Misinformation detection in Thai-language content on social media: a case study in health information

Weeranuch Proysaithong

Name: Weeranuch Proysaithong

LCSH: Social media

LCSH: Machine learning

ThaSH: Thai language -- Errors of usage

Abstract: The continuous increase in the use of social media has made misinformation a significant problem. This research aims to develop a model for detecting Thai misinformation on social media, focusing on the impact of text preprocessing techniques on model accuracy. Three text preprocessing methods were selected: Replacing Numbers with Thai Words, Removing Punctuation, and Removing stop Words. These methods were experimented with three classification models: Naive Bayes, Support Vector Machine, and Random Forest. The results showed that the best performance was achieved when using the Remove Numbers with Thai words preprocessing method and the Support Vector Machine model, with an accuracy of 95.47%

King Mongkut's Institute of Technology Ladkrabang. Central Library

Address: BANGKOK

Email: Lifelong@kmitl.ac.th

Name: Jiraphat Yokrattanasak

Role: Thesis Advisor

Created: 2024

Modified: 2024-11-12

Issued: 2024-11-12

วิทยานิพนธ์/Thesis

application/pdf

eng

DegreeName: Master of Science

Level: Master's Degree

Descipline: Data Science and Analytics

Grantor: King Mongkut's Institute of Technology Ladkrabang

©copyrights King Mongkut's Institute of Technology Ladkrabang

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