Interface Design to Mitigate Inflation in Recommender Systems

Author:

Shahout Rana1ORCID,Peisakhovsky Yehonatan2ORCID,Stoikov Sasha3ORCID,Garg Nikhil3ORCID

Affiliation:

1. Computer Science, Harvard University, USA

2. Technion, Israel

3. Cornell Tech, USA

Publisher

ACM

Reference25 articles.

1. Gediminas Adomavicius , Jesse Bockstedt , Shawn Curley , and Jingjing Zhang . 2011 . Recommender systems, consumer preferences, and anchoring effects . In RecSys 2011 workshop on human decision making in recommender systems. 35–42 . Gediminas Adomavicius, Jesse Bockstedt, Shawn Curley, and Jingjing Zhang. 2011. Recommender systems, consumer preferences, and anchoring effects. In RecSys 2011 workshop on human decision making in recommender systems. 35–42.

2. Mary  J Allen and Wendy  M Yen . 2001. Introduction to measurement theory . Waveland Press . Mary J Allen and Wendy M Yen. 2001. Introduction to measurement theory. Waveland Press.

3. Arslan Aziz , Hui Li , and Rahul Telang . 2020. The Consequences of Rating Inflation on Platforms: Evidence from a Quasi-Experiment. SSRN Electronic Journal ( 2020 ). Arslan Aziz, Hui Li, and Rahul Telang. 2020. The Consequences of Rating Inflation on Platforms: Evidence from a Quasi-Experiment. SSRN Electronic Journal (2020).

4. John Bound , Charles Brown , and Nancy Mathiowetz . 2001. Measurement error in survey data . In Handbook of econometrics. Vol. 5 . Elsevier , 3705–3843. John Bound, Charles Brown, and Nancy Mathiowetz. 2001. Measurement error in survey data. In Handbook of econometrics. Vol. 5. Elsevier, 3705–3843.

5. M Claypool , P Le , M Wased , 2001. Implicit interest indicators [C]. In ; Proce of the IUI’ 01. M Claypool, P Le, M Wased, 2001. Implicit interest indicators [C]. In; Proce of the IUI’01.

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