Fuzzy-Weighted Sentiment Recognition for Educational Text-Based Interactions

Christos Troussas, Christos Papakostas, Akrivi Krouska, Phivos Mylonas

2025

Abstract

In web-based educational environments, students often express complex emotional states – such as confusion, frustration, or engagement – through reflective texts, forum posts, and peer interactions. Traditional sentiment analysis tools struggle to capture these subtle, mixed signals due to their reliance on rigid classification schemes and lack of domain sensitivity. To address this, we propose a fuzzy-weighted sentiment recognition framework designed specifically for educational text-based interactions. The system combines an augmented sentiment lexicon, rule-based modifier detection, and semantic similarity using pretrained Sentence-BERT embeddings to extract nuanced sentiment signals. These inputs are interpreted by a Mamdani-type fuzzy inference engine, producing a continuous sentiment score and a confidence weight that reflect both the strength and reliability of the learner’s affective state. The paper details the linguistic pipeline, fuzzy membership functions, inference rules, and aggregation strategies that enable interpretable and adaptive sentiment modeling. Evaluation on a corpus of 1125 annotated student texts from a university programming course shows that the proposed system outperforms both lexicon-based and deep learning baselines in accuracy, robustness, and interpretability, demonstrating its value for affect-aware educational applications.

Paper Citation

in Harvard Style

Troussas C., Papakostas C., Krouska A. and Mylonas P. (2025). Fuzzy-Weighted Sentiment Recognition for Educational Text-Based Interactions. In Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-772-6, SciTePress, pages 420-428. DOI: 10.5220/0013794200003985

in Bibtex Style

@conference{webist25,
author={Christos Troussas and Christos Papakostas and Akrivi Krouska and Phivos Mylonas},
title={Fuzzy-Weighted Sentiment Recognition for Educational Text-Based Interactions},
booktitle={Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2025},
pages={420-428},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013794200003985},
isbn={978-989-758-772-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - Fuzzy-Weighted Sentiment Recognition for Educational Text-Based Interactions
SN - 978-989-758-772-6
AU - Troussas C.
AU - Papakostas C.
AU - Krouska A.
AU - Mylonas P.
PY - 2025
SP - 420
EP - 428
DO - 10.5220/0013794200003985
PB - SciTePress