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

Kenta Yamada, Hayato Yamana

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルAdvanced Information Networking and Applications - Proceedings of the 35th International Conference on Advanced Information Networking and Applications AINA 2021
編集者Leonard Barolli, Isaac Woungang, Tomoya Enokido
出版社Springer Science and Business Media Deutschland GmbH
ページ635-641
ページ数7
ISBN(印刷版)9783030750770
DOI
出版ステータスPublished - 2021
イベント35th International Conference on Advanced Information Networking and Applications, AINA 2021 - Toronto [state] ON, Canada
継続期間: 2021 5 122021 5 14

出版物シリーズ

名前Lecture Notes in Networks and Systems
227
ISSN(印刷版)2367-3370
ISSN(電子版)2367-3389

Conference

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

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 信号処理
  • コンピュータ ネットワークおよび通信

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