Research Paper Reading
1.Predicting Depression via Social Media
De Choudhury, M., Gamon, M., Counts, S., & Horvitz, E. (2013). Predicting Depression via Social Media. Proceedings of the International AAAI Conferenc
2.Quantifying Mental Health Signals in Twitter
Glen Coppersmith, Mark Dredze, and Craig Harman. 2014. Quantifying Mental Health Signals in Twitter. In Proceedings of the Workshop on Computational L
3.Methodological Gaps in Predicting Mental Health States from Social Media: Triangulating Diagnostic Signals
> Sindhu Kiranmai Ernala, Michael L. Birnbaum, Kristin A. Candan, Asra F. Rizvi, William A. Sterling, John M. Kane, and Munmun De Choudhury. 2019. M
4.The Language of Social Support in Social Media and Its Effect on Suicidal Ideation Risk
De Choudhury, M., & Kıcıman, E. (2017). The Language of Social Support in Social Media and its Effect on Suicidal Ideation Risk. Proceedings of the ..
5.Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media
De Choudhury, M., Kiciman, E., Dredze, M., Coppersmith, G., & Kumar, M. (2016). Discovering Shifts to Suicidal Ideation from Mental Health Content in
6.Methods in predictive techniques for mental health status on social media: a critical review
Chancellor, S., & De Choudhury, M. (2020). Methods in predictive techniques for mental health status on social media: A critical review. Npj Digital M
7.A machine learning approach predicts future risk to suicidal ideation from social media data
Roy, A., Nikolitch, K., McGinn, R., Jinah, S., Klement, W., & Kaminsky, Z. A. (2020). A machine learning approach predicts future risk to suicidal ide
8.Deep neural networks detect suicide risk from textual Facebook posts
Ophir, Y., Tikochinski, R., Asterhan, C. S., Sisso, I., & Reichart, R. (2020). Deep neural networks detect suicide risk from textual Facebook posts. S