Casey Dugan

3.8k total citations · 1 hit paper
56 papers, 2.1k citations indexed

About

Casey Dugan is a scholar working on Artificial Intelligence, Information Systems and Management and Information Systems. According to data from OpenAlex, Casey Dugan has authored 56 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 16 papers in Information Systems and Management and 13 papers in Information Systems. Recurrent topics in Casey Dugan's work include Personal Information Management and User Behavior (11 papers), Ethics and Social Impacts of AI (11 papers) and Mobile Crowdsensing and Crowdsourcing (8 papers). Casey Dugan is often cited by papers focused on Personal Information Management and User Behavior (11 papers), Ethics and Social Impacts of AI (11 papers) and Mobile Crowdsensing and Crowdsourcing (8 papers). Casey Dugan collaborates with scholars based in United States, Israel and Australia. Casey Dugan's co-authors include Michael Müller, Philipp Geyer, David R. Millen, Joan Morris DiMicco, Beth Brownholtz, Werner Geyer, Ido Guy, Jilin Chen, Dakuo Wang and Rosta Farzan and has published in prestigious journals such as ACM Transactions on Computer-Human Interaction, Proceedings of the ACM on Human-Computer Interaction and ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam).

In The Last Decade

Casey Dugan

53 papers receiving 2.0k citations

Hit Papers

Motivations for social networking at work 2008 2026 2014 2020 2008 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Motivations for social networking at work
    2008 467 citations Joan Morris DiMicco, David R. Millen et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Casey Dugan United States 19 677 574 547 527 422 56 2.1k
Kai Riemer Australia 25 1.2k 1.8× 934 1.6× 260 0.5× 339 0.6× 544 1.3× 147 2.5k
Ravi Vatrapu Denmark 25 567 0.8× 484 0.8× 489 0.9× 750 1.4× 157 0.4× 136 2.4k
Laura Granka United States 14 961 1.4× 372 0.6× 811 1.5× 1.7k 3.2× 235 0.6× 21 3.4k
David R. Millen United States 27 1.3k 1.9× 1.2k 2.0× 503 0.9× 828 1.6× 700 1.7× 98 3.6k
Wai‐Tat Fu United States 23 426 0.6× 206 0.4× 494 0.9× 393 0.7× 157 0.4× 105 1.8k
Haiyi Zhu United States 24 541 0.8× 425 0.7× 537 1.0× 266 0.5× 76 0.2× 84 1.8k
Bettina Berendt Belgium 21 894 1.3× 179 0.3× 751 1.4× 836 1.6× 295 0.7× 109 2.3k
Jens Großklags Germany 24 1.8k 2.6× 212 0.4× 746 1.4× 1.0k 2.0× 409 1.0× 137 2.9k
Dan Frankowski United States 15 479 0.7× 650 1.1× 351 0.6× 544 1.0× 145 0.3× 20 1.8k
Olivier Toubia United States 26 1.3k 1.8× 317 0.6× 292 0.5× 126 0.2× 536 1.3× 70 2.9k

Countries citing papers authored by Casey Dugan

Since Specialization
Citations

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

Fields of papers citing papers by Casey Dugan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Casey Dugan

This figure shows the co-authorship network connecting the top 25 collaborators of Casey Dugan. A scholar is included among the top collaborators of Casey Dugan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Casey Dugan. Casey Dugan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Dugan, Casey, et al.. (2025). Current and Future Use of Large Language Models for Knowledge Work. Proceedings of the ACM on Human-Computer Interaction. 9(7). 1–24.
3.
Ashktorab, Zahra, et al.. (2025). Helping the Helper : Supporting Peer Counselors via AI-Empowered Practice and Feedback. Proceedings of the ACM on Human-Computer Interaction. 9(2). 1–45. 2 indexed citations
4.
Dugan, Casey, et al.. (2024). How Knowledge Workers Use and Want to Use LLMs in an Enterprise Context. 1–8. 13 indexed citations
5.
Dugan, Casey, et al.. (2024). Evaluating What Others Say: The Effect of Accuracy Assessment in Shaping Mental Models of AI Systems. Proceedings of the ACM on Human-Computer Interaction. 8(CSCW2). 1–26. 2 indexed citations
6.
Dugan, Casey, et al.. (2024). Grounding with Structure: Exploring Design Variations of Grounded Human-AI Collaboration in a Natural Language Interface. Proceedings of the ACM on Human-Computer Interaction. 8(CSCW2). 1–27.
7.
Pan, Qian, Casey Dugan, James M. Johnson, et al.. (2023). Follow the Successful Herd: Towards Explanations for Improved Use and Mental Models of Natural Language Systems. 220–239. 7 indexed citations
8.
Ashktorab, Zahra, et al.. (2023). SME-in-the-loop: Interaction Preferences when Supervising Bots in Human-AI Communities. 2281–2303. 3 indexed citations
9.
Ashktorab, Zahra, et al.. (2023). Decision Making Strategies and Team Efficacy in Human-AI Teams. Proceedings of the ACM on Human-Computer Interaction. 7(CSCW1). 1–24. 16 indexed citations
10.
Chakraborti, Tathagata, Casey Dugan, Thomas Gschwind, et al.. (2022). A Goal-Driven Natural Language Interface for Creating Application Integration Workflows. Proceedings of the AAAI Conference on Artificial Intelligence. 36(11). 13155–13157. 2 indexed citations
11.
Lee, Tak Yeon, et al.. (2021). Experiments on Motivational Feedback for Crowdsourced Workers. Proceedings of the International AAAI Conference on Web and Social Media. 7(1). 341–350. 10 indexed citations
12.
Gero, Katy Ilonka, Zahra Ashktorab, Casey Dugan, et al.. (2020). Mental Models of AI Agents in a Cooperative Game Setting. 1–12. 72 indexed citations
13.
Ashktorab, Zahra, Casey Dugan, James M. Johnson, et al.. (2020). Human-AI Collaboration in a Cooperative Game Setting. Proceedings of the ACM on Human-Computer Interaction. 4(CSCW2). 1–20. 44 indexed citations
14.
Dugan, Casey, et al.. (2019). Explaining models an empirical study of how explanations impact fairness judgment. 275–285. 1 indexed citations
15.
Müller, Michael, et al.. (2017). What Did I Ask You to Do, by When, and for Whom?. 1009–1023. 3 indexed citations
16.
Geyer, Philipp, et al.. (2011). An open, social microcalender for the enterprise. 247–256. 9 indexed citations
17.
Cheng, Li-Te, Casey Dugan, Michael Müller, et al.. (2011). Finding Moments of Play at Work. 4 indexed citations
18.
Geyer, Werner, Casey Dugan, Joan Morris DiMicco, et al.. (2008). Use and reuse of shared lists as a social content type. 1545–1554. 30 indexed citations
19.
Farzan, Rosta, et al.. (2008). Results from deploying a participation incentive mechanism within the enterprise. 563–572. 185 indexed citations
20.
Dugan, Casey, Werner Geyer, Michael Müller, et al.. (2008). It's all 'about you'. 703–706. 20 indexed citations

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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