Markus Bayer
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Sentiment Analysis and Opinion Mining
- Text and Document Classification Technologies
Papers in
-
- Information and Cyber Security 4
- Software Engineering Research 3
- Digital and Cyber Forensics 2
-
- Topic Modeling 5
- Natural Language Processing Techniques 4
- Co-authors
- Christian Reuter (12 shared papers)Marc–André Kaufhold (7 shared papers)Marcel Keller (1 shared paper)Björn Buchhold (1 shared paper)Tobias Frey (1 shared paper)Markus Fratz (2 shared papers)Tobias Beckmann (2 shared papers)Daniel Carl (2 shared papers)
- Journals
- International Journal of Machine Learning and Cybernetics (1 paper)Applied Optics (1 paper)Information Processing & Management (1 paper)Transactions of the Association for Computational Linguistics (1 paper)ACM Computing Surveys (1 paper)
- Partner nations
- Germany
In The Last Decade
Markus Bayer
15 papers receiving 546 citations
Markus Bayer's Hit Papers
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 337
- Health Informatics 10
- Communication 50
- Information Systems 126
- Signal Processing 56
Countries citing papers authored by Markus Bayer
This map shows the geographic impact of Markus Bayer'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 Markus Bayer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Bayer more than expected).
Fields of papers citing papers by Markus Bayer
This network shows the impact of papers produced by Markus Bayer. 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 Markus Bayer. The network helps show where Markus Bayer may publish in the future.
Co-authors
The 17 scholars most cited alongside Markus Bayer, 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 | A Survey on Data Augmentation for Text Classification Hit paper breakdown → | 2022 | 261 |
| 2 | 2022 | 96 | |
| 3 | 2019 | 75 | |
| 4 | 2024 | 31 | |
| 5 | 2019 | 27 | |
| 6 | 2023 | 17 | |
| 7 | 2021 | 16 | |
| 8 | 2021 | 13 | |
| 9 | 2024 | 12 | |
| 10 | 2021 | 6 | |
| 11 | 2019 | 3 | |
| 12 | 2021 | 3 | |
| 13 | 2018 | 2 | |
| 14 | 2025 | 1 | |
| 15 | 2025 | 1 | |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 | |
| 19 | 2026 | 0 | |
| 20 | 2026 | 0 |
About Markus Bayer
Markus Bayer is a scholar working on Information Systems, Artificial Intelligence, Communication, Sociology and Political Science and Media Technology, having authored 20 papers that have together received 564 indexed citations. Recurring topics across this work include Misinformation and Its Impacts (5 papers), Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers), Information and Cyber Security (4 papers), Software Engineering Research (3 papers), Digital Holography and Microscopy (2 papers), Public Relations and Crisis Communication (2 papers) and Digital and Cyber Forensics (2 papers). The work is most often cited by research in Artificial Intelligence (337 citations), Health Informatics (10 citations), Communication (50 citations), Information Systems (126 citations) and Signal Processing (56 citations). Markus Bayer has collaborated with scholars based in Germany. Frequent co-authors include Christian Reuter, Marc–André Kaufhold, Marcel Keller, Björn Buchhold, Tobias Frey, Markus Fratz, Tobias Beckmann, Daniel Carl, Stefan Guthe and Daniel M. Hartung. Their work appears in journals such as International Journal of Machine Learning and Cybernetics, Applied Optics, Information Processing & Management, Transactions of the Association for Computational Linguistics and ACM Computing Surveys.
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.