Michael Färber
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Semantic Web and Ontologies
- Advanced Graph Neural Networks
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
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- Data Quality and Management
Papers in
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- Topic Modeling 38
- Natural Language Processing Techniques 25
- Semantic Web and Ontologies 23
- Advanced Text Analysis Techniques 13
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- Web Data Mining and Analysis 8
- Co-authors
- Achim Rettinger (14 shared papers)Adam Jatowt (17 shared papers)Dimitri Kténas (3 shared papers)Kilian Roth (1 shared paper)Robin Gerzaguet (1 shared paper)Miquel Payaró (2 shared papers)Leonardo Gomes Baltar (1 shared paper)Jean‐Baptiste Doré (1 shared paper)
In The Last Decade
Michael Färber
91 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 611
- Management Science and Operations Research 184
- Information Systems 267
- Information Systems and Management 69
- Computer Networks and Communications 185
Countries citing papers authored by Michael Färber
This map shows the geographic impact of Michael Färber'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 Michael Färber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Färber more than expected).
Fields of papers citing papers by Michael Färber
This network shows the impact of papers produced by Michael Färber. 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 Michael Färber. The network helps show where Michael Färber may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Färber, 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 101 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 239 | |
| 2 | 2017 | 168 | |
| 3 | 2019 | 90 | |
| 4 | 2020 | 64 | |
| 5 | 2012 | 51 | |
| 6 | 2020 | 28 | |
| 7 | 2022 | 26 | |
| 8 | Annotating and Analyzing Biased Sentences in News Articles using Crowdsourcing | 2020 | 23 |
| 9 | 2021 | 20 | |
| 10 | 2018 | 19 | |
| 11 | 2020 | 18 | |
| 12 | 2007 | 13 | |
| 13 | 2023 | 12 | |
| 14 | 2021 | 12 | |
| 15 | 2020 | 12 | |
| 16 | 2018 | 11 | |
| 17 | 2016 | 11 | |
| 18 | 2018 | 11 | |
| 19 | 2021 | 10 | |
| 20 | 2021 | 10 |
About Michael Färber
Michael Färber is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Molecular Biology and Electrical and Electronic Engineering, having authored 101 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (38 papers), Natural Language Processing Techniques (25 papers), Semantic Web and Ontologies (23 papers), Advanced Text Analysis Techniques (13 papers), Biomedical Text Mining and Ontologies (13 papers), Data Quality and Management (12 papers), Web Data Mining and Analysis (8 papers) and Scientific Computing and Data Management (8 papers). The work is most often cited by research in Artificial Intelligence (611 citations), Management Science and Operations Research (184 citations), Information Systems (267 citations), Information Systems and Management (69 citations) and Computer Networks and Communications (185 citations). Michael Färber has collaborated with scholars based in Germany, Japan and Austria. Frequent co-authors include Achim Rettinger, Adam Jatowt, Dimitri Kténas, Kilian Roth, Robin Gerzaguet, Miquel Payaró, Leonardo Gomes Baltar, Jean‐Baptiste Doré, Oriol Font-Bach and Vincent Berg. Their work appears in journals such as Scientometrics, Language Resources and Evaluation, Lecture notes in computer science, Quantitative Science Studies and Journal of Optical Communications and Networking.
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.