F. Maxwell Harper

7.8k total citations · 2 hit papers
38 papers, 4.7k citations indexed

About

F. Maxwell Harper is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, F. Maxwell Harper has authored 38 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Information Systems, 12 papers in Artificial Intelligence and 9 papers in Management Science and Operations Research. Recurrent topics in F. Maxwell Harper's work include Recommender Systems and Techniques (22 papers), Mobile Crowdsensing and Crowdsourcing (8 papers) and Expert finding and Q&A systems (7 papers). F. Maxwell Harper is often cited by papers focused on Recommender Systems and Techniques (22 papers), Mobile Crowdsensing and Crowdsourcing (8 papers) and Expert finding and Q&A systems (7 papers). F. Maxwell Harper collaborates with scholars based in United States, Netherlands and Chile. F. Maxwell Harper's co-authors include Joseph A. Konstan, Loren Terveen, Sherry Xin Li, Yan Chen, Daphne R. Raban, Sheizaf Rafaeli, Tien Thanh Nguyen, Ruotong Wang, Haiyi Zhu and Shuo Chang and has published in prestigious journals such as American Economic Review, ACM Transactions on Information Systems and Information Systems Frontiers.

In The Last Decade

F. Maxwell Harper

36 papers receiving 4.5k citations

Hit Papers

The MovieLens Datasets 2014 2026 2018 2022 2015 2014 500 1000 1.5k 2.0k
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. The MovieLens Datasets
    2015 2.1k citations F. Maxwell Harper, Joseph A. Konstan ACM Transactions on Interactive Intelligent Systems profile →
  2. Exploring the filter bubble
    2014 256 citations Tien Thanh Nguyen, F. Maxwell Harper 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
F. Maxwell Harper United States 23 2.9k 2.1k 882 721 711 38 4.7k
Jaime Teevan United States 43 3.7k 1.3× 2.5k 1.2× 792 0.9× 1.1k 1.6× 469 0.7× 152 7.8k
Francesco Bonchi Italy 42 1.8k 0.6× 3.1k 1.5× 770 0.9× 870 1.2× 500 0.7× 188 6.8k
Eytan Adar United States 37 1.9k 0.7× 2.8k 1.3× 1.3k 1.4× 1.3k 1.8× 472 0.7× 106 7.6k
Li Chen Hong Kong 38 3.0k 1.0× 2.7k 1.3× 798 0.9× 996 1.4× 871 1.2× 262 5.7k
Dietmar Jannach Austria 43 4.8k 1.6× 3.1k 1.5× 1.5k 1.7× 1.1k 1.6× 1.4k 2.0× 225 7.3k
Daniel S. Weld United States 48 2.6k 0.9× 6.0k 2.9× 976 1.1× 422 0.6× 884 1.2× 128 8.9k
Mounia Lalmas United Kingdom 33 1.8k 0.6× 1.7k 0.8× 527 0.6× 623 0.9× 441 0.6× 216 3.8k
Kalervo Järvelin Finland 32 4.3k 1.5× 3.7k 1.8× 1.3k 1.5× 479 0.7× 745 1.0× 162 7.7k
Margaret Burnett United States 47 2.2k 0.8× 1.8k 0.8× 610 0.7× 457 0.6× 173 0.2× 262 7.2k
Gary Marchionini United States 36 3.7k 1.3× 1.9k 0.9× 1.5k 1.7× 1.0k 1.4× 277 0.4× 194 7.2k

Countries citing papers authored by F. Maxwell Harper

Since Specialization
Citations

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

Fields of papers citing papers by F. Maxwell Harper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by F. Maxwell Harper. 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 F. Maxwell Harper. The network helps show where F. Maxwell Harper may publish in the future.

Co-authorship network of co-authors of F. Maxwell Harper

This figure shows the co-authorship network connecting the top 25 collaborators of F. Maxwell Harper. A scholar is included among the top collaborators of F. Maxwell Harper 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 F. Maxwell Harper. F. Maxwell Harper 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.
Sun, Lu, F. Maxwell Harper, Chia-Jung Lee, Vanessa Murdock, & Bárbara Poblete. (2023). Characterizing and Identifying Socially Shared Self-Descriptions in Product Reviews. Proceedings of the International AAAI Conference on Web and Social Media. 17. 808–819. 1 indexed citations
2.
3.
Chang, Shuo, et al.. (2021). CrowdLens: Experimenting with Crowd-Powered Recommendation and Explanation. Proceedings of the International AAAI Conference on Web and Social Media. 10(1). 52–61.
4.
Wang, Ruotong, F. Maxwell Harper, & Haiyi Zhu. (2020). Factors Influencing Perceived Fairness in Algorithmic Decision-Making. 1–14. 120 indexed citations
5.
Zhao, Qian, F. Maxwell Harper, Gediminas Adomavičius, & Joseph A. Konstan. (2018). Explicit or implicit feedback? engagement or satisfaction?. 1331–1340. 34 indexed citations
6.
Zhao, Qian, Martijn C. Willemsen, Gediminas Adomavičius, F. Maxwell Harper, & Joseph A. Konstan. (2018). Interpreting user inaction in recommender systems. TU/e Research Portal. 40–48. 15 indexed citations
7.
Zhong, Yifan, et al.. (2018). A field study of related video recommendations. 274–278. 4 indexed citations
8.
Chang, Shuo, et al.. (2017). Understanding How People Use Natural Language to Ask for Recommendations. 229–237. 46 indexed citations
9.
Nguyen, Tien Thanh, F. Maxwell Harper, Loren Terveen, & Joseph A. Konstan. (2017). User Personality and User Satisfaction with Recommender Systems. Information Systems Frontiers. 20(6). 1173–1189. 75 indexed citations
10.
Harper, F. Maxwell & Joseph A. Konstan. (2015). The MovieLens Datasets. ACM Transactions on Interactive Intelligent Systems. 5(4). 1–19. 2071 indexed citations breakdown →
11.
Harper, F. Maxwell, et al.. (2015). Putting Users in Control of their Recommendations. 3–10. 67 indexed citations
12.
Chang, Shuo, F. Maxwell Harper, & Loren Terveen. (2015). Using Groups of Items for Preference Elicitation in Recommender Systems. 1258–1269. 36 indexed citations
13.
Logie, John, Joseph Weinberg, F. Maxwell Harper, & Joseph A. Konstan. (2011). Asked and Answered: On Qualities and Quantities of Answers in Online Q&A Sites. 24–31. 3 indexed citations
14.
Harper, F. Maxwell, et al.. (2009). Facts or friends?. 759–768. 193 indexed citations
15.
Harper, F. Maxwell, Daphne R. Raban, Sheizaf Rafaeli, & Joseph A. Konstan. (2008). Predictors of answer quality in online Q&A sites. 865–874. 315 indexed citations
16.
McCarthy, Joseph F., et al.. (2008). The context, content & community collage. 97–106. 32 indexed citations
17.
Chen, Yan, F. Maxwell Harper, Joseph A. Konstan, & Sherry Xin Li. (2007). Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 0. 5 indexed citations
18.
Frankowski, Dan, Shyong K. Lam, Shilad Sen, et al.. (2007). Recommenders everywhere:. 47–60. 12 indexed citations
19.
Sen, Shilad, et al.. (2007). The quest for quality tags. 361–361. 58 indexed citations
20.
Sen, Shilad, Shyong K. Lam, Al Mamunur Rashid, et al.. (2006). tagging, communities, vocabulary, evolution. 181–190. 273 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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