David Sweeney

1.3k citations
30 papers · 694 · h-index 12

Impact in

Papers in

David Sweeney

29 papers receiving 669 citations

Peers

David Sweeney
Comparison fields: 5 of 101
  • Human-Computer Interaction 339
  • Computer Vision and Pattern Recognition 252
  • Computer Science Applications 33
  • Information Systems and Management 40
  • Management of Technology and Innovation 38
Replace Kyeong‐Ah Jeong with:
Kyeong‐Ah Jeong United States
Benjamim Fonseca Portugal
David Alonso-Ríos Spain
Heidi Krömker Germany
Jorge Bacca Colombia
Marco Romano Italy
Indira Thouvenin France
Carlos Bermejo Hong Kong
Iina Aaltonen Finland
Sang Won Lee United States
David Sweeney relative to Kyeong‐Ah Jeong United States Kyeong‐Ah Jeong's profile →
Citations per field
00.5×10×20×30×42.5×
Kyeong‐Ah Jeong · 1×
Citations per year

Countries citing papers authored by David Sweeney

Since Specialization
Citations

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

Fields of papers citing papers by David Sweeney

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016227
2 2015139
3 201453
4 201452
5 201727
6 201626
7 202426
8 201324
9 201418
10 201514
11 201614
12 201113
13 201212
14 202311
15 20237
16 20045
17 20244
18 20103
19 20143
20 20143

About David Sweeney

David Sweeney is a scholar working on Human-Computer Interaction, Information Systems, Industrial and Manufacturing Engineering, Computer Science Applications and Computer Networks and Communications, having authored 30 papers that have together received 694 indexed citations. Recurring topics across this work include Innovative Human-Technology Interaction (4 papers), Interactive and Immersive Displays (3 papers), Mobile Crowdsensing and Crowdsourcing (2 papers), Information Systems Theories and Implementation (2 papers), Advanced Data Storage Technologies (2 papers), Cloud Data Security Solutions (2 papers), Tactile and Sensory Interactions (2 papers) and Digital Transformation in Industry (2 papers). The work is most often cited by research in Human-Computer Interaction (339 citations), Computer Vision and Pattern Recognition (252 citations), Computer Science Applications (33 citations), Information Systems and Management (40 citations) and Management of Technology and Innovation (38 citations). David Sweeney has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Alex S. Taylor, Tim W. Regan, Siân E. Lindley, Vasillis Vlachokyriakos, Pushmeet Kohli, Cem Keskin, Jamie Shotton, Shahram Izadi, Julien Valentin and Jonathan M. Taylor. Their work appears in journals such as ACM Transactions on Graphics, IEEE Pervasive Computing, American Journal of Community Psychology, Insights the UKSG journal and Water Research.

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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