Incremental Machine Learning for Text Classification in Comment Moderation Systems
Wolters, Anna; Müller, Kilian; Riehle, Dennis Maximilian
Abstract
Over the last decade, researchers presented (semi-)automated comment moderation systems (CMS) based on machine learning (ML) and natural language processing (NLP) techniques to support the identification of hateful and offensive comments in online discussion forums. A common challenge in providing and operating comment moderation systems is the dynamic nature of language. As language evolves over time, continuous performance evaluations and resource-inefficient model retraining are applied to ensure high-quality identification of hate speech in the long-term use of comment moderation systems. To study the potentials of adaptable machine learning models embedded in comment moderation systems, we present an incremental machine learning approach for semi-automated comment moderation systems. This study shows a comparison of incrementally-trained ML models and batch-trained ML models used in comment moderation systems.
Keywords
Incremental Learning; Text Classification; Comment Moderation Systems
Cite as
Wolters, A., Müller, K., & Riehle, D. M. (2022). Incremental Machine Learning for Text Classification in Comment Moderation Systems. In Spezzano, F., Amaral, A., Ceolin, D., Fazio, L., & Serra, E. (Eds.),
Disinformation in Open Online Media — 4th Multidisciplinary International Symposium, MISDOOM 2022, Boise, ID, USA, October 11–12, 2022, Proceedings (pp. 138–153). Lecture Notes in Computer Science: Vol. 13545. Cham: Springer Nature.
Details
Publication type
Research article in proceedings (conference)
Peer reviewed
Yes
Publication status
Published
Year
2022
Conference
4th Multidisciplinary International Symposium on Disinformation in Open Online Media
Venue
Boise, ID
Book title
Disinformation in Open Online Media - 4th Multidisciplinary International Symposium, MISDOOM 2022, Boise, ID, USA, October 11–12, 2022, Proceedings
Editor
Spezzano, Francesca; Amaral, Adriana; Ceolin, Davide; Fazio, Lisa; Serra, Edoardo
Start page
138
End page
153
Volume
13545
Title of series
Lecture Notes in Computer Science
Publisher
Springer Nature
Place
Cham
Language
English
ISSN
0302-9743
ISBN
978-3-031-18252-5
DOI
