Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)

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A Multi-Factor Framework for Assessing Social Media Comments

Authors
V. S. Arnav Ajay Krishna1, *, S. Aditilakshmi1, S. Saravanan1, D. Punitha1
1SRM Institute of Science and Technology, Vadapalani, Chennai, India
*Corresponding author.
Corresponding Author
V. S. Arnav Ajay Krishna
Available Online 31 October 2025.
DOI
10.2991/978-94-6463-866-0_38How to use a DOI?
Keywords
Linguistics; KeyBERT; cosine similarity; RoBERTa
Abstract

Online comment sections, especially on social media platforms like Reddit, offer rich opportunities for public discussion—but they also suffer from an overwhelming volume of low-quality, repetitive, or toxic content. While previous research has largely focused on sentiment analysis or the detection of hate speech, relatively little attention has been paid to evaluating the overall usefulness of comments within their specific conversational contexts. This project addresses that gap by proposing a multi-dimensional framework designed to highlight insightful, relevant, and civil contributions while deprioritizing those that are redundant, off-topic, or harmful. By incorporating linguistic features such as syntactic structures, discourse markers, and semantic coherence, this framework enhances the precision of evaluating comment quality. Leveraging large-scale Reddit data and recent advances in natural language processing, the system combines semantic clustering, contextual analysis, and content evaluation to compute a single usefulness score for each comment. The goal is to promote more meaningful online discourse by offering a scalable solution that not only detects problematic content but also actively elevates valuable discussion.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
31 October 2025
ISBN
978-94-6463-866-0
ISSN
2589-4919
DOI
10.2991/978-94-6463-866-0_38How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - V. S. Arnav Ajay Krishna
AU  - S. Aditilakshmi
AU  - S. Saravanan
AU  - D. Punitha
PY  - 2025
DA  - 2025/10/31
TI  - A Multi-Factor Framework for Assessing Social Media Comments
BT  - Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
PB  - Atlantis Press
SP  - 450
EP  - 460
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-866-0_38
DO  - 10.2991/978-94-6463-866-0_38
ID  - Krishna2025
ER  -