StressSGCL: A Stress-Specific Embeddings Learning Approach using Contrastive Learning over Skip-Gram Model

Muhammad Abulaish; Rumjot Kaur; Amit Kumar Sah

doi:10.36190/2025.17

Workshop Proceedings of the 19th International AAAI Conference on Web and Social Media

Workshop: CySoc 2025: 6th International Workshop on Cyber Social Threats

DOI: 10.36190/2025.17

Published: 2025-06-05

StressSGCL: A Stress-Specific Embeddings Learning Approach using Contrastive Learning over Skip-Gram Model

Muhammad Abulaish, Rumjot Kaur, Amit Kumar Sah

In this paper, we present StressSGCL, a novel approach that produces stress-specific word embeddings to enhance stress detection in social media posts. The proposed approach improves contextual representation by integrating the skip-gram model with transformers-based Pre-trained Language Models (PLMs). Subsequently, it refines these embeddings through supervised contrastive learning, which focuses on the differentiation of stress-related emotional content. The StressSGCL is evaluated using two PLMs (BERT and MentalBERT) on three benchmark datasets from Twitter and Reddit. Empirical evaluation...

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