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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Validating Machine Learning Algorithms for Twitter Data Against Established Measures of Suicidality
Scott Braithwaite, Christophe Giraud-Carrier, Josh West, et al.
JMIR Mental Health (2016) Vol. 3, Iss. 2, pp. e21-e21
Open Access | Times Cited: 192

Showing 1-25 of 192 citing articles:

Methods in predictive techniques for mental health status on social media: a critical review
Stevie Chancellor, Munmun De Choudhury
npj Digital Medicine (2020) Vol. 3, Iss. 1
Open Access | Times Cited: 387
Predicting Anxiety, Depression and Stress in Modern Life using Machine Learning Algorithms
A. Priya, Shruti Garg, Neha Prerna Tigga
Procedia Computer Science (2020) Vol. 167, pp. 1258-1267
Open Access | Times Cited: 319
Researching Mental Health Disorders in the Era of Social Media: Systematic Review
Akkapon Wongkoblap, Miguel A. Vadillo, Vasa Ćurčin
Journal of Medical Internet Research (2017) Vol. 19, Iss. 6, pp. e228-e228
Open Access | Times Cited: 251
Are Mechanical Turk worker samples representative of health status and health behaviors in the U.S.?
Kelly Walters, Dimitri Christakis, Davene R. Wright
PLoS ONE (2018) Vol. 13, Iss. 6, pp. e0198835-e0198835
Open Access | Times Cited: 227
Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study
Qijin Cheng, Tim M. H. Li, Chi-Leung Kwok, et al.
Journal of Medical Internet Research (2017) Vol. 19, Iss. 7, pp. e243-e243
Open Access | Times Cited: 219
Infodemiology and Infoveillance: Scoping Review
Amaryllis Mavragani
Journal of Medical Internet Research (2020) Vol. 22, Iss. 4, pp. e16206-e16206
Open Access | Times Cited: 216
Detection of Suicide Ideation in Social Media Forums Using Deep Learning
Michael M. Tadesse, Hongfei Lin, Bo Xu, et al.
Algorithms (2019) Vol. 13, Iss. 1, pp. 7-7
Open Access | Times Cited: 184
The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review
Taylor A. Burke, Brooke A. Ammerman, Ross Jacobucci
Journal of Affective Disorders (2018) Vol. 245, pp. 869-884
Closed Access | Times Cited: 176
Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations
Rebecca A. Bernert, Amanda M. Hilberg, Ruth Melia, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 16, pp. 5929-5929
Open Access | Times Cited: 162
A machine learning approach predicts future risk to suicidal ideation from social media data
Arunima Roy, Katerina Nikolitch, Rachel McGinn, et al.
npj Digital Medicine (2020) Vol. 3, Iss. 1
Open Access | Times Cited: 161
Detecting and Analyzing Suicidal Ideation on Social Media Using Deep Learning and Machine Learning Models
Theyazn H. H. Aldhyani, Saleh Nagi Alsubari, Ali Saleh Alshebami, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 19, pp. 12635-12635
Open Access | Times Cited: 73
Depression Detection From Social Networks Data Based on Machine Learning and Deep Learning Techniques: An Interrogative Survey
Khan Md. Hasib, Md Rafiqul Islam, Shadman Sakib, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 10, Iss. 4, pp. 1568-1586
Closed Access | Times Cited: 58
Depression Sentiment Analysis using Machine Learning Techniques:A Review
Ashwani Kumar, Sunita Beniwal
International Journal of Computational and Experimental Science and Engineering (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Who is the "Human" in Human-Centered Machine Learning
Stevie Chancellor, Eric P. S. Baumer, Munmun De Choudhury
Proceedings of the ACM on Human-Computer Interaction (2019) Vol. 3, Iss. CSCW, pp. 1-32
Open Access | Times Cited: 144
Sentiment analysis of social networking sites (SNS) data using machine learning approach for the measurement of depression
Anees Ul Hassan, Jamil Hussain, Musarrat Hussain, et al.
2021 International Conference on Information and Communication Technology Convergence (ICTC) (2017), pp. 138-140
Closed Access | Times Cited: 141
Detection of suicide-related posts in Twitter data streams
Mia Johnson Vioulès, Bilel Moulahi, Jérôme Azé, et al.
IBM Journal of Research and Development (2018) Vol. 62, Iss. 1, pp. 7:1-7:12
Open Access | Times Cited: 138
Multi-class machine classification of suicide-related communication on Twitter
Pete Burnap, Gualtiero B. Colombo, Rosie Amery, et al.
Online Social Networks and Media (2017) Vol. 2, pp. 32-44
Open Access | Times Cited: 131
Detecting Suicidal Ideation on Forums: Proof-of-Concept Study
Ahmet Emre Aladağ, Serra Müderrisoğlu, Naz Berfu Akbaş, et al.
Journal of Medical Internet Research (2018) Vol. 20, Iss. 6, pp. e215-e215
Open Access | Times Cited: 123
Using Social Media for Mental Health Surveillance
Ruba Skaik, Diana Inkpen
ACM Computing Surveys (2020) Vol. 53, Iss. 6, pp. 1-31
Closed Access | Times Cited: 107
Methodological Gaps in Predicting Mental Health States from Social Media
Sindhu Kiranmai Ernala, Michael L. Birnbaum, Kristin Candan, et al.
(2019), pp. 1-16
Closed Access | Times Cited: 95
Toward Real-Time Infoveillance of Twitter Health Messages
Jason B. Colditz, Kar‐Hai Chu, Sherry Emery, et al.
American Journal of Public Health (2018) Vol. 108, Iss. 8, pp. 1009-1014
Open Access | Times Cited: 85
Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention
Lei Cao, Huijun Zhang, Ling Feng, et al.
(2019)
Open Access | Times Cited: 82
A Time-Aware Transformer Based Model for Suicide Ideation Detection on Social Media
Ramit Sawhney, Harshit Joshi, Saumya Gandhi, et al.
(2020)
Open Access | Times Cited: 82
Automatic detection of depression symptoms in twitter using multimodal analysis
Ramin Safa, Peyman Bayat, Leila Moghtader
The Journal of Supercomputing (2021) Vol. 78, Iss. 4, pp. 4709-4744
Open Access | Times Cited: 82
Smartphones and the Neuroscience of Mental Health
Claire M. Gillan, Robb B. Rutledge
Annual Review of Neuroscience (2021) Vol. 44, Iss. 1, pp. 129-151
Open Access | Times Cited: 81
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