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 3
- Software Engineering Research 3
-
- Optical measurement and interference techniques 2
- Co-authors
- Christian Reuter (9 shared papers)Marc–André Kaufhold (5 shared papers)Marcel Keller (1 shared paper)Björn Buchhold (1 shared paper)Tobias Frey (1 shared paper)Tobias Beckmann (2 shared papers)Daniel Carl (2 shared papers)Milad Mirbabaie (1 shared paper)
- Journals
- International Journal of Machine Learning and Cybernetics (1 paper)Computers & Security (1 paper)Information Processing & Management (1 paper)Applied Optics (1 paper)ACM Transactions on Privacy and Security (1 paper)
- Partner nations
- Germany
In The Last Decade
Markus Bayer
11 papers receiving 409 citations
Markus Bayer's Hit Papers
Peers
Comparison fields: 5 of 90
- Artificial Intelligence 261
- Health Informatics 9
- Communication 40
- Information Systems 96
- Signal Processing 41
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 13 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 | 212 |
| 2 | 2022 | 73 | |
| 3 | 2019 | 61 | |
| 4 | 2019 | 23 | |
| 5 | 2024 | 22 | |
| 6 | 2023 | 12 | |
| 7 | 2021 | 12 | |
| 8 | 2024 | 4 | |
| 9 | 2019 | 3 | |
| 10 | 2021 | 3 | |
| 11 | 2018 | 1 |
About Markus Bayer
Markus Bayer is a scholar working on Information Systems, Computer Vision and Pattern Recognition, Artificial Intelligence, Sociology and Political Science and Atomic and Molecular Physics, and Optics, having authored 11 papers that have together received 426 indexed citations. Recurring topics across this work include Information and Cyber Security (3 papers), Software Engineering Research (3 papers), Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers), Image Processing Techniques and Applications (2 papers), Misinformation and Its Impacts (2 papers), Digital Holography and Microscopy (2 papers) and Optical measurement and interference techniques (2 papers). The work is most often cited by research in Artificial Intelligence (261 citations), Health Informatics (9 citations), Communication (40 citations), Information Systems (96 citations) and Signal Processing (41 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, Tobias Beckmann, Daniel Carl, Milad Mirbabaie, Jennifer Fromm and Stefan Stieglitz. Their work appears in journals such as International Journal of Machine Learning and Cybernetics, Computers & Security, Information Processing & Management, Applied Optics and ACM Transactions on Privacy and Security.
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.