A Large-Scale Social Media Corpus for the Detection of Youth Depression (Project Note)

Author:

Zaghouani Wajdi

Publisher

Elsevier BV

Subject

General Engineering

Reference17 articles.

1. Alcohol use and risky sexual behavior among college students and youth: evaluating the evidence;Cooper;Journal of Studies on Alcohol, supplement,2002

2. Zafarani, R., Liu, H. (2013). Connecting Users across Social Media Sites: A Behavioral-Modeling Approach, In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 41-49). ACM.

3. Social Media Mining: An Introduction;Zafarani,2014

4. The secret life of pronouns;Pennebaker James;New Scientist,2011

5. The development and psychometric properties of LIWC2007;Pennebaker James,2007

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1. Constructing Depression Prediction Model using ChatGPT and Machine Learning Algorithms;2023 12th International Conference on Awareness Science and Technology (iCAST);2023-11-09

2. Depression Detection Based on Features of Depressive Behaviour Through Social Media Analytic: A Systematic Literature Review;Lecture Notes in Electrical Engineering;2023

3. Depression Detection on Malay Dialects Using GPT-3;2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES);2022-12-07

4. An Analysis and Detection of Misleading Information on Social Media Using Machine Learning Techniques;Advances in Electronic Government, Digital Divide, and Regional Development;2022-06-10

5. Depression Detection on Social Media;2022 1st International Conference on Informatics (ICI);2022-04-14

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