Samuel W. K. Chan
- Health top 5%
- Health disparities and outcomes 4
- Applied Psychology top 10%
- Demography top 5%
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- Stock Market Forecasting Methods 2
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- Topic Modeling 8
- Natural Language Processing Techniques 8
- Advanced Text Analysis Techniques 6
- Speech and dialogue systems 3
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- Child and Animal Learning Development 3
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- Spatial Cognition and Navigation 2
- Co-authors
- James FranklinJoseph T. F. LauPhoenix K. H. MoKira S. BirdittSteven H. ZaritLindsay PitzerMelissa M. FranksKaren L. Fingerman
- Journals
- Decision Support Systems (4 papers)IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans (2 papers)Learning and Motivation (2 papers)
- 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
- Neuropsychology and Physiological Psychology 41
- Health 131
- Applied Psychology 55
- Demography 107
- Management Science and Operations Research 85
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
The 25 scholars most cited alongside Samuel W. K. Chan, 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 | 2024 | 1 | |
| 2 | 2022 | 14 | |
| 3 | 2021 | 29 | |
| 4 | 2018 | 108 | |
| 5 | 2017 | 14 | |
| 6 | 2017 | 1 | |
| 7 | 2016 | 95 | |
| 8 | 2013 | 130 | |
| 9 | 2012 | 15 | |
| 10 | 2011 | 60 | |
| 11 | Tree Topological Features for Unlexicalized Parsing | 2010 | 3 |
| 12 | 2010 | 150 | |
| 13 | 2009 | 3 | |
| 14 | 2005 | 11 | |
| 15 | 2004 | 3 | |
| 16 | 2003 | 8 | |
| 17 | 2003 | 9 | |
| 18 | 2001 | 5 | |
| 19 | 2000 | 1 | |
| 20 | 1999 | 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), Advanced Text Analysis Techniques (6 papers), Health disparities and outcomes (4 papers), Speech and dialogue systems (3 papers), Child and Animal Learning Development (3 papers), Stock Market Forecasting Methods (2 papers) and Spatial Cognition and Navigation (2 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 Decision Support Systems, IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans, Learning and Motivation, The Journals of Gerontology Series B and Cities.
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.