Psychological Impact of Internet Blackouts: A Case Study With Machine Learning-Based Stress Analysis
Access to the internet has become a vital part of modern life, especially for communication and essential services. However, during politically sensitive times, internet blackouts can disrupt daily routines, leading to significant psychological impacts. This study explores the mental health effects...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10994435/ |
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| author | Mohammad Ariful Islam Tahidul Islam Gahangir Hossain M. Mofazzal Hossain |
| author_facet | Mohammad Ariful Islam Tahidul Islam Gahangir Hossain M. Mofazzal Hossain |
| author_sort | Mohammad Ariful Islam |
| collection | DOAJ |
| description | Access to the internet has become a vital part of modern life, especially for communication and essential services. However, during politically sensitive times, internet blackouts can disrupt daily routines, leading to significant psychological impacts. This study explores the mental health effects of the internet shutdown imposed during the Bangladesh Quota Movement in July 2024, when the government cut off access to control information flow. The blackout hindered communication, financial transactions, and critical services, amplifying stress, feelings of isolation, and emotional distress. A survey of 2,085 participants was conducted to assess the behavioral, emotional, and psychological consequences, particularly in academic, work, and social settings. Stress levels among respondents varied from minimal to extreme, reflecting widespread mental distress. To classify these stress levels, machine learning models; Decision Tree (DT), Random Forest (RF), Bernoulli Naive Bayes (BNB), Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) were applied. The SVM model outperformed others, achieving high precision (99.33%), recall (99.00%), F1-score (99.33%), and accuracy (99.49%). This study underscores the urgent need for mental health support during such crises, particularly in low- and middle-income countries like Bangladesh, where mental health care is often neglected. These findings are aligned with Sustainable Development Goal (SDG 3), “Good Health and Well-Being,” stressing the importance of mental health interventions in fostering resilience, well-being, and social stability during crises. |
| format | Article |
| id | doaj-art-1376fbe0b11b427bb04e05bc491b3057 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| spelling | doaj-art-1376fbe0b11b427bb04e05bc491b30572025-08-20T03:48:07ZengIEEEIEEE Access2169-35362025-01-0113835058352710.1109/ACCESS.2025.356843410994435Psychological Impact of Internet Blackouts: A Case Study With Machine Learning-Based Stress AnalysisMohammad Ariful Islam0Tahidul Islam1Gahangir Hossain2https://orcid.org/0000-0002-8205-4939M. Mofazzal Hossain3https://orcid.org/0000-0001-9679-3276Department of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, AustraliaDepartment of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, BangladeshDepartment of Data Science, University of North Texas, Denton, TX, USADepartment of Electrical and Electronic Engineering, Southeast University, Dhaka, BangladeshAccess to the internet has become a vital part of modern life, especially for communication and essential services. However, during politically sensitive times, internet blackouts can disrupt daily routines, leading to significant psychological impacts. This study explores the mental health effects of the internet shutdown imposed during the Bangladesh Quota Movement in July 2024, when the government cut off access to control information flow. The blackout hindered communication, financial transactions, and critical services, amplifying stress, feelings of isolation, and emotional distress. A survey of 2,085 participants was conducted to assess the behavioral, emotional, and psychological consequences, particularly in academic, work, and social settings. Stress levels among respondents varied from minimal to extreme, reflecting widespread mental distress. To classify these stress levels, machine learning models; Decision Tree (DT), Random Forest (RF), Bernoulli Naive Bayes (BNB), Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) were applied. The SVM model outperformed others, achieving high precision (99.33%), recall (99.00%), F1-score (99.33%), and accuracy (99.49%). This study underscores the urgent need for mental health support during such crises, particularly in low- and middle-income countries like Bangladesh, where mental health care is often neglected. These findings are aligned with Sustainable Development Goal (SDG 3), “Good Health and Well-Being,” stressing the importance of mental health interventions in fostering resilience, well-being, and social stability during crises.https://ieeexplore.ieee.org/document/10994435/Internet blackoutquota movementmental healthmachine learningsustainable development goal (SDG 3) |
| spellingShingle | Mohammad Ariful Islam Tahidul Islam Gahangir Hossain M. Mofazzal Hossain Psychological Impact of Internet Blackouts: A Case Study With Machine Learning-Based Stress Analysis IEEE Access Internet blackout quota movement mental health machine learning sustainable development goal (SDG 3) |
| title | Psychological Impact of Internet Blackouts: A Case Study With Machine Learning-Based Stress Analysis |
| title_full | Psychological Impact of Internet Blackouts: A Case Study With Machine Learning-Based Stress Analysis |
| title_fullStr | Psychological Impact of Internet Blackouts: A Case Study With Machine Learning-Based Stress Analysis |
| title_full_unstemmed | Psychological Impact of Internet Blackouts: A Case Study With Machine Learning-Based Stress Analysis |
| title_short | Psychological Impact of Internet Blackouts: A Case Study With Machine Learning-Based Stress Analysis |
| title_sort | psychological impact of internet blackouts a case study with machine learning based stress analysis |
| topic | Internet blackout quota movement mental health machine learning sustainable development goal (SDG 3) |
| url | https://ieeexplore.ieee.org/document/10994435/ |
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