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Detecting Fake News in MANET Messaging Using an Ensemble Based Computational Social System

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Image Analysis and Processing. ICIAP 2022 Workshops (ICIAP 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13374))

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Abstract

Mobile Adhoc Networks (MANETs) are utilised in a variety of mission-critical situations and as such, it is important to detect any fake news that exists in such networks. This research proposes an Ensemble Based Computational Social System for fake news detection in MANET messaging. As such this research combines the power of Veracity, a unique, computational social system with that of Legitimacy, a dedicated ensemble learning technique, to detect fake news in MANET messaging. Veracity uses five algorithms namely, VerifyNews, CompareText, PredictCred, CredScore and EyeTruth for the capture, computation and analysis of the credibility and content data features using computational social intelligence. To validate Veracity, a dataset of publisher credibility-based and message content-based features is generated to predict fake news. To analyse the data features, Legitimacy, a unique ensemble learning prediction model is used. Four analytical methodologies are used to analyse these experimental results. The analysis of the results reports a satisfactory performance of the Veracity architecture combined with the Legitimacy model for the task of fake news detection in MANET messaging.

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Author information

Authors and Affiliations

  1. Department of Computing and Information Technology, The University of the West Indies at St Augustine, St Augustine, Trinidad & Tobago

    Amit Neil Ramkissoon & Wayne Goodridge

Authors
  1. Amit Neil Ramkissoon
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  2. Wayne Goodridge
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Corresponding author

Correspondence to Amit Neil Ramkissoon .

Editor information

Editors and Affiliations

  1. National Research Council, Lecce, Italy

    Pier Luigi Mazzeo

  2. Università Politecnica delle Marche, Ancona, Italy

    Emanuele Frontoni

  3. Boston University, Boston, MA, USA

    Stan Sclaroff

  4. National Research Council, Lecce, Italy

    Cosimo Distante

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Ramkissoon, A.N., Goodridge, W. (2022). Detecting Fake News in MANET Messaging Using an Ensemble Based Computational Social System. In: Mazzeo, P.L., Frontoni, E., Sclaroff, S., Distante, C. (eds) Image Analysis and Processing. ICIAP 2022 Workshops. ICIAP 2022. Lecture Notes in Computer Science, vol 13374. Springer, Cham. https://doi.org/10.1007/978-3-031-13324-4_24

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  • DOI: https://doi.org/10.1007/978-3-031-13324-4_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13323-7

  • Online ISBN: 978-3-031-13324-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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