Social media use among adolescents with limited family support: Insights from Uses and Gratifications Theory
DOI:
https://doi.org/10.61126/dtcs.v4i1.162Keywords:
social media, adolescents, broken-home families, Uses and Gratifications Theory, IndonesiaAbstract
This study examines social media use among adolescents from broken-home family backgrounds, focusing on how it shapes emotional coping strategies and influences emotional well-being. As social media has become deeply embedded in adolescents' daily lives, it plays an important role in their social and emotional experiences. Drawing on the Uses and Gratifications Theory, this study explores the motives underlying social media use to fulfill emotional and psychological needs among adolescents experiencing disharmonious family relationships. A qualitative descriptive approach was employed involving 24 Indonesian adolescents who met the study's inclusion criteria. Data were collected through in-depth interviews and observations of participants' everyday social media use. The findings show that social media functions as an emotional coping mechanism, enabling adolescents to regulate emotions and manage personal stress. Scrolling emerged as the most common activity for emotional distraction, while liking, sharing, and commenting served as forms of social validation. Consequently, many participants spent more time engaging with social media than interacting with their families. The emotional connections formed through social media fulfilled needs that remained unmet within their family environments. Among the available platforms, Instagram was the most preferred because its features best accommodated participants' emotional needs and preferences.
References
American Academy of Pediatrics. (2023). Center of excellence on social media and youth mental health. https://www.aap.org/en/patient-care/center-of-excellence-on-social-media-and-youth-mental-health/
American Psychological Association. (2002). Developing adolescents: A reference for professionals. American Psychological Association.
Baumeister, R. F., & Leary, M. R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117(3), 497–529. https://doi.org/10.1037/0033-2909.117.3.497
Baumrind, D. (1991). The influence of parenting style on adolescent competence and substance use. The Journal of Early Adolescence, 11(1), 56–95. https://doi.org/10.1177/0272431691111004
boyd, d. (2014). It's complicated: The social lives of networked teens. Yale University Press.
Castells, M. (2009). Communication power. Oxford University Press.
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook "friends": Social capital and college students' use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143–1168. https://doi.org/10.1111/j.1083-6101.2007.00367.x
Kad, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. Public Opinion Quarterly, 37(4), 509–523. https://doi.org/10.1086/268109
Lim, M. (2013). Many clicks but little sticks: Social media activism in Indonesia. Journal of Contemporary Asia, 43(4), 636–657. https://doi.org/10.1080/00472336.2013.769386
Lim, M. (2017). Freedom to hate: Social media, algorithmic enclaves, and the rise of tribal nationalism in Indonesia. Critical Asian Studies, 49(3), 411–427. https://doi.org/10.1080/14672715.2017.1341188
Liu, B. (2012). Sentiment analysis and opinion mining. Foundations and Trends in Information Retrieval, 5(1), 1–167. https://doi.org/10.2200/S00416ED1V01Y201204HLT016
Loader, B. D., & Mercea, D. (2011). Networking democracy? Information, Communication & Society, 14(6), 757–769. https://doi.org/10.1080/1369118X.2011.592648
Mall, R., Nagpal, M., Salminen, J., Almerekhi, H., Jung, S., & Jansen, B. J. (2024). Politics on YouTube: Detecting online group polarization based on news videos' comments. SAGE Open, 14(2), Article 21582440241253376. https://doi.org/10.1177/21582440241253376
McCombs, M. E., & Shaw, D. L. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36(2), 176–187. https://doi.org/10.1086/267990
Möller, A. M., Kühne, R., Baumgartner, S. E., & Peter, J. (2019). Exploring user responses to entertainment and political videos: An automated content analysis of YouTube. Social Science Computer Review, 38(5), 614–630. https://doi.org/10.1177/0894439318790704
Muaz, A., Santoso, J., & Purwarianti, A. (2019). Experiment and analysis of cross-language sentiment analysis on Twitter. In 2019 International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA) (pp. 1–6). IEEE. https://doi.org/10.1109/ICAICTA.2019.8904074
Nature. (2023). Tools such as ChatGPT threaten transparent science: Here are our ground rules for their use. Nature, 613(7945), 612. https://doi.org/10.1038/d41586-023-00191-1
Nichols, B. (2010). Introduction to documentary (2nd ed.). Indiana University Press.
O'Mahony, P., & Skillington, T. (2013). The public sphere and the politics of knowledge. In P. O'Mahony (Ed.), The contemporary theory of the public sphere (pp. 1–20). Peter Lang.
Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1–2), 1–135. https://doi.org/10.1561/1500000011
Plantinga, C. (1997). Rhetoric and representation in nonfiction film. Cambridge University Press.
Scheufele, D. A. (1999). Framing as a theory of media effects. Journal of Communication, 49(1), 103–122. https://doi.org/10.1111/j.1460-2466.1999.tb02784.x
Sobieraj, S., & Berry, J. M. (2011). From incivility to outrage: Political discourse in blogs, talk radio, and cable news. Political Communication, 28(1), 19–41. https://doi.org/10.1080/10584609.2010.542360
Sorensen, L. (2024). Populist disruption and the fourth age of political communication. European Journal of Communication, 39(1), 3–19. https://doi.org/10.1177/02673231231209467
Sunstein, C. R. (2017). #Republic: Divided democracy in the age of social media. Princeton University Press.
Tashakkori, A., Johnson, R. B., & Teddlie, C. (2021). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences (2nd ed.). Sage.
Thelwall, M. (2018). Social media analytics for YouTube comments: Potential and limitations. Cyberpsychology, Behavior, and Social Networking, 21(6), 341–347. https://doi.org/10.1089/cyber.2017.0568
van Dijk, T. A. (2008). Discourse and power. Palgrave Macmillan.
Veneti, A., Jackson, D., & Lilleker, D. G. (2019). Visual political communication. Palgrave Macmillan. https://doi.org/10.1007/978-3-030-18729-3
Wongso, R., Setiawan, D. A., & Suhartono, D. (2023). Causal language modeling of Indonesian BERT sentiment classification. Procedia Computer Science, 216, 396–403. https://doi.org/10.1016/j.procs.2022.12.153
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