02NLP / September 27, 2024
Leveraging BERT-Enhanced MLP Classifier for Automated Stress Detection in Social Media Articles
2024 International Conference on Advances in Computing Research on Science Engineering and Technology (ACROSET)
Amlan Nayak, Amiya Ranjan Panda, Debapam Pal, Sudatta Jana, Pratim Mangaldas Dasude, Utkarsh Anand
01Abstract
The surge in stress-related content on social media platforms has sparked concerns over the mental well-being of online community members. This study addresses the detection of stress from social media articles, focusing on data gathered from platforms such as Reddit and Twitter. Through the application of machine learning techniques, our objective is to create automated tools capable of identifying stress-inducing content and tracking mental health trends in online discourse. To achieve this, we compiled a dataset comprising over 8000 social media articles from Reddit and Twitter, each labeled as stress-inducing or non-stress-inducing. Our analysis began with exploratory data analysis to uncover insights into the dataset's characteristics, followed by preprocessing steps to clean and prepare the text data for modeling. Experiments using various machine learning models, including Logistic Regression, Gaussian Processes Classifier, and BERT-Enhanced MLP Classifier, were then conducted. The latter leverages BERT embeddings to capture contextualized representations of the text data, resulting in superior classification performance. The results demonstrate the BERT-Enhanced MLP Classifier's effectiveness, achieving an accuracy of 0.95 and surpassing baseline models. This study contributes to the advancement of automated tools for mental health monitoring and support in online communities, potentially aiding in timely interventions for individuals at risk.
02At a glance
Taken directly from the abstract.
- Task
- Stress detection in social media text
- Data
- Over 8,000 Reddit and Twitter articles, labeled stress-inducing or not
- Models
- Logistic Regression, Gaussian Processes Classifier, BERT-Enhanced MLP
- Best result
- BERT-Enhanced MLP, accuracy 0.95, ahead of the baselines
03Details
- Publisher
- IEEE
- Published
- September 27, 2024
- Pages
- 1-6
- DOI
- 10.1109/ACROSET62108.2024.10743857
- Cited by
- 3 (Google Scholar, Oct 2026)
04Cite this paper
IEEE style.
A. Nayak, A. R. Panda, D. Pal, S. Jana, P. M. Dasude, U. Anand, "Leveraging BERT-Enhanced MLP Classifier for Automated Stress Detection in Social Media Articles," in 2024 International Conference on Advances in Computing Research on Science Engineering and Technology (ACROSET), IEEE, Sep. 2024, pp. 1–6, doi: 10.1109/ACROSET62108.2024.10743857.