Sentiment Analysis in Adolescents' Online Communication
An AI/ML Approach for Early Mental State Assessment
DOI:
https://doi.org/10.58445/rars.1595Keywords:
AI, Adolescents, online communicationAbstract
The surge in mental health issues among adolescents in the digital age, coupled with a lack of studies on individuals unaware of their mental status, propels our research. We emphasize the need for large-scale screening through natural language processing and machine learning, given the limitations of conventional methods in understanding the intricacies of online interactions.
Our project addresses the challenge of understanding adolescents' mental states by using machine learning to scrutinize text-based conversations on social media platforms. Focused on the critical adolescence period, our research captures intricacies overlooked by conventional methods. Integrating the AI model into a website enables real-time data input, providing dynamic analysis reflecting current trends.
Our project develops a software program using machine learning algorithms to train an AI model and construct a website for real-time analysis of text-based conversations among adolescents.
References
Guntuku,Sharath Chandra, Yaden, David B., Kern, Margaret L., Ungar, Lyle H., Eichstaedt Johannes C., “Detecting Depression and Mental Illness on Social Media: an Integrative Review.”, Science Direct, Dec. 2017, https://www.sciencedirect.com/science/article/abs/pii/S2352154617300384
Burdisso, Sergio G., “Using Text Classification to Estimate the Depression Level of Reddit Users: Semantic Scholar.” Journal of Computer Science and Technology, Semantic Scholar, 17 April 2021, https://www.semanticscholar.org/paper/Using-Text-Classification-to-Estimate-the-Level-of-Burdisso-Errecalde/e5d213b24b53f70d561fad6091ccecc5cda16553
Price, Hazel. Language of Mental Illness: Corpus Linguistics and the Construction of Mental Illness in the Press. Cambridge University Press, 2022.
Kassin, Saul, and Bull Kovera, Margaret. “Forensic Personality and Social Psychology.” The Oxford Handbook of Personality and Social Psychology, 2018, pp. 856–884., https://doi.org/10.1093/oxfordhb/9780190224837.013.34.
Tadesse, M. M., Lin, H. , Xu, B. and Yang,L., "Detection of Depression-Related Posts in Reddit Social Media Forum," in IEEE Access, 2021, vol. 7, pp. 44883-44893, 2019, doi:10.1109/ACCESS.2019.2909180
“Beck's Depression Inventory - Ismanet.org.” Beck's Depression Inventory PDF, https://www.ismanet.org/doctoryourspirit/pdfs/Beck-Depression-Inventory-BDI.pdf.
Additional Files
Posted
Categories
License
Copyright (c) 2024 Arushi Mani, Atharv Mahajan
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.