John O’Donovan

70 papers receiving 2.7k citations

John O’Donovan's Hit Papers

Trust in recommender systems 2005 · 691 citations
6910+7+14Years since publication200400600

Peers

John O’Donovan
Comparison fields: 5 of 76
  • Information Systems 1.6k
  • Human-Computer Interaction 123
  • Computer Vision and Pattern Recognition 336
  • Artificial Intelligence 441
  • Sociology and Political Science 447
Replace Nava Tintarev with:
Nava Tintarev Netherlands
Shilad Sen United States
Denis Parra Chile
Vincent Wade Ireland
Shyong K. Lam United States
Marco Furini Italy
Sibel Adalı United States
Rosie Jones United States
Fabian Abel Germany
Werner Geyer United States
John O’Donovan relative to Nava Tintarev Netherlands Nava Tintarev's profile →
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Citations per year

Countries citing papers authored by John O’Donovan

Since Specialization
Citations

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

Fields of papers citing papers by John O’Donovan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John O’Donovan. 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 John O’Donovan. The network helps show where John O’Donovan may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Trust in recommender systems
Hit paper breakdown →
2005691
2 2012229
3 2008130
4 2019130
5 2012115
6 2012114
7 2018112
8 201094
9 201994
10 201291
11 201282
12 201878
13 201661
14 201755
15 201653
16 201644
17 201337
18 202034
19 201933
20 201332

About John O’Donovan

John O’Donovan is a scholar working on Information Systems, Computer Vision and Pattern Recognition, Social Psychology, Human-Computer Interaction and Sociology and Political Science, having authored 70 papers that have together received 2.8k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (39 papers), Misinformation and Its Impacts (9 papers), Human-Automation Interaction and Safety (8 papers), Data Visualization and Analytics (7 papers), Information Retrieval and Search Behavior (5 papers), Augmented Reality Applications (4 papers), Access Control and Trust (3 papers) and Sentiment Analysis and Opinion Mining (3 papers). The work is most often cited by research in Information Systems (1.6k citations), Human-Computer Interaction (123 citations), Computer Vision and Pattern Recognition (336 citations), Artificial Intelligence (441 citations) and Sociology and Political Science (447 citations). John O’Donovan has collaborated with scholars based in United States, Ireland and United Kingdom. Frequent co-authors include Barry Smyth, Tobias Höllerer, Svetlin Bostandjiev, James Schaffer, Brynjar Gretarsson, Denis Parra, Pigi Kouki, Jay Pujara, Lise C. Getoor and Sibel Adalı. Their work appears in journals such as ACM Transactions on Interactive Intelligent Systems, Computer Graphics Forum, International Journal of Human-Computer Studies, ACM Transactions on Intelligent Systems and Technology and Network Science.

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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