Daniel Kluver

858 citations
15 papers · 446 · h-index 11

Impact in

Papers in

Daniel Kluver

14 papers receiving 431 citations

Peers

Daniel Kluver
Comparison fields: 5 of 56
  • Human-Computer Interaction 103
  • Information Systems 202
  • Computer Science Applications 44
  • Management Science and Operations Research 89
  • Communication 41
Replace Chris Newell with:
Chris Newell Switzerland
Nava Tintarev Netherlands
Shuo Chang United States
Ying‐Hsang Liu Australia
Huahai Yang United States
Praveen Chandar United States
Svetlin Bostandjiev United States
Maria Soledad Pera United States
Hana Habib United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Kluver

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kluver

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Daniel Kluver, 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 Daniel Kluver Line = papers co-authored together Daniel Kluver links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2017100
2 201565
3 201862
4 201437
5 201537
6 201333
7 202127
8 201223
9 202120
10 201718
11 201815
12 20225
13 20233
14 20241
15 20250

About Daniel Kluver

Daniel Kluver is a scholar working on Information Systems, Management Science and Operations Research, Marketing, Artificial Intelligence and Management Information Systems, having authored 15 papers that have together received 446 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (8 papers), Advanced Bandit Algorithms Research (5 papers), Consumer Market Behavior and Pricing (5 papers), Sentiment Analysis and Opinion Mining (2 papers), FinTech, Crowdfunding, Digital Finance (2 papers), Expert finding and Q&A systems (2 papers), Digital Communication and Language (2 papers) and Auction Theory and Applications (2 papers). The work is most often cited by research in Human-Computer Interaction (103 citations), Information Systems (202 citations), Computer Science Applications (44 citations), Management Science and Operations Research (89 citations) and Communication (41 citations). Daniel Kluver has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Michael D. Ekstrand, Joseph A. Konstan, Loren Terveen, Jacob Thebault-Spieker, Brent Hecht, F. Maxwell Harper, Tien Thanh Nguyen, Hoda Mehrpouyan, John Riedl and Aaron Halfaker. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, User Modeling and User-Adapted Interaction, Proceedings of the International AAAI Conference on Web and Social Media, TU/e Research Portal and Scholar Works (Boise State University).

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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