2020 - ACM Fellow For contributions to recommender systems, economics and computation, and online communities
2010 - ACM Software System Award For the GroupLens Collaborative Filtering Recommender Systems, which showed how to automate the process by which a distributed set of users could receive personalized recommendations by sharing ratings, leading to both commercial products and extensive research.
His scientific interests lie mostly in Reputation, Internet privacy, The Internet, Online participation and World Wide Web. His Reputation study incorporates themes from Convention, Advertising, Encryption and Inefficiency. His work deals with themes such as Social media, Rank, Rumor and Skepticism, which intersect with Internet privacy.
His studies deal with areas such as Interpersonal communication, Social design, Flourishing and Anonymity as well as The Internet. His World Wide Web study is mostly concerned with Recommender system and Collaborative filtering. His study in the fields of Slope One and MovieLens under the domain of Collaborative filtering overlaps with other disciplines such as User modeling.
His primary areas of study are World Wide Web, The Internet, Recommender system, Internet privacy and Multimedia. His work on News aggregator, Presentation, Personalization and Collaborative filtering as part of general World Wide Web research is frequently linked to Viewpoints, bridging the gap between disciplines. The concepts of his The Internet study are interwoven with issues in Computer security, Anonymity and Public relations.
The study incorporates disciplines such as Information loss and Artificial intelligence in addition to Recommender system. His Internet privacy research includes elements of Social media and Reputation. His Reputation system study, which is part of a larger body of work in Reputation, is frequently linked to Identity, bridging the gap between disciplines.
Paul Resnick focuses on Social media, Internet privacy, Politics, Artificial intelligence and Set. His study in Social media is interdisciplinary in nature, drawing from both Rumor, Fraction, The Internet, Popularity and Data science. In his study, which falls under the umbrella issue of Internet privacy, Social consciousness, Feeling and Computer security is strongly linked to Data collection.
Paul Resnick has researched Artificial intelligence in several fields, including Meaningful learning, Critical thinking, Machine learning and Usage data. The Visualization study combines topics in areas such as World Wide Web and Usability. His biological study focuses on Session.
The scientist’s investigation covers issues in Internet privacy, Information retrieval, Social media, Data collection and Public relations. His Internet privacy research integrates issues from Collective identity, Social bonding and Reputation. The Recommender system and Ranking research Paul Resnick does as part of his general Information retrieval study is frequently linked to other disciplines of science, such as Matrix completion, therefore creating a link between diverse domains of science.
His research investigates the connection with Social media and areas like Simple which intersect with concerns in Artificial intelligence. The various areas that Paul Resnick examines in his Data collection study include Framing, Political communication, Innocence, Content analysis and Natural language. Paul Resnick has included themes like Management, Categorization, Politics and Commitment device in his Public relations study.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
GroupLens: an open architecture for collaborative filtering of netnews
Paul Resnick;Neophytos Iacovou;Mitesh Suchak;Peter Bergstrom.
conference on computer supported cooperative work (1994)
Recommender systems
Paul Resnick;Hal R. Varian.
Communications of The ACM (1997)
Reputation systems
Paul Resnick;Ko Kuwabara;Richard Zeckhauser;Eric Friedman.
Communications of The ACM (2000)
Trust among strangers in internet transactions: Empirical analysis of eBay' s reputation system
Paul Resnick;Richard Zeckhauser.
Applied Microeconomics, The Economics of the Internet and E-Commerce (2002)
The value of reputation on eBay: A controlled experiment
Paul Resnick;Richard Zeckhauser;John Swanson;Kate Lockwood.
Experimental Economics (2006)
The Social Cost of Cheap Pseudonyms
Eric J. Friedman;Paul Resnick.
Journal of Economics and Management Strategy (2001)
Building Successful Online Communities: Evidence-Based Social Design
Robert E. Kraut;Paul Resnick;Sara Kiesler;Yuqing Ren.
(2012)
Using Social Psychology to Motivate Contributions to Online Communities
Kimberly S. Ling;Gerard Beenen;Pamela J. Ludford;Xiaoqing Wang.
Journal of Computer-Mediated Communication (2005)
Beyond Bowling Together: SocioTechnical Capital
Paul Resnick.
(2001)
Eliciting Informative Feedback: The Peer-Prediction Method
Nolan Miller;Paul Resnick;Richard Zeckhauser.
Management Science (2005)
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