Bastian Haarmann
Impact in
- Health Informatics top 10%
- Communication top 10%
- Social Media and Politics
- Media Studies and Communication
Papers in
-
- Semantic Web and Ontologies 4
- Topic Modeling 2
- Natural Language Processing Techniques 1
- Bayesian Modeling and Causal Inference 1
-
- Web Data Mining and Analysis 1
- Co-authors
- Mario Haim (1 shared paper)Andreas Graefe (1 shared paper)Hans‐Bernd Brosius (1 shared paper)Jürgen Ziegler (1 shared paper)Claus Stadler (1 shared paper)U. Schade (1 shared paper)Jens Lehmann (1 shared paper)Michael R. Hieb (1 shared paper)
- Journals
- Journalism (1 paper)Fraunhofer-Publica (Fraunhofer-Gesellschaft) (2 papers)Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (1 paper)Zenodo (CERN European Organization for Nuclear Research) (2 papers)
- Partner nations
- GermanyUnited StatesGreece
In The Last Decade
Bastian Haarmann
6 papers receiving 187 citations
Peers
Comparison fields: 5 of 48
- Health Informatics 12
- Communication 55
- Safety Research 43
- General Social Sciences 14
- Artificial Intelligence 87
Countries citing papers authored by Bastian Haarmann
This map shows the geographic impact of Bastian Haarmann'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 Bastian Haarmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bastian Haarmann more than expected).
Fields of papers citing papers by Bastian Haarmann
This network shows the impact of papers produced by Bastian Haarmann. 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 Bastian Haarmann. The network helps show where Bastian Haarmann may publish in the future.
Co-authors
The 8 scholars most cited alongside Bastian Haarmann, 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 | 2016 | 193 | |
| 2 | Automatic generation of large causal Bayesian networks from user oriented models | 2011 | 2 |
| 3 | 2017 | 2 | |
| 4 | 2015 | 1 | |
| 5 | Ontology on demand | 2014 | 1 |
| 6 | 2011 | 1 | |
| 7 | 2015 | 1 |
About Bastian Haarmann
Bastian Haarmann is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Communication and Sociology and Political Science, having authored 7 papers that have together received 201 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (4 papers), Topic Modeling (2 papers), Scientific Computing and Data Management (1 paper), Web Data Mining and Analysis (1 paper), Simulation Techniques and Applications (1 paper), Natural Language Processing Techniques (1 paper), Bayesian Modeling and Causal Inference (1 paper) and Software Engineering and Design Patterns (1 paper). The work is most often cited by research in Health Informatics (12 citations), Communication (55 citations), Safety Research (43 citations), General Social Sciences (14 citations) and Artificial Intelligence (87 citations). Bastian Haarmann has collaborated with scholars based in Germany, United States and Greece. Frequent co-authors include Mario Haim, Andreas Graefe, Hans‐Bernd Brosius, Jürgen Ziegler, Claus Stadler, U. Schade, Jens Lehmann and Michael R. Hieb. Their work appears in journals such as Journalism, Fraunhofer-Publica (Fraunhofer-Gesellschaft), Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) and Zenodo (CERN European Organization for Nuclear Research).
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.