Johan Bos

5.7k citations
143 papers · 3.0k · h-index 30

Impact in

    • Natural Language Processing Techniques
    • Topic Modeling
    • Speech and dialogue systems
    • Semantic Web and Ontologies
    • Text Readability and Simplification
    • Advanced Text Analysis Techniques
  • Health top 2%
    • Health disparities and outcomes

Papers in

Johan Bos

132 papers receiving 2.6k citations

Peers

Johan Bos
Comparison fields: 5 of 138
  • Artificial Intelligence 2.1k
  • Health 195
  • Language and Linguistics 146
  • Communication 79
  • Computer Vision and Pattern Recognition 223
Replace Jennifer Foster with:
Jennifer Foster Ireland
David Jurgens United States
Maarten Sap United States
Alexa T. McCray United States
Megha Agrawal India
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Citations per field
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Citations per year

Countries citing papers authored by Johan Bos

Since Specialization
Citations

This map shows the geographic impact of Johan Bos'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 Johan Bos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johan Bos more than expected).

Fields of papers citing papers by Johan Bos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Johan Bos. 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 Johan Bos. The network helps show where Johan Bos may publish in the future.

Co-authors

The 25 scholars most cited alongside Johan Bos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Johan Bos Line = papers co-authored together Johan Bos links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 143 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997176
2 2008168
3
Predicting the 2011 Dutch Senate Election Results with Twitter
2012151
4 2007149
5 2005133
6 2004129
7 1994125
8 199596
9
DIPPER : Description and formalisation of an information-state update dialogue system architecture
200372
10 199772
11 200167
12 201264
13 199660
14 200757
15 199552
16 201451
17
2013. Gamification for word sense labeling
201350
18 200341
19 199039
20 201736

About Johan Bos

Johan Bos is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Language and Linguistics, General Health Professions and Control and Systems Engineering, having authored 143 papers that have together received 3.0k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (91 papers), Topic Modeling (69 papers), Semantic Web and Ontologies (32 papers), Speech and dialogue systems (29 papers), Text Readability and Simplification (15 papers), Multi-Agent Systems and Negotiation (12 papers), Syntax, Semantics, Linguistic Variation (8 papers) and Multimodal Machine Learning Applications (8 papers). The work is most often cited by research in Artificial Intelligence (2.1k citations), Health (195 citations), Language and Linguistics (146 citations), Communication (79 citations) and Computer Vision and Pattern Recognition (223 citations). Johan Bos has collaborated with scholars based in Netherlands, United Kingdom and Italy. Frequent co-authors include Karien Stronks, H. van de Mheen, James Curran, Valerio Basile, Erik Tjong Kim Sang, Katja Markert, Kilian Evang, Johan P. Mackenbach, Noortje J. Venhuizen and Malvina Nissim. Their work appears in journals such as Language Resources and Evaluation, Computational Linguistics, International Journal of Epidemiology, IEEE Intelligent Systems and Avian Pathology.

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.

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