Detection of Depression Signals from Social Media Data-Reference-Cited by-同舟云学术

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Detection of Depression Signals from Social Media Data

Published:2021 Issue: Volume: Page:191-209
ISSN:
Container-title:Smart Connected World
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Author:

Ahmad Tameem,Ahmed Sayyed Usman,Ahmad Nesar

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-76387-9_10

Reference46 articles.

1. Aalbers, G., McNally, R. J., Heeren, A., et al. (2019). Social media and depression symptoms: A network perspective. Journal of Experimental Psychology. General. https://doi.org/10.1037/xge0000528

2. Ahmad, T., & Ahmad, N. (2020). A simple guide to implement data retrieval through natural language database query interface (NLDQ) (pp. 37–41).

3. Ahmad, T., Ahmed, S. U., Ali, S. O., & Khan, R. (2020a). Beginning with exploring the way for rumor free social networks. Journal of Statistics & Management Systems, 23, 231–238. https://doi.org/10.1080/09720510.2020.1724623.

4. Ahmad, T., Anwar, M. A., & Haque, M. (2020b). Machine learning techniques for intrusion detection. In B. B. Gupta (National Institute of Technology, Kurukshetra, India) & Srivathsan Srinivasagopalan (AT&T U) (Eds.), Handbook of research on intrusion detection systems (pp. 47–65). IGI Global.

5. Akhtar, N., Javed, H., & Ahmad, T. (2019). Hierarchical summarization of text documents using topic modeling and formal concept analysis. In Advances in Intelligent Systems and Computing.

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