A Classification Algorithm to Recognize Fake News Websites
| Autor: | Benedetto Torrisi, Giuseppe Pernagallo, Davide Bennato |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Information retrieval
Computer science Reliability (computer networking) 05 social sciences Section (typography) 02 engineering and technology Websites Statistics - Applications Misleading information Computer Science - Computers and Society Binary data. Classification algorithm Fake news Logit Misleading information Websites Fake news 020204 information systems 0502 economics and business Logit 0202 electrical engineering electronic engineering information engineering cs.SI Binary data. Classification algorithm Classifier (UML) 050203 business & management News media |
| Zdroj: | Studies in Classification, Data Analysis, and Knowledge Organization ISBN: 9783030512217 |
| DOI: | 10.1007/978-3-030-51222-4_25 |
| Popis: | “Fake news” is information that generally spreads on the web, which mimics the form of reliable news media content. In this paper, we use a classifier to distinguish a reliable source from a fake news website based on information potentially available on websites, such as the presence of a “contact us” section or a secured connection. This framework offers a concrete solution to attribute a “reliability score” to news websites, defined as the probability that a source is reliable or not, and based on this probability a user can decide if the news is worth sharing. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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