Learning and incentives in user-generated content: Multi-armed bandits with endogenous arms

ITCS 2013 - Proceedings of the 2013 ACM Conference on Innovations in Theoretical Computer Science

Volumn , Issue , 2013, Pages 233-246

  Ghosh, Arpita ^a   Hummel, Patrick ^b  

^a Cornell University ^*  (United States)

^b GOOGLE INC   (United States)

Author keywords

attention economics; endogenous arms; game theory; multi armed bandits; quality of online content; user generated content (UGC)

Indexed keywords

ENDOGENOUS ARMS; ERROR PRONES; HIGH QUALITY; LOW QUALITIES; MODIFIED MECHANISM; MULTI ARMED BANDIT; MULTI-ARMED BANDIT PROBLEM; ON-LINE CONTENTS; RELATIVE QUALITIES; SUBLINEAR; USER-GENERATED CONTENT;

COMPUTER SCIENCE; GAME THEORY; STATISTICS;

LEARNING ALGORITHMS;

EID: 84873376815     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2422436.2422465     Document Type: Conference Paper

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