Jan Kocoń
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 2%
- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Natural Language Processing Techniques
- Hate Speech and Cyberbullying Detection
- Advanced Text Analysis Techniques
- AI in Service Interactions
Papers in
-
- Topic Modeling 42
- Natural Language Processing Techniques 30
- Sentiment Analysis and Opinion Mining 28
- Advanced Text Analysis Techniques 11
- Hate Speech and Cyberbullying Detection 9
- Semantic Web and Ontologies 9
- Authorship Attribution and Profiling 7
- Speech and dialogue systems 5
- Co-authors
- Piotr Miłkowski (24 shared papers)Przemysław Kazienko (24 shared papers)Kamil Kanclerz (13 shared papers)Marcin Gruza (15 shared papers)Maciej Piasecki (16 shared papers)Arkadiusz Janz (11 shared papers)Julita Bielaniewicz (8 shared papers)Marcin Oleksy (10 shared papers)
In The Last Decade
Jan Kocoń
62 papers receiving 1.1k citations
Jan Kocoń's Hit Papers
Peers
Comparison fields: 5 of 100
- Health Informatics 152
- Artificial Intelligence 846
- General Social Sciences 31
- Computer Science Applications 42
- Safety Research 38
Countries citing papers authored by Jan Kocoń
This map shows the geographic impact of Jan Kocoń'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 Jan Kocoń with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Kocoń more than expected).
Fields of papers citing papers by Jan Kocoń
This network shows the impact of papers produced by Jan Kocoń. 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 Jan Kocoń. The network helps show where Jan Kocoń may publish in the future.
Co-authors
The 25 scholars most cited alongside Jan Kocoń, 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 75 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | ChatGPT: Jack of all trades, master of none Hit paper breakdown → | 2023 | 447 |
| 2 | 2021 | 78 | |
| 3 | 2019 | 38 | |
| 4 | 2020 | 36 | |
| 5 | 2023 | 34 | |
| 6 | 2013 | 32 | |
| 7 | 2021 | 29 | |
| 8 | 2021 | 28 | |
| 9 | 2023 | 25 | |
| 10 | 2021 | 23 | |
| 11 | 2022 | 20 | |
| 12 | 2022 | 18 | |
| 13 | 2021 | 18 | |
| 14 | 2023 | 17 | |
| 15 | 2021 | 15 | |
| 16 | 2019 | 14 | |
| 17 | 2021 | 13 | |
| 18 | 2024 | 12 | |
| 19 | 2012 | 11 | |
| 20 | 2023 | 11 |
About Jan Kocoń
Jan Kocoń is a scholar working on Artificial Intelligence, Sociology and Political Science, Social Psychology, Information Systems and Computer Vision and Pattern Recognition, having authored 75 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (42 papers), Natural Language Processing Techniques (30 papers), Sentiment Analysis and Opinion Mining (28 papers), Advanced Text Analysis Techniques (11 papers), Hate Speech and Cyberbullying Detection (9 papers), Semantic Web and Ontologies (9 papers), Authorship Attribution and Profiling (7 papers) and Speech and dialogue systems (5 papers). The work is most often cited by research in Health Informatics (152 citations), Artificial Intelligence (846 citations), General Social Sciences (31 citations), Computer Science Applications (42 citations) and Safety Research (38 citations). Jan Kocoń has collaborated with scholars based in Poland, Canada and China. Frequent co-authors include Piotr Miłkowski, Przemysław Kazienko, Kamil Kanclerz, Marcin Gruza, Maciej Piasecki, Arkadiusz Janz, Julita Bielaniewicz, Marcin Oleksy, Michał Marcińczuk and Bartłomiej Koptyra. Their work appears in journals such as Information Fusion, Language Resources and Evaluation, Cognitive Studies | Études cognitives, Information Processing & Management and Lecture notes in computer science.
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.