Thai clickbait detection using natural language processing with machine learning techniques

Name: Praphan Klairith.

keyword: Clickbait.

LCSH: Machine learning.

LCSH: Internet searching.

LCSH: Neural networks (Computer science)

LCSH: Cyberstalking -- Prevention.

LCSH: Internet fraud -- Prevention.

LCSH: Detectors.

Abstract: This thesis proposes the approach based on machine learning for detection of Thai clickbait. The clickbait messages often adopt eye-catching on wording, lagging of information on a content to attract visitors. The clickbait corpus is contributed by crowdsourcing, 30,000 of headlines are selected to draw up the dataset. In this work, we attempt to develop a clickbait detection model using two type of features in the embedding layer and three different networks in the hidden layer. Bidirectional Long-short term memory with word-level embedding performs very well achieving an accuracy rate of 0.98, fl- score of 0.98

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Name: Sansiri Tanachutiwat

Role: Thesis advisors.

Email : sansirit@kmutnb.ac.th, sansiri.t.sse@tggs-bangkok.org

Created: 2017

Modified: 2563-10-12

Issued: 2020-10-12

วิทยานิพนธ์/Thesis

application/pdf

eng

DegreeName: Master of Engineering

Level: Master's Degree

Descipline: Electrical and Software Systems Engineering (International Program)

Grantor: King Mongkut's University of Technology North Bangkok

©copyrights King Mongkut's University of Technology North Bangkok

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