Nepali Fake News Detection Using Machine Learning Algorithms
Year: 2025
Type: article
Abstract: The Internet's rapid development makes it possible for information to spread quickly through websitesor social networks. Fake or unverified news spreads on social media and reaches thousands of userswithout anyone questioning its veracity. Misinformation or fabricated news that spreads on social mediawith the intention of harming a person, group, or agency is known as fake news. Various machine-learningtechniques have been used to distinguish fake news from real. In this paper, we tried to achieve this usingmachine learning techniques and natural language processing. We use frequency-inverse documentfrequency as a feature extraction method and logistic regression, support vector machine and Naive Bayesas the classifier. We use a dataset with labels for fake and real news to train our model.
Author: Rakshya Sharma, Bidhya Sharma, Prashikshya Baral, Susmita Parajuli
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6931001896
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