Caroline Jay

2.3k citations
144 papers · 1.3k · h-index 18

Impact in

Papers in

Caroline Jay

131 papers receiving 1.3k citations

Peers

Caroline Jay
Comparison fields: 5 of 136
  • Human-Computer Interaction 361
  • Human Factors and Ergonomics 89
  • Computer Science Applications 82
  • Health Informatics 17
  • Cognitive Neuroscience 218
Replace Frode Eika Sandnes with:
Frode Eika Sandnes Norway
Jeff Sauro United States
Sri Kurniawan United States
Tassos A. Mikropoulos Greece
Adam Fourney United States
Nikola Banović United States
Jerry Alan Fails United States
Alberto Raposo Brazil
Martin Maguire United Kingdom
Carmelo Ardito Italy
Caroline Jay relative to Frode Eika Sandnes Norway Frode Eika Sandnes's profile →
Citations per field
00.5×1.5×1.9×
Frode Eika Sandnes · 1×
Citations per year

Countries citing papers authored by Caroline Jay

Since Specialization
Citations

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

Fields of papers citing papers by Caroline Jay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 144 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007105
2 201463
3 201559
4 201749
5 202144
6 201439
7 200837
8 201436
9 200336
10 200534
11 201834
12 201432
13 201726
14 201225
15 200824
16 202117
17 201717
18 201017
19 201317
20 200717

About Caroline Jay

Caroline Jay is a scholar working on Human-Computer Interaction, Cognitive Neuroscience, Information Systems, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 144 papers that have together received 1.3k indexed citations. Recurring topics across this work include Tactile and Sensory Interactions (19 papers), Digital Accessibility for Disabilities (15 papers), Data Visualization and Analytics (14 papers), Gaze Tracking and Assistive Technology (11 papers), Biomedical Text Mining and Ontologies (11 papers), Scientific Computing and Data Management (10 papers), Virtual Reality Applications and Impacts (10 papers) and Semantic Web and Ontologies (9 papers). The work is most often cited by research in Human-Computer Interaction (361 citations), Human Factors and Ergonomics (89 citations), Computer Science Applications (82 citations), Health Informatics (17 citations) and Cognitive Neuroscience (218 citations). Caroline Jay has collaborated with scholars based in United Kingdom, United States and Saudi Arabia. Frequent co-authors include Roger Hubbold, Simon Harper, Markel Vigo, Mashhuda Glencross, Robert Stevens, Andy Brown, Alan Davies, Niels Peek, Julia Mueller and Julio Vega. Their work appears in journals such as International Journal of Human-Computer Studies, Scientific Reports, Journal of Medical Internet Research, Journal of Systems and Software and Journal of the American Medical Informatics Association.

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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