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

Kenta Yamada, Hayato Yamana

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationAdvanced Information Networking and Applications - Proceedings of the 35th International Conference on Advanced Information Networking and Applications AINA 2021
EditorsLeonard Barolli, Isaac Woungang, Tomoya Enokido
PublisherSpringer Science and Business Media Deutschland GmbH
Pages635-641
Number of pages7
ISBN (Print)9783030750770
DOIs
Publication statusPublished - 2021
Event35th International Conference on Advanced Information Networking and Applications, AINA 2021 - Toronto [state] ON, Canada
Duration: 2021 May 122021 May 14

Publication series

NameLecture Notes in Networks and Systems
Volume227
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference35th International Conference on Advanced Information Networking and Applications, AINA 2021
Country/TerritoryCanada
CityToronto [state] ON
Period21/5/1221/5/14

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications

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