LFWE: Linguistic Feature Based Word Embedding for Hindi Fake News Detection

Author:

Sharma Richa1ORCID,Arya Arti1ORCID

Affiliation:

1. PES University

Abstract

It is essential for research communities to investigate ways for authenticating news. The use of linguistic feature based analysis to automatically detect false news is gaining popularity among the scientific community. However, such techniques are exclusively created for English, leaving low-resource languages like Hindi behind. To address this issue, we constructed a novel annotated Hindi Fake News (HinFakeNews) dataset of roughly 33,300 articles that can be utilized to develop autonomous fake news detection systems. This work provides a two-stage benchmark model for identifying fake news in Hindi using machine learning. The proposed model, LFWE (Linguistic Feature Based Word Embedding), generates word embedding over linguistic features. This article focuses on 23 key linguistic features (15 extracted and 08 derived) for successful detection of Hindi fake news. These features are grouped as lexical, semantic, syntactic, psycho-linguistic, readability, and quantity features. The contribution is twofold. In the first phase, the dataset is preprocessed and linguistic features are extracted. In the second phase, feature sets are generated as word embeddings, and an Ensemble voting classification is carried out on the feature sets. According to experimental findings, the LFWE model accurately detects and classifies fake news in Hindi with an accuracy of 98.49%.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Reference51 articles.

1. S. Rukmini. 2019. In India who speaks in English and where? from. https://www.livemint.com/news/india/in-india-who-speaks-in-english-and-where-1557814101428.html.

2. Language-Independent Fake News Detection: English, Portuguese, and Spanish Mutual Features

3. Syeda Zainab Akbar, Divyanshu Kukreti, Somya Sagarika, and Joyojeet Pal. 2020. Temporal Patterns in COVID-19 Related Digital Misinformation in India. Retrieved April 7, 2023 from http://joyojeet.people.si.umich.edu/temporal-patterns-in-covid-19-misinformation-in-india/.

4. Where is Your Evidence: Improving Fact-checking by Justification Modeling

5. Social Media and Fake News in the 2016 Election

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3