A majority-based learning system for detecting misinformation

IF 2.9 4区管理学 Q2 COMPUTER SCIENCE, CYBERNETICS

Behaviour & Information Technology Pub Date : 2024-03-06 DOI:10.1080/0144929x.2024.2326562

Hanchun Kao, Yu-Ju Tu, Yu-Hsiang (John) Huang, Troy Strader

引用次数: 0

Abstract

Combating misinformation is both a multifaceted problem and a pressing societal concern. In response, we propose a user-centric system founded on the majority vote model, offering flexibility and s...

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基于多数的错误信息检测学习系统

打击错误信息既是一个多方面的问题，也是一个紧迫的社会问题。为此，我们提出了一个以用户为中心的系统，该系统建立在多数票模式的基础上，具有灵活性和安全性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Behaviour & Information Technology 工程技术-计算机：控制论

CiteScore

7.70

自引率

8.10%

发文量

159

审稿时长

5 months

期刊介绍： Behaviour & Information Technology (BIT) puts people before technology. As such it deviates from other related journals. It is the primary scientific venue for peer-reviewed publications on human-centred IT. BIT reports original research studies, practical case studies, and thoughtful articles on: • usability and user experience (UX) • human computer interaction (HCI) • human-centred and user-centred design • the social, business and human aspects of the digital world. The Journal attracts authors and readers from a variety of disciplines (e.g., usability, user experience, psychology, ergonomics, computer science, and sociology), originating from both academics and industry. All papers are subject to initial appraisal by the Editor, and, if found suitable for further consideration, will undertake rigorous double blind peer review by independent, anonymous expert referees.