Fake News Detection Datasets: A Review and Research Opportunities

Pummy Dhiman, Amandeep Kaur, Yasir Hamid, Nedal Ababneh
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引用次数: 1

Abstract

: The impact of fake news is far-reaching, a ff ecting journalism, the economy, and democracy. In response, there has been a surge in research focused on detecting and combating fake news, resulting in the development of datasets, techniques, and fact-verification methods. One crucial aspect of this e ff ort is the creation of diverse and representative datasets for training and evaluating machine learning models for fake news detection. This review paper examines the available datasets relevant to detecting fake news, with a particular emphasis on those available in the Indian context, where few resources exist. By identifying research opportunities and highlighting existing corpora, this paper aims to assist researchers in improving their fake news detection studies and contributing to more comprehensive research on the topic. To the best of our knowledge, no survey has specifically focused on accessible corpora in the Indian context, making this review a valuable resource for researchers in the field.
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假新闻检测数据集:回顾与研究机会
:假新闻影响深远,对新闻业、经济和民主都有影响。为此,有关检测和打击虚假新闻的研究激增,数据集、技术和事实验证方法也随之发展起来。这项工作的一个重要方面是创建各种具有代表性的数据集,用于训练和评估假新闻检测的机器学习模型。这篇综述论文研究了与检测假新闻相关的可用数据集,并特别强调了在印度背景下可用的数据集,因为印度的资源很少。通过确定研究机会和强调现有语料库,本文旨在帮助研究人员改进假新闻检测研究,并为更全面地研究该主题做出贡献。据我们所知,还没有一项调查专门关注印度背景下的可访问语料库,因此本综述成为该领域研究人员的宝贵资源。
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来源期刊
International Journal of Computing and Digital Systems
International Journal of Computing and Digital Systems Business, Management and Accounting-Management of Technology and Innovation
CiteScore
1.70
自引率
0.00%
发文量
111
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