For a complete list of publications, please visit Professor Konstan's Google Scholar page or the GroupLens lab's website.

Recent

Ruoyan Kong, Haiyi Zhu, and Joseph A. Konstan. Learning to Ignore: A Case Study of Organization-Wide Bulk Email Effectiveness. Proceedings of the ACM on Human-Computer Interaction (CSCW 2021), 1-23.

Joseph T. Yun, Claire M. Segijn, Stewart Pearson, Edward C. Malthouse, Joseph A. Konstan & Venkatesh Shankar (2020) Challenges and Future Directions of Computational Advertising Measurement Systems, Journal of Advertising, 49:4, 446-458, DOI: 10.1080/00913367.2020.1795757

Helen Fu, Terrence J Adam, Joseph A Konstan, Julian Wolfson, Thomas Clancy, Jean F Wyman. Influence of Patient Characteristics and Psychological Needs on Diabetes Mobile App Usability in Adults with Type 1 or Type 2 Diabetes on Insulin Therapy. JMIR Diuabetes. doi:10.2196/11462 (2019).

Qian Zhao, Martijn C. Willemsen, Gediminas Adomavicius, F. Maxwell Harper, and Joseph A. Konstan. 2018. Interpreting user inaction in recommender systems. In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys '18). ACM, New York, NY, USA, 40-48. DOI: https://doi.org/10.1145/3240323.3240366 (acceptance rate: 18%)

Raghav Pavan Karumur, Bown Yu, Haiyi Zhu, and Joseph A. Konstan. 2018. Content is King, Leadership Lags: Effects of Prior Experience on Newcomer Retention and Productivity in Online Production Groups. Proceedings of ACM CHI 2018. (acceptance rate: 25.7%)

Taavi Taijala, Martijn Willemsen, and Joseph A. Konstan. 2018. MovieExplorer: Building an Interactive Exploration Tool from Ratings and Latent Taste Spaces. Proceedings of ACM SAC 2018 track on Recommender Systems: Theory, User Interactions, and Applications. (acceptance rate: 21.6%)

Qian Zhao, F. Maxwell Harper, Gediminas Adomavicius, and Joseph A. Konstan. 2018. Explicit or Implicit Feedback? Engagement or Satisfaction? — A Field Experiment on Machine-Learning-Based Recommender Systems. Proceedings of ACM SAC 2018 track on Recommender Systems:  Theory, User Interactions, and Applications. (acceptance rate: 21.6%)

Denis Kotkov, Joseph A. Konstan, Qian Zhao, and Jari Veijalainen. 2018. Investigating Serendipity in Recommender Systems Based on Real User Feedback. Proceedings of ACM SAC 2018 track on Recommender Systems: Theory, User Interactions, and Applications. (acceptance rate: 21.6%)

Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, and Justin Zobel. From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing, Recommender Systems into Predictive Sciences. Dagstuhl Manifestos 7(1) 96-139 (2018).

Tomu Tominaga, Yoshinori Hijikata, & Joseph A. Konstan. How self-disclosure in Twitter profiles relate to anonymity consciousness and usage objectives: a cross-cultural study. Journal of Computational Social (2018) pp. 1-45. https://doi.org/10.1007/s42001-018-0023-z

Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, and Joseph A. Konstan. Towards Performance Modeling and Performance Prediction across IR/RecSys/NLP. Dagstuhl Reports 7(10), 2018, pp. 139-146.

Jie Kang, Kyle Condiff, Shuo Chang, Joseph A. Konstan, Loren Terveen, and F. Maxwell Harper. 2017. Understanding How People Use Natural Language to Ask for Recommendations. Proceedings of RecSys ’17, Como, Italy, August 27-31, 2017, https://doi.org/10.1145/3109859.3109873

Qian Zhao, Gediminas Adomavicius, F. Maxwell Harper, Martijn Willemsen, and Joseph A. Konstan. 2017. Toward Better Interactions in Recommender Systems: Cycling and Serpentining Approaches for Top-N Item Lists. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17). ACM, New York, NY, USA, 1444-1453. (acceptance rate: 35% after two rounds of review)

Weiwen Leung, Haiyi Zhu, and Joseph A. Konstan. 2017. The Effect of Emotional Cues from the NFL on Wikipedia Contributions. Proc. ACM Hum.-Comput. Interact. 1, CSCW, Article 66 (December 2017), 21 pages.

Jacob Thebault-Spieker, Daniel Kluver, Maximilian A. Klein, Aaron Halfaker, Brent Hecht, Loren Terveen, and Joseph A. Konstan. 2017. Simulation Experiments on (the Absence of) Ratings Bias in Reputation Systems. Proc. ACM Hum.-Comput. Interact. 1, CSCW, Article 101 (December 2017), 25 pages.

Raghav Pavan Karumur, Tien T. Nguyen, Joseph A. Konstan. Personality, User Preferences, and Behavior in Recommender Systems. Information Systems Frontiers 20(6) 1241-1265, online Sept. 13, 2017

Tien T. Nguyen, F. Maxwell Harper, Loren Terveen, Joseph A. Konstan. User Personality and User Satisfaction with Recommender Systems.  Information Systems Frontiers 20(6) 1173-1189, online Sept. 3, 2017

Fernando Mourão, Leonardo Rocha, Camila Araújo, Wagner Meira Jr., Joseph Konstan. What Surprises does your past have for you?, Information Systems, 71:137-151, Nov. 2017, ISSN 0306-4379, https://doi.org/10.1016/j.is.2017.08.001.

F. Maxwell Harper and Joseph A. Konstan. The MovieLens Datasets: History and Context. ACM Trans. Interact. Intell. Syst. 5, 4, Article 19 (December 2015), 19 pages. DOI=http://dx.doi.org/10.1145/2827872

 

Top 10 Most Cited

Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl. 2001. Item-based Collaborative Filtering Recommendation Algorithms. Proceedings of the Tenth International World Wide Web Conference.

Jonathan L. Herlocker, Joseph A. Konstan, Loren G. Terveen, and John T. Riedl. 2004. Evaluating Collaborative Filtering Recommender Systems. ACM Trans. Inf. Syst. 22, 1: 5–53.

Jonathan L. Herlocker, Joseph A. Konstan, Al Borchers, and John Riedl. 1999. An Algorithmic Framework for Performing Collaborative Filtering. Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM, 230–237.

Joseph A. Konstan, Bradley N. Miller, David Maltz, Jonathan L. Herlocker, Lee R. Gordon, and John Riedl. 1997. GroupLens: Applying Collaborative Filtering to Usenet News. Commun. ACM 40, 3: 77–87.

Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl. 2000. Analysis of Recommendation Algorithms for e-Commerce. Proceedings of the 2nd ACM Conference on Electronic Commerce, ACM, 158–167.

F Maxwell Harper, Joseph A Konstan. 2015. The movielens datasets: History and context. ACM transactions on interactive intelligent systems (tiis), ACM, 1-19.

J Ben Schafer, Joseph A Konstan, John Riedl. 2001. E-commerce recommendation applications Data mining and knowledge discovery, 5, 1: 115-153.

J Ben Schafer, Joseph A Konstan, John Riedl. 1999.Recommender systems in e-commerce. Proceedings of the 1st ACM conference on Electronic commerce, 158-166.

Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl. 2000. Application of dimensionality reduction in recommender system-a case study. University of Minnesota, Deaprtment of Computer Science.

Jonathan L Herlocker, Joseph A Konstan, John Riedl. 2000. Explaining collaborative filtering recommendations. Proceedings of the 2000 ACM conference on Computer supported cooperative work, 241-250.