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Title:
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PROPOSAL FOR A MODEL FOR DETECTING FAKE
NEWS ON SOCIAL MEDIA IN MEXICO |
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Author(s):
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Carlos Augusto Jiménez Zarate and Leticia Amalia Neira Tovar |
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ISBN:
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978-989-8704-38-2 |
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Editors:
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Piet Kommers, Inmaculada Arnedillo Sánchez and Pedro Isaías |
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Year:
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2022 |
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Edition:
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Single |
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Keywords:
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Fake News, Machine Learning, Social Media |
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First Page:
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92 |
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Last Page:
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98 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The emission of false news on social networks has been increasing continuously, this work analyzes the different automatic
detection techniques used for false news, proposes an integration of different machine learning algorithms in addition to
the development of a new data set of news tweets in Mexico. To do this, an extraction of tweets from the Mexican media
and from sites known as transmitters of false news in Mexico was carried out. The dataset classification test showed that it
was the passive-aggressive algorithm that obtained the best accuracy with 79.6%. |
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