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First-Impression-Based Unreliable Web Pages Detection – Does First Impression Work?

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Advanced Information Networking and Applications (AINA 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 227))

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Abstract

Considering the continuous increase in the number of web pages worldwide, detecting unreliable pages, such as those containing fake news, is indispensable. Natural language processing and social-information-based methods have been proposed for web page credibility evaluation. However, the applicability of the former to web pages is limited because a model is required for each language, while the latter is poorly adapted to changes, owing to its dependence on external services that can be discontinued. To solve these problems, herein we propose a first-impression-based web credibility evaluation method. Our experimental evaluation of a fake news corpus gave an accuracy of 0.898, which is superior to those of existing methods.

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Acknowledgment

This work was supported by JSPS KAKENHI (Grant Number 17KT0085).

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Authors and Affiliations

  1. Department of Computer Science and Communications Engineering, Waseda University, Tokyo, Japan

    Kenta Yamada & Hayato Yamana

Authors
  1. Kenta Yamada
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  2. Hayato Yamana
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Corresponding author

Correspondence to Kenta Yamada .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Computer Science, Ryerson University, Toronto, ON, Canada

    Isaac Woungang

  3. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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Yamada, K., Yamana, H. (2021). First-Impression-Based Unreliable Web Pages Detection – Does First Impression Work?. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-030-75078-7_63

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