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Credibility and Reliability News Evaluation Based on Artificial Intelligent Service with Feature Segmentation Searching and Dynamic Clustering

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Combating Fake News with Computational Intelligence Techniques

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1001))

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Abstract

Recently, fake news are spread through Internet, social media, specific organizations or parties. Considering the affection of the fake news to the credibility and reliability, to check and be aware of the news is needed. Based on the artificial intelligence and suitable k-means grouping method, the existed and proved fake news could be used to train the proposed system. The features of the fake news could be classified and identified according to the proposed system in this research. In addition, according to these found features, the news announced or spread by the specific person, organizations, or group, could be classified as the doubtful news.

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Acknowledgements

Thanks for the support of Cloud Computing and Intelligent System Lad. (CCIS Lab.) of National Formosa University.

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Authors and Affiliations

  1. Cloud Computing and Intelligent System Laboratory, Department of CSIE, National Formosa University, Huwei, Taiwan

    Ming-Shen Jian

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  1. Ming-Shen Jian
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Correspondence to Ming-Shen Jian .

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Editors and Affiliations

  1. Hassan II University, Casablanca, Morocco

    Mohamed Lahby

  2. United International University, Dhaka, Bangladesh

    Al-Sakib Khan Pathan

  3. Sultan Moulay Slimane University, Khouribga, Morocco

    Yassine Maleh

  4. Taibah University, Madinah, Saudi Arabia

    Wael Mohamed Shaher Yafooz

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Jian, MS. (2022). Credibility and Reliability News Evaluation Based on Artificial Intelligent Service with Feature Segmentation Searching and Dynamic Clustering. In: Lahby, M., Pathan, AS.K., Maleh, Y., Yafooz, W.M.S. (eds) Combating Fake News with Computational Intelligence Techniques. Studies in Computational Intelligence, vol 1001. Springer, Cham. https://doi.org/10.1007/978-3-030-90087-8_9

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