Autor: | Kin Fun Li, Fayez Gebali, Mohamed K. Elhadad |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Process (engineering)
business.industry Computer science 05 social sciences Internet privacy 02 engineering and technology Social issues 0506 political science Politics 050602 political science & public administration 0202 electrical engineering electronic engineering information engineering Disinformation 020201 artificial intelligence & image processing Mobile technology Social media Tracking (education) Misinformation business |
| Zdroj: | PACRIM |
| DOI: | 10.1109/pacrim47961.2019.8985062 |
| Popis: | These days there are instabilities in many societies in the world, either because of political, economic, and other societal issues. The advance in mobile technology has enabled social media to play a vital role in organizing activities in favour or against certain parties or countries. Many researchers see the need to develop automated systems that are capable of detecting and tracking fake news on social media. In this paper, we introduce a systematic survey on the process of fake news detection on social media. The types of data and the categories of features used in the detection model, as well as benchmark datasets are discussed. |
| Databáze: | OpenAIRE |
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