Oct 2026· International Journal of Machine Learning and Cybernetics· Vol 17· 0 citations· 48 references
TL;DR
A modified DistilBERT that incorporates lexical emotion representations into the transformer pipeline via a feature fusion layer with attention weighting is proposed, which enables the joint learning of semantic dependencies, lexical cues, and text embeddings, which enhances the recognition of underrepresented emotions.
This research introduces a Hybrid Attention Learning with Graph Convolutional Network for Text-Based Emotion Detection (HALGCN-TED) framework, aiming to develop a robust and automated model to improve the representation and detection of complex emotional patterns.
Mohammad A. Mahzari, Noah N. Alsager, A. Hilal· Research Journal in Advanced...· 0 citations
Emotion detection from textual data plays an important role in understanding the emotional content expressed through written language. Moreover, the natural language processing (NLP) provides useful techniques for analyzing textual content and identifying meaningful linguistic patterns associated with different emotion...
Noah N. Alsager, Mohammad A. Mahzari, H. Alsager· Research Journal in Advanced...· 0 citations
Emotion detection is the process of recognizing the emotional state expressed through textual content. It has become an important task in Natural Language Processing (NLP) due to the growing amount of text-based communication. Moreover, the NLP techniques help to analyze textual information and classify it into differe...
Mohammad A. Mahzari, Noah N. Alsager, A. Hilal· Research Journal in Advanced...· 0 citations
Corpus linguistics offers a structured approach to assess huge set of texts (corpora) to uncover language patterns, structural relationships, and semantic interpretations. Within text-based emotion recognition (TER), corpus linguistics facilitates the identification of linguistic features that show underlying emotional...
Noah N. Alsager, Mohammad A. Mahzari, H. Alsager· Research Journal in Advanced...· 0 citations
The virtualized nature of online English instruction weakens affective interaction between teachers and learners. This study proposes a multimodal dialogue emotion recognition method based on a semantic-enhanced graph and develops an emotion classification framework optimized for the unique multimodal noise and implici...
Xiao-Li Huang, A. Cheema· PeerJ Computer Science· 0 citations
This paper presents an end-to-end pipeline for automated social media discourse analysis, integrating situation extraction from natural language texts, emotion classification, and value identification. Most existing approaches are limited to binary sentiment analysis and do not account for the value context underlying...
Ko Hein, D. Palchunov· Vestnik NSU Series Informati...· 0 citations
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