Community recommendation for text post in social media

Name: Sarach Tuomchomtam

LCSH: Kasetsart University -- Theses. M.S. (Computer Science) 2018

Classification :.LCCS: QA76.9.D343

LCSH: Kasetsart University. -- Department of Computer Science -- Theses

LCSH: Data mining

LCSH: Text data mining

LCSH: Social media

Abstract: Reddit is a popular social media website where users can submit content such as direct links and text posts into a forum called subreddit. The average number of new subreddits created reaches 500 per day. Because of the vast and growing number of subreddits, users need to discover and familiarize themselves with all existing communities before submission. We propose new feature sets for an online community which are text posts ratio, the average length of text in the post and the domain-specific features. The community recommendation framework is designed and experimented based on Reddit dataset. The framework successfully identifies and collects textual communities by finding their representatives using clustering algorithm namely DBSCAN, then a logistic regression algorithm is applied to recommend a list of communities with high content similarity to a given post. Comprehensive experimental evaluations on Reddit dataset reveal that the proposed framework achieves high precision at 90%.

Kasetsart University. Office of the University Library

Address: Bangkok

Email: tdckulib@ku.ac.th

Name: Nuanwan Soonthornphisaj

Role: Thesis Advisor

Created: 2018

Modified: 2025-07-09

Issued: 2025-07-09

วิทยานิพนธ์/Thesis

application/pdf

URL: https://www.lib.ku.ac.th/KUthesis/2561/sarach-tuo-all.pdf

CallNumber: QA76.9.D343 .S27

eng

DegreeName: Master of Science

Level: Master's Degree

Descipline: Computer Science

Grantor: Kasetsart University

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