Gabriele Pergola
- Artificial Intelligence top 5%
- Topic Modeling 13
- Advanced Text Analysis Techniques 7
- Sentiment Analysis and Opinion Mining 5
- Natural Language Processing Techniques 5
- General Social Sciences top 10%
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- Biomedical Text Mining and Ontologies 3
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- Multimodal Machine Learning Applications 3
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- Computational Drug Discovery Methods 2
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- Pharmacovigilance and Adverse Drug Reactions 2
- Journals
- Computers in Biology and Medicine (1 paper)Information Processing & Management (1 paper)Warwick Research Archive Portal (University of Warwick) (4 papers)
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Gabriele Pergola
19 papers receiving 240 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 216
- Experimental and Cognitive Psychology 62
- General Social Sciences 10
- Health Informatics 2
- Signal Processing 12
Countries citing papers authored by Gabriele Pergola
This map shows the geographic impact of Gabriele Pergola'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 Gabriele Pergola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriele Pergola more than expected).
Fields of papers citing papers by Gabriele Pergola
This network shows the impact of papers produced by Gabriele Pergola. 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 Gabriele Pergola. The network helps show where Gabriele Pergola may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gabriele Pergola, 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 | 3 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 6 | |
| 8 | 2022 | 9 | |
| 9 | 2022 | 3 | |
| 10 | 2022 | 5 | |
| 11 | 2021 | 11 | |
| 12 | 2021 | 29 | |
| 13 | 2021 | 90 | |
| 14 | 2021 | 1 | |
| 15 | 2021 | 10 | |
| 16 | 2020 | 6 | |
| 17 | 2019 | 23 | |
| 18 | 2019 | 41 | |
| 19 | 2016 | 1 | |
| 20 | 2016 | 1 |
About Gabriele Pergola
Gabriele Pergola is a scholar working on Health Informatics, Toxicology, Artificial Intelligence, General Social Sciences and Health Information Management, having authored 21 papers that have together received 245 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Advanced Text Analysis Techniques (7 papers), Sentiment Analysis and Opinion Mining (5 papers), Natural Language Processing Techniques (5 papers), Biomedical Text Mining and Ontologies (3 papers), Multimodal Machine Learning Applications (3 papers), Computational Drug Discovery Methods (2 papers) and Pharmacovigilance and Adverse Drug Reactions (2 papers). The work is most often cited by research in Artificial Intelligence (216 citations), Experimental and Cognitive Psychology (62 citations), General Social Sciences (10 citations), Health Informatics (2 citations) and Signal Processing (12 citations). Gabriele Pergola has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Yulan He, Lin Gui, Deyu Zhou, Lixing Zhu, Yu Zhou, Ruifeng Xu, Byron Wallace, Elena Kochkina, Jiazheng Li and Maria Liakata. Their work appears in journals such as Computers in Biology and Medicine, Information Processing & Management, Warwick Research Archive Portal (University of Warwick), Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies and Proceedings of the AAAI Conference on Artificial Intelligence.
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.