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:
Supervised machine learning models for depression sentiment analysis
Ibidun Christiana Obagbuwa, Samantha Danster, Onil Colin Chibaya
Frontiers in Artificial Intelligence (2023) Vol. 6
Open Access | Times Cited: 12
Ibidun Christiana Obagbuwa, Samantha Danster, Onil Colin Chibaya
Frontiers in Artificial Intelligence (2023) Vol. 6
Open Access | Times Cited: 12
Showing 12 citing articles:
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
Ashwani Kumar, Sunita Beniwal
International Journal of Computational and Experimental Science and Engineering (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 2
DepressionEmo: A novel dataset for multilabel classification of depression emotions
Abu Bakar Siddiqur Rahman, Hoang-Thang Ta, Lotfollah Najjar, et al.
Journal of Affective Disorders (2024) Vol. 366, pp. 445-458
Open Access | Times Cited: 5
Abu Bakar Siddiqur Rahman, Hoang-Thang Ta, Lotfollah Najjar, et al.
Journal of Affective Disorders (2024) Vol. 366, pp. 445-458
Open Access | Times Cited: 5
Electrophysiological biomarkers based on CISANET characterize illness severity and suicidal ideation among patients with major depressive disorder
Yuchen Liang, Xuelin Gu, Yifan Shi, et al.
Medical & Biological Engineering & Computing (2025)
Closed Access
Yuchen Liang, Xuelin Gu, Yifan Shi, et al.
Medical & Biological Engineering & Computing (2025)
Closed Access
Analysis of Depressed Patients’ Sentiments Towards Treatment: AI Approach for Healthcare Professionals
Maria El-Badaoui, Noreddine Gherabi, Fatima Qanouni
Lecture notes in networks and systems (2025), pp. 64-71
Closed Access
Maria El-Badaoui, Noreddine Gherabi, Fatima Qanouni
Lecture notes in networks and systems (2025), pp. 64-71
Closed Access
“Uncovering Responses”: A Sentiment Analysis Approach to Racial Violence Among Black Parents in Missouri
Ivy N. Smith, Edward H. Sargent, JaNiene E. Peoples, et al.
SAGE Open (2025) Vol. 15, Iss. 2
Open Access
Ivy N. Smith, Edward H. Sargent, JaNiene E. Peoples, et al.
SAGE Open (2025) Vol. 15, Iss. 2
Open Access
Patient Voices in Dialysis Care: Sentiment Analysis and Topic Modeling Study of Social Media Discourse
Ravi Shankar, Qian Xu, Anjali Bundele
Journal of Medical Internet Research (2025) Vol. 27, pp. e70128-e70128
Open Access
Ravi Shankar, Qian Xu, Anjali Bundele
Journal of Medical Internet Research (2025) Vol. 27, pp. e70128-e70128
Open Access
An End-to-End framework for extracting observable cues of depression from diary recordings
Izidor Mlakar, Umut Ariöz, Urška Smrke, et al.
Expert Systems with Applications (2024) Vol. 257, pp. 125025-125025
Open Access | Times Cited: 3
Izidor Mlakar, Umut Ariöz, Urška Smrke, et al.
Expert Systems with Applications (2024) Vol. 257, pp. 125025-125025
Open Access | Times Cited: 3
Comparative analysis of machine learning versus traditional method for early detection of parental depression symptoms in the NICU
Fatima Sadjadpour, Niyousha Hosseinichimeh, Vida Abedi, et al.
Frontiers in Public Health (2024) Vol. 12
Open Access
Fatima Sadjadpour, Niyousha Hosseinichimeh, Vida Abedi, et al.
Frontiers in Public Health (2024) Vol. 12
Open Access
Prediction of Depression Severity and Personalised Risk Factors Using Machine Learning on Multimodal Data
Adefemi Ayodele, Adedotun Adetunla, Esther T. Akinlabi
International Journal of Online and Biomedical Engineering (iJOE) (2024) Vol. 20, Iss. 09, pp. 130-143
Open Access
Adefemi Ayodele, Adedotun Adetunla, Esther T. Akinlabi
International Journal of Online and Biomedical Engineering (iJOE) (2024) Vol. 20, Iss. 09, pp. 130-143
Open Access
Sentiment Analysis and Machine Learning Approaches in Covid-19 Tweets
Ibidun Christiana Obagbuwa, Onil Colin Chibaya
(2024), pp. 1-7
Closed Access
Ibidun Christiana Obagbuwa, Onil Colin Chibaya
(2024), pp. 1-7
Closed Access
Advanced Comparative Analysis of Machine Learning and Transformer Models for Depression and Suicide Detection in Social Media Texts
Biodoumoye George Bokolo, Qingzhong Liu
Electronics (2024) Vol. 13, Iss. 20, pp. 3980-3980
Open Access
Biodoumoye George Bokolo, Qingzhong Liu
Electronics (2024) Vol. 13, Iss. 20, pp. 3980-3980
Open Access
Patient Voices in Dialysis Care: Sentiment Analysis and Topic Modeling Study of Social Media Discourse (Preprint)
Ravi Shankar, Qian Xu, Anjali Bundele
(2024)
Closed Access
Ravi Shankar, Qian Xu, Anjali Bundele
(2024)
Closed Access
Depression Predicting Model For Social Media User’s Emotions Using Deep Learning Methods
P. M. Jadhav, Sonia Sonia, Ashish Kulkarni
Journal Of Advanced Zoology (2023)
Open Access
P. M. Jadhav, Sonia Sonia, Ashish Kulkarni
Journal Of Advanced Zoology (2023)
Open Access
Depression Predicting Model For Social Media User’s Emotions Using Deep Learning Methods
P. M. Jadhav, Sonia Sonia, Ashish Kulkarni
Journal Of Advanced Zoology (2023)
Open Access
P. M. Jadhav, Sonia Sonia, Ashish Kulkarni
Journal Of Advanced Zoology (2023)
Open Access
An Empirical and Statistical Analysis of Regression Algorithms Used for Mental Fitness Prediction
Vibha Jamadagni, Darshana Vedavalli, Surbhi Priyadarshi, et al.
2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) (2023), pp. 805-810
Closed Access
Vibha Jamadagni, Darshana Vedavalli, Surbhi Priyadarshi, et al.
2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) (2023), pp. 805-810
Closed Access
