Samuel W. K. Chan
- Sociology and Political Science top 5%
- Health top 5%
- Artificial Intelligence top 10%
- Social Psychology top 10%
- Clinical Psychology
- Co-authors
- James FranklinJoseph T. F. LauPhoenix K. H. MoKira S. BirdittSteven H. ZaritLindsay PitzerMelissa M. FranksKaren L. Fingerman
- Topics
- Topic Modeling (8 papers)Natural Language Processing Techniques (8 papers)Advanced Text Analysis Techniques (6 papers)
- Journals
- Expert Systems with ApplicationsIEEE Transactions on Knowledge and Data EngineeringDecision Support Systems
- Partner nations
- Hong KongUnited KingdomUnited States
In The Last Decade
Samuel W. K. Chan
22 papers receiving 658 citations
Peers
Comparison fields: 5 of 93
- Sociology and Political Science 268
- Health 131
- Artificial Intelligence 127
- Social Psychology 120
- Clinical Psychology 108
Countries citing papers authored by Samuel W. K. Chan
This map shows the geographic impact of Samuel W. K. Chan'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 Samuel W. K. Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel W. K. Chan more than expected).
Fields of papers citing papers by Samuel W. K. Chan
This network shows the impact of papers produced by Samuel W. K. Chan. 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 Samuel W. K. Chan. The network helps show where Samuel W. K. Chan may publish in the future.
Co-authorship network of co-authors of Samuel W. K. Chan
This figure shows the co-authorship network connecting the top 25 collaborators of Samuel W. K. Chan. A scholar is included among the top collaborators of Samuel W. K. Chan 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 Samuel W. K. Chan. Samuel W. K. Chan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 14 | |
| 3 | 29 | |
| 4 | 108 | |
| 5 | 14 | |
| 6 | 1 | |
| 7 | 95 | |
| 8 | 130 | |
| 9 | 15 | |
| 10 | 60 | |
| 11 | Tree Topological Features for Unlexicalized Parsing | 3 |
| 12 | 150 | |
| 13 | 3 | |
| 14 | 11 | |
| 15 | 3 | |
| 16 | 8 | |
| 17 | 9 | |
| 18 | 5 | |
| 19 | 1 | |
| 20 | 2 |
About Samuel W. K. Chan
Samuel W. K. Chan is a scholar working on Neuropsychology and Physiological Psychology, Health and Applied Psychology, having authored 22 papers that have together received 684 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (8 papers) and Advanced Text Analysis Techniques (6 papers). The work is most often cited by research in Neuropsychology and Physiological Psychology (41 citations), Health (131 citations) and Applied Psychology (55 citations). Samuel W. K. Chan has collaborated with scholars based in Hong Kong, United Kingdom and United States. Frequent co-authors include James Franklin, Joseph T. F. Lau, Phoenix K. H. Mo, Kira S. Birditt, Steven H. Zarit, Lindsay Pitzer, Melissa M. Franks, Karen L. Fingerman, Daniel K. Mroczek and Avron Spiro. Their work appears in journals such as Expert Systems with Applications, IEEE Transactions on Knowledge and Data Engineering and Decision Support Systems.
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.