William Raffe

544 citations
37 papers · 334 · h-index 11

Impact in

Papers in

William Raffe

35 papers receiving 326 citations

Peers

William Raffe
Comparison fields: 5 of 81
  • Human-Computer Interaction 68
  • Developmental and Educational Psychology 93
  • Artificial Intelligence 124
  • Computer Vision and Pattern Recognition 60
  • Sociology and Political Science 104
Replace Anton Bogdanovych with:
Anton Bogdanovych Australia
Ioannis Paliokas Greece
Nur Azlina Mohamed Mokmin Malaysia
Aung Pyae Finland
Newton Lee United States
Ray J. Hickey United Kingdom
Phil Lopes Switzerland
Luciano Nocera United States
Maria Beatriz Carmo Portugal
Kai Kuikkaniemi Finland
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Citations per field
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Anton Bogdanovych · 1×
Citations per year

Countries citing papers authored by William Raffe

Since Specialization
Citations

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

Fields of papers citing papers by William Raffe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside William Raffe, 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 William Raffe Line = papers co-authored together William Raffe links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202053
2 201739
3 201632
4 201518
5 201814
6 202014
7 201213
8 201913
9 201311
10 201810
11 202010
12 201810
13 201410
14 201810
15 20119
16 20218
17 20237
18 20195
19 20195
20 20205

About William Raffe

William Raffe is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Developmental and Educational Psychology and Human-Computer Interaction, having authored 37 papers that have together received 334 indexed citations. Recurring topics across this work include Artificial Intelligence in Games (15 papers), Digital Games and Media (9 papers), Educational Games and Gamification (9 papers), Video Analysis and Summarization (6 papers), Reinforcement Learning in Robotics (5 papers), Stroke Rehabilitation and Recovery (4 papers), Virtual Reality Applications and Impacts (3 papers) and Sports Analytics and Performance (3 papers). The work is most often cited by research in Human-Computer Interaction (68 citations), Developmental and Educational Psychology (93 citations), Artificial Intelligence (124 citations), Computer Vision and Pattern Recognition (60 citations) and Sociology and Political Science (104 citations). William Raffe has collaborated with scholars based in Australia, Germany and Netherlands. Frequent co-authors include Jaime García, Fabio Zambetta, Xiaodong Li, Florian Mueller, Alexey Voinov, Michael Hitchens, Anders Drachen, Rafet Sifa, A. Imran Nordin and Karla Félix Navarro. Their work appears in journals such as ACM Transactions on Computer-Human Interaction, Environmental Modelling & Software, IEEE Transactions on Computational Intelligence and AI in Games, Group Decision and Negotiation and IEEE Transactions on Games.

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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