Jonathan Bragg

1.0k citations
29 papers · 432 · h-index 13

Impact in

    • Mobile Crowdsensing and Crowdsourcing
    • Open Source Software Innovations
    • Topic Modeling
    • Data Stream Mining Techniques
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Privacy-Preserving Technologies in Data

Papers in

Jonathan Bragg

27 papers receiving 416 citations

Peers

Jonathan Bragg
Comparison fields: 5 of 64
  • Computer Science Applications 228
  • Artificial Intelligence 258
  • Management Science and Operations Research 85
  • Health Informatics 9
  • Human Factors and Ergonomics 10
Replace Pavel Kucherbaev with:
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Jonathan Bragg relative to Pavel Kucherbaev Italy Pavel Kucherbaev's profile →
Citations per field
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Pavel Kucherbaev · 1×
Citations per year

Countries citing papers authored by Jonathan Bragg

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Bragg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201387
2 201650
3 201637
4 201929
5 202328
6 201624
7 201822
8 201721
9 201418
10 202416
11 202315
12 202214
13
Artificial Intelligence and Collective Intelligence
201412
14 202210
15 201710
16 20229
17 20218
18 20254
19
Fake It Till You Make It: Learning-Compatible Performance Support.
20193
20
Learning on the Job: Optimal Instruction for Crowdsourcing
20153

About Jonathan Bragg

Jonathan Bragg is a scholar working on Artificial Intelligence, Information Systems, Computer Science Applications, Management Science and Operations Research and Information Systems and Management, having authored 29 papers that have together received 432 indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (11 papers), Data Stream Mining Techniques (6 papers), Topic Modeling (6 papers), Auction Theory and Applications (5 papers), Software Engineering Research (3 papers), Scientific Computing and Data Management (3 papers), Advanced Text Analysis Techniques (3 papers) and Digital Accessibility for Disabilities (3 papers). The work is most often cited by research in Computer Science Applications (228 citations), Artificial Intelligence (258 citations), Management Science and Operations Research (85 citations), Health Informatics (9 citations) and Human Factors and Ergonomics (10 citations). Jonathan Bragg has collaborated with scholars based in United States, India and Israel. Frequent co-authors include Daniel S. Weld, Mausam Mausam, Lydia B. Chilton, Lucy Lu Wang, Daniel S. Weld, Christopher H. Lin, Andrew Head, Kyle Lo, Dan Weld and Quan Ze Chen. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, ACM Transactions on Computer-Human Interaction, ACM Transactions on Interactive Intelligent Systems, Uncertainty in Artificial Intelligence and Adaptive Agents and Multi-Agents 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.

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