Benjamin Müller
Impact in
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- Natural Language Processing Techniques
- Topic Modeling
- Text Readability and Simplification
Papers in
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- Natural Language Processing Techniques 3
- Topic Modeling 3
- Text Readability and Simplification 1
- Semantic Web and Ontologies 1
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- Migration, Refugees, and Integration 1
- Co-authors
- Beat P. Müller‐Stich (1 shared paper)Franziska Mathis-Ullrich (1 shared paper)Martin Wagner (1 shared paper)Sebastian Olbrich (1 shared paper)Rob van der Goot (1 shared paper)Arkaitz Zubiaga (1 shared paper)Tommaso Caselli (1 shared paper)Nikola Ljubešić (1 shared paper)
- Journals
- Big Data & Society (1 paper)SHILAP Revista de lepidopterología (1 paper)Data Archiving and Networked Services (DANS) (1 paper)MADOC (University of Mannheim) (2 papers)
In The Last Decade
Benjamin Müller
7 papers receiving 51 citations
Peers
Comparison fields: 5 of 29
- Health Informatics 4
- Artificial Intelligence 22
- Computer Vision and Pattern Recognition 12
- Biomedical Engineering 18
- Management Information Systems 3
Countries citing papers authored by Benjamin Müller
This map shows the geographic impact of Benjamin Müller'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 Benjamin Müller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Müller more than expected).
Fields of papers citing papers by Benjamin Müller
This network shows the impact of papers produced by Benjamin Müller. 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 Benjamin Müller. The network helps show where Benjamin Müller may publish in the future.
Co-authors
The 25 scholars most cited alongside Benjamin Müller, 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 | 2020 | 27 | |
| 2 | 2021 | 18 | |
| 3 | The Artifact’s Theory – A Grounded Theory Perspective on Design Science Research | 2011 | 4 |
| 4 | 2023 | 4 | |
| 5 | Leaking confidential information by non-malicious user behavior in Enterprise Systems - an empirical study | 2011 | 1 |
| 6 | Technology and the Separation of Work and Non-Work Life: Two Sides of a Coin? | 2011 | 1 |
| 7 | 2025 | 1 | |
| 8 | 2025 | 0 |
About Benjamin Müller
Benjamin Müller is a scholar working on Artificial Intelligence, Sociology and Political Science, Information Systems, Communication and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 56 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (3 papers), Topic Modeling (3 papers), Text Readability and Simplification (1 paper), Semantic Web and Ontologies (1 paper), Migration, Refugees, and Integration (1 paper), Open Source Software Innovations (1 paper), Information and Cyber Security (1 paper) and COVID-19 Digital Contact Tracing (1 paper). The work is most often cited by research in Health Informatics (4 citations), Artificial Intelligence (22 citations), Computer Vision and Pattern Recognition (12 citations), Biomedical Engineering (18 citations) and Management Information Systems (3 citations). Benjamin Müller has collaborated with scholars based in Germany, France and Australia. Frequent co-authors include Beat P. Müller‐Stich, Franziska Mathis-Ullrich, Martin Wagner, Sebastian Olbrich, Rob van der Goot, Arkaitz Zubiaga, Tommaso Caselli, Nikola Ljubešić, Rahmad Mahendra and Barbara Plank. Their work appears in journals such as Big Data & Society, SHILAP Revista de lepidopterología, Data Archiving and Networked Services (DANS) and MADOC (University of Mannheim).
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.