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Exploring Mental Stress Expressions in Online Communities: A Subreddit Analysis

Tran Anh Tuan, Nguyen Huu Nghia, Tran Dai An, Dao Thi Thanh Loan

Abstract


Objectives: This study aims to comprehensively explore trends, sentiments, and visualization of mental stress expressions in online communities, focusing on discussions within subreddits on the social media platform Reddit. Methods/Analysis: Advanced text analysis and statistical techniques are employed to achieve the study’s objectives. The research utilizes natural language processing (NLP) methods, sentiment analysis, and topic modeling to unravel the intricate layers of mental stress expressions found in posts across diverse subreddits. Additionally, engagement metrics, such as Redditors’ scores and the number of comments, are analyzed to discern distinctive information and patterns of interest. Findings: The research sheds light on prevalent trends, sentiments, and themes related to mental stress in online conversations before and after January 2020. The findings provide valuable insights into patterns of exciting topics, shared experiences of stress, coping mechanisms, and the significant role of virtual communities in offering support and understanding. Novelty/Improvement: The novelty lies in applying advanced text analysis techniques, including sentiment analysis with the majority voting method combining different machine learning techniques and topic modeling with semantic networks, to gain a deeper understanding of the dynamics of mental stress expressions in online communities. The research explores current patterns and distinguishes itself by examining temporal variations in stress-related posts and their correlation with engagement metrics, offering an innovative perspective on mental health discussions in the digital age.

 

Doi: 10.28991/HEF-2024-05-02-01

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Keywords


Mental Stress; Sentiment Analysis; Public Opinion; Subreddits; Natural Language Processing.

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Full Text: PDF

DOI: 10.28991/HEF-2024-05-02-01

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