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Research Article

Machine Learning-Based Approach: Enhancing Social Media Platform

Sivakumar Nagarajan1
Technical Architect, I & I Software Inc, 2571 Baglyos Circle, Suite B-32, Bethlehem, Pennsylvania, USA

Published Online: September-October 2024

Pages: 01-07

References

1) Mingoia, J.; Hutchinson, A.D.; Wilson, C.; Gleaves, D.H. The relationship between social networking site use and the internalization of a
thin ideal in females: A meta-analytic review. Front. Psychol. 2017, 8, 1351
2) Verduyn, P.; Ybarra, O.; Résibois, M.; Jonides, J.; Kross, E. Do social network sites enhance or undermine subjective well-being? A critical
review. Soc. Issues Policy Rev. 2017, 11, 274–302.
3) Yang, C.-C. Instagram use, loneliness, and social comparison orientation: Interact and browse on social media, but don’t
compare. Cyberpsychology Behav. Soc. Netw. 2016, 19, 703–708.
4) Lup, K.; Trub, L.; Rosenthal, L. Instagram# instasad?: Exploring associations among instagram use, depressive symptoms, negative social
comparison, and strangers followed. Cyberpsychology Behav. Soc. Netw. 2015, 18, 247–252.
5) Dionísio, N.; Alves, F.; Ferreira, P.M.; Bessani, A. Cyberthreat detection from twitter using deep neural networks. In Proceedings of the 2019
International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, 14–19 July 2019; pp. 1–8.
6) Taherdoost, H.; Madanchian, M. Artificial Intelligence and Sentiment Analysis: A Review in Competitive Research. Computers 2023, 12, 37.
7) Jayatilake, S.M.D.A.C.; Ganegoda, G.U. Involvement of machine learning tools in healthcare decision making. J. Healthc. Eng. 2021, 2021,
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