Classification and Detection of Amharic Language Fake News on Social Media Using Machine Learning Approach

Authors

  • Kedir Lemma Arega School of Technology and Informatics, Department of Information Technology, Ambo University, Ethiopia

DOI:

https://doi.org/10.30564/ese.v4i1.3885

Abstract

The pervasive idea of web-based media stages brought about a lot of sight and sound information in interpersonal organizations. The transparency and unlimited way of sharing the data via online media stage encourages data spread across the organization paying little mind to its noteworthiness.The multiplication of misdirecting data in regular access news sources, for example, web-based media channels, news websites, and online papers has made it trying to recognize dependable news sources, in this way expanding the requirement for computational devices to give bits of knowledge into the unwavering quality of online substance. The broad spread of phony news contrarily affects people and society. Along these lines, counterfeit news identification via web-based media has as of late become arising research drawing in enormous consideration. Observing the possible damage caused by the rapid spread of fake news in various fields such as politics and finance, the use of language analysis to automatically identify fake news has attracted the attention of the research community. A social networking service is a platform for people with similar interests, activities,or backgrounds to form social networks or social relations. Participants who register on this site with its own expression (often a profile) and social links are generally offered a social network service.

Keywords:

Amharic fake news detection, Amharic posts and comments datasets, Classification, Machine learning, Social media

References

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How to Cite

Arega, K. L. (2022). Classification and Detection of Amharic Language Fake News on Social Media Using Machine Learning Approach. Electrical Science & Engineering, 4(1), 1–6. https://doi.org/10.30564/ese.v4i1.3885

Issue

Vol. 4 , Iss. 1 (April 2022)

Article Type

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