Kim Schouten
- Artificial Intelligence top 2%
- Information Systems top 5%
- Sociology and Political Science top 10%
- Management Science and Operations Research top 10%
- Statistical and Nonlinear Physics
- Co-authors
- Flavius FrăsincarRommert DekkerFrederik HogenboomErik‐Hans KlijnAlexander HogenboomFranciska de JongAnnelies de KleinJ.C. Reubi
- Topics
- Advanced Text Analysis Techniques (14 papers)Sentiment Analysis and Opinion Mining (13 papers)Text and Document Classification Technologies (6 papers)
- Journals
- International Journal of CancerExpert Systems with ApplicationsIEEE Transactions on Cybernetics
- Partner nations
- NetherlandsAustriaGermany
In The Last Decade
Kim Schouten
22 papers receiving 838 citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Artificial Intelligence 748
- Information Systems 180
- Sociology and Political Science 129
- Management Science and Operations Research 58
- Statistical and Nonlinear Physics 32
Countries citing papers authored by Kim Schouten
This map shows the geographic impact of Kim Schouten'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 Kim Schouten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kim Schouten more than expected).
Fields of papers citing papers by Kim Schouten
This network shows the impact of papers produced by Kim Schouten. 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 Kim Schouten. The network helps show where Kim Schouten may publish in the future.
Co-authorship network of co-authors of Kim Schouten
This figure shows the co-authorship network connecting the top 25 collaborators of Kim Schouten. A scholar is included among the top collaborators of Kim Schouten based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kim Schouten. Kim Schouten is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 8 | |
| 6 | 26 | |
| 7 | 14 | |
| 8 | 23 | |
| 9 | 111 | |
| 10 | 5 | |
| 11 | 1 | |
| 12 | Survey on Aspect-Level Sentiment Analysisbreakdown → | 548 |
| 13 | 9 | |
| 14 | Linked data in action: Personalized museum tours on mobile devices | 5 |
| 15 | 9 | |
| 16 | 6 | |
| 17 | Searching and hyperlinking using word importance segment boundaries in MediaEval 2013 | 2 |
| 18 | 5 | |
| 19 | 24 | |
| 20 | 19 |
About Kim Schouten
Kim Schouten is a scholar working on General Social Sciences, Artificial Intelligence and Communication, having authored 22 papers that have together received 888 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (14 papers), Sentiment Analysis and Opinion Mining (13 papers) and Text and Document Classification Technologies (6 papers). The work is most often cited by research in Artificial Intelligence (748 citations), Information Systems (180 citations) and General Social Sciences (20 citations). Kim Schouten has collaborated with scholars based in Netherlands, Austria and Germany. Frequent co-authors include Flavius Frăsincar, Rommert Dekker, Frederik Hogenboom, Erik‐Hans Klijn, Alexander Hogenboom, Franciska de Jong, Annelies de Klein, J.C. Reubi, J.A. Foekens and Aart H. Bootsma. Their work appears in journals such as International Journal of Cancer, Expert Systems with Applications and IEEE Transactions on Cybernetics.
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.