Social Media Addiction among the Rural Youth: An AI Interpretation

Abstract views: 138 / PDF downloads: 34


  • Thongam Victory Khanganbi Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore
  • M. Priya Avinahilingam Institute for Home Science and Higher Education for Women, Coimbatore


The impact of social media increasingly influences rural youth in India. Artificial Intelligence is a vast interdisciplinary arena with many domains, not only all the computing disciplines, but also linguistics, neuroscience, statistics, engineering, economics, control theory, and others. The study was undertaken to predict social media addiction by machine learning and to know the accuracy of the addiction level among rural youth. The data were collected through the snowball sampling method, including those using smartphones in rural Coimbatore during the COVID period (2022). A total of 128 rural youth from Coimbatore aged 18 to 24 years were selected as respondents and used naïve Bayes classifier methods to predict the addiction level on social media. 99 respondents were taken under the training set, and the remaining 29 were under the prediction sets to know the accuracy of the Byes model in predicting social media addiction levels. The study predicted its usage accuracy with social media addiction using artificial intelligence and machine learning. The majority of the rural youth were moderately addicted and there were many more causative variables to be assessed further. The naïve byes model accuracy in predicting social media addiction observed was 93.9%.


• Christian, H., Suhartono, D., Chowanda, A. et al. Text-based personality prediction from multiple social media data sources using pre-trained language model and model averaging. J Big Data 8, 68 (2021).

• Confusion Matrix for Machine Learning - Analytics Vidhya.

• Damien Lekkas, Robert J. Klein, Nicholas C. Jacobson, Predicting acute suicidal ideation on Instagram using ensemble machine learning models, Internet Interventions, Volume 25,2021,100424, ISSN 2214-7829,

• Indra, Edi Winarko, Reza Pulungan, Trending topics detection of Indonesian tweets using BN-grams and Doc-p, Journal of King Saud University - Computer and Information Sciences, Volume 31, Issue 2,2019, Pages 266-274, ISSN 1319-1578,

• Jeremy NH, Prasetyo C, Suhartono D. Identifying personality traits for Indonesian users from the Twitter dataset. Int J Fuzzy Logic Intell Syst. 2019;19(4):283–9.

• Leong, Lai-Ying & Hew, Teck-Soon & Ooi, Keng-Boon & Lee, Voon-Hsien & Hew, Jun-Jie. (2019). A hybrid SEM-neural network analysis of social media addiction. Expert Systems with Applications. 133. 10.1016/j.eswa.2019.05.024.

• Lin H, Jia J, Nie L, Shen G, Chua T. What does social media say about your stress?. Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI'16); July 2016; New York, USA. 2016. Jul, pp. 3775–3781.

• N. Valakunde and S. Ravikumar, "Prediction of Addiction to Social Media," 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2019, pp. 1-6, DOI: 10.1109/ICECCT.2019.8869399

• Naïve Bayes Algorithm.

• R.C. Brown, E. Bendig, T. Fischer, A.D. Goldwich, H. Baumeister, P.L. Plener Can acute suicidality be predicted by Instagram data? Results from qualitative and quantitative language analysis PLoS ONE, 14 (9) (2019), Article e0220623, 10.1371/journal.pone.0220623

• Rubaiyat, Nadia & Apsara, Anika & Chaki, Dipankar & Arif, Hossain & Israt, Lamiah & Kabir, Lamiya & Alam, Md Golam Rabiul. (2019). Classification of Depression, Internet Addiction and Prediction of Self-esteem among University Students. 1-6. 10.1109/ICCIT48885.2019.9038211

• Savci, Mustafa & Tekin, Ahmet. (2020). Prediction of problematic social media use (PSU) using machine learning approaches. Current Psychology. 10.1007/s12144-020-00794-1.

• Priyanka Ranu, Rashmi Tyagi, Jatesh Kathpalia, Vinod Kumar (2023), Impact of Social Media on the Heath of the Rural Youth: A Sociological Study. IAHRW International Journal of Social Sciences Review,Pp-247-251,vol-11 no.02

• Patwari, Indrani and Patwari, Indrani, Use of social media by Rural Youth in India: A Boon or a Bane (June 11, 2020). Available at SSRN: or

• Görkemli, H. N. (2017). Internet and social media usage of secondary school students in rural areas. Manas Sosyal Araştırmalar Dergisi, 6(1), 1-11

• Cabral, Jaclyn. (2008). Is Generation Y Addicted to social media? Elon Journal of Undergraduate Research in Communications. 2.






How to Cite

Social Media Addiction among the Rural Youth: An AI Interpretation. (2024). Indian Journal of Extension Education, 60(2), 52-55.