Manas Gaur
Impact in
- Applied Psychology top 5%
- Digital Mental Health Interventions
- Health Informatics top 5%
Papers in
-
- Topic Modeling 17
- Machine Learning in Healthcare 12
- Explainable Artificial Intelligence (XAI) 5
- Sentiment Analysis and Opinion Mining 4
-
- Mental Health via Writing 13
- Co-authors
- Amit Sheth (30 shared papers)Ugur Kursuncu (10 shared papers)Krishnaprasad Thirunarayan (13 shared papers)Amanuel Alambo (8 shared papers)Jyotishman Pathak (6 shared papers)Amélie Gyrard (4 shared papers)Ramakanth Kavuluru (2 shared papers)Saeedeh Shekarpour (2 shared papers)
- Journals
- IEEE Internet Computing (4 papers)JMIR Public Health and Surveillance (2 papers)International Journal of Infectious Diseases (1 paper)AI Magazine (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Manas Gaur
49 papers receiving 759 citations
Peers
Comparison fields: 5 of 98
- Applied Psychology 134
- Health Informatics 21
- Artificial Intelligence 394
- Social Psychology 238
- Experimental and Cognitive Psychology 68
Countries citing papers authored by Manas Gaur
This map shows the geographic impact of Manas Gaur's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Manas Gaur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manas Gaur more than expected).
Fields of papers citing papers by Manas Gaur
This network shows the impact of papers produced by Manas Gaur. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Manas Gaur. The network helps show where Manas Gaur may publish in the future.
Co-authors
The 25 scholars most cited alongside Manas Gaur, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 121 | |
| 2 | 2018 | 59 | |
| 3 | 2023 | 53 | |
| 4 | 2019 | 40 | |
| 5 | 2019 | 34 | |
| 6 | 2019 | 33 | |
| 7 | 2022 | 32 | |
| 8 | 2019 | 31 | |
| 9 | 2018 | 30 | |
| 10 | 2022 | 25 | |
| 11 | 2023 | 23 | |
| 12 | 2021 | 23 | |
| 13 | 2020 | 23 | |
| 14 | 2021 | 22 | |
| 15 | Personalized Health Knowledge Graph. | 2018 | 22 |
| 16 | 2022 | 19 | |
| 17 | 2023 | 19 | |
| 18 | 2022 | 16 | |
| 19 | 2022 | 14 | |
| 20 | 2023 | 14 |
About Manas Gaur
Manas Gaur is a scholar working on Artificial Intelligence, Social Psychology, Information Systems, Applied Psychology and Molecular Biology, having authored 55 papers that have together received 777 indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Mental Health via Writing (13 papers), Machine Learning in Healthcare (12 papers), Digital Mental Health Interventions (6 papers), Mental Health Research Topics (5 papers), Explainable Artificial Intelligence (XAI) (5 papers), COVID-19 epidemiological studies (4 papers) and Sentiment Analysis and Opinion Mining (4 papers). The work is most often cited by research in Applied Psychology (134 citations), Health Informatics (21 citations), Artificial Intelligence (394 citations), Social Psychology (238 citations) and Experimental and Cognitive Psychology (68 citations). Manas Gaur has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Amit Sheth, Ugur Kursuncu, Krishnaprasad Thirunarayan, Amanuel Alambo, Jyotishman Pathak, Amélie Gyrard, Ramakanth Kavuluru, Saeedeh Shekarpour, Kalpa Gunaratna and Raminta Daniulaityte. Their work appears in journals such as IEEE Internet Computing, JMIR Public Health and Surveillance, International Journal of Infectious Diseases, AI Magazine and PLoS ONE.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.