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Predicting the perceived quality of online mathematics contributions from users' reputations

Published: 07 May 2011 Publication History

Abstract

There are two perspectives on the role of reputation in collaborative online projects such as Wikipedia or Yahoo! Answers. One, user reputation should be minimized in order to increase the number of contributions from a wide user base. Two, user reputation should be used as a heuristic to identify and promote high quality contributions. The current study examined how offline and online reputations of contributors affect perceived quality in MathOverflow, an online community with 3470 active users. On MathOverflow, users post high-level mathematics questions and answers. Community members also rate the quality of the questions and answers. This study is unique in being able to measure offline reputation of users. Both offline and online reputations were consistently and independently related to the perceived quality of authors' submissions, and there was only a moderate correlation between established offline and newly developed online reputation.

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cover image ACM Conferences
CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
May 2011
3530 pages
ISBN:9781450302289
DOI:10.1145/1978942
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 May 2011

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Author Tags

  1. community question-answering
  2. information quality
  3. online reputation

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CHI '11 Paper Acceptance Rate 410 of 1,532 submissions, 27%;
Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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  • (2023)Identification and Characterization of Spammers from Lists of Recipients2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)10.1109/ACCAI58221.2023.10200212(1-7)Online publication date: 25-May-2023
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  • (2020)You Get What You Pay for on Health Care Question and Answer Platforms: Nonparticipant Observational StudyJournal of Medical Internet Research10.2196/1353422:1(e13534)Online publication date: 15-Jan-2020
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