Ugur Kursuncu
- Applied Psychology top 5%
- Social Psychology top 10%
- Mental Health via Writing 3
- Artificial Intelligence top 10%
- Topic Modeling 5
- Sentiment Analysis and Opinion Mining 2
- Health Information Management top 10%
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- Mobile Crowdsensing and Crowdsourcing 3
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- Spam and Phishing Detection 2
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- Terrorism, Counterterrorism, and Political Violence 2
- Digital Games and Media 1
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- Social Media and Politics 1
- Co-authors
- Manas GaurAmit ShethKrishnaprasad ThirunarayanAmanuel AlamboJyotishman PathakRamakanth KavuluruEyyüb Y. KıbışSerhat Simsek
- Journals
- IEEE Internet Computing (1 paper)JMIR Public Health and Surveillance (1 paper)Expert Systems with Applications (1 paper)
- Partner nations
- United StatesTürkiyeSpain
In The Last Decade
Ugur Kursuncu
13 papers receiving 350 citations
Peers
Comparison fields: 5 of 79
- Applied Psychology 87
- Social Psychology 172
- Artificial Intelligence 191
- Health Information Management 17
- Experimental and Cognitive Psychology 46
Countries citing papers authored by Ugur Kursuncu
This map shows the geographic impact of Ugur Kursuncu'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 Ugur Kursuncu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ugur Kursuncu more than expected).
Fields of papers citing papers by Ugur Kursuncu
This network shows the impact of papers produced by Ugur Kursuncu. 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 Ugur Kursuncu. The network helps show where Ugur Kursuncu may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Ugur Kursuncu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2022 | 0 | |
| 4 | 2020 | 2 | |
| 5 | 2020 | 10 | |
| 6 | 2019 | 31 | |
| 7 | 2019 | 118 | |
| 8 | 2019 | 32 | |
| 9 | 2019 | 39 | |
| 10 | 2019 | 51 | |
| 11 | 2018 | 55 | |
| 12 | Personalized Prediction of Suicide Risk for Web-based Intervention | 2018 | 1 |
| 13 | 2018 | 8 | |
| 14 | 2016 | 7 | |
| 15 | 2014 | 1 | |
| 16 | 2014 | 7 |
About Ugur Kursuncu
Ugur Kursuncu is a scholar working on Computer Science Applications, Artificial Intelligence, Information Systems, Social Psychology and Information Systems and Management, having authored 16 papers that have together received 362 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Mental Health via Writing (3 papers), Spam and Phishing Detection (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Terrorism, Counterterrorism, and Political Violence (2 papers), Social Media and Politics (1 paper) and Digital Games and Media (1 paper). The work is most often cited by research in Applied Psychology (87 citations), Social Psychology (172 citations), Artificial Intelligence (191 citations), Health Information Management (17 citations) and Experimental and Cognitive Psychology (46 citations). Ugur Kursuncu has collaborated with scholars based in United States, Türkiye and Spain. Frequent co-authors include Manas Gaur, Amit Sheth, Krishnaprasad Thirunarayan, Amanuel Alambo, Jyotishman Pathak, Ramakanth Kavuluru, Eyyüb Y. Kıbış, Serhat Simsek, Ali Dağ and Raminta Daniulaityte. Their work appears in journals such as IEEE Internet Computing, JMIR Public Health and Surveillance, Expert Systems with Applications, Proceedings of the ACM on Human-Computer Interaction and International Journal of Semantic Computing.
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.