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Information Reputation, Ratings, and Quality on the Web

Information Reputation, Ratings, and Quality on the Web. Nick Diakopoulos | nad@cc.gatech.edu School of Interactive Computing. Reputation, Ratings, Recommender Systems. Amazon.com Movielens.org (U Minnesota) Digg.com Slashdot.com Newstrust.net. Reputation, Ratings, Recommender Systems.

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Information Reputation, Ratings, and Quality on the Web

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  1. Information Reputation, Ratings, and Quality on the Web Nick Diakopoulos | nad@cc.gatech.edu School of Interactive Computing

  2. Reputation, Ratings, Recommender Systems • Amazon.com • Movielens.org (U Minnesota) • Digg.com • Slashdot.com • Newstrust.net

  3. Reputation, Ratings, Recommender Systems • Datatypes: numeric, text, tags • Explicit / Implicit • Manual / Automatic (content based) • Anonymous? Blind review? • Aggregation of Evaluations • Timescale, type of content • Incentives for honest contribution: money, influence, fun, somatic? • Impact of liars • Transparency of rating system • Paul Resnick and Hal Varian. Recommender Systems. CACM March 1997. • Thomas Adler, Luca de Alfaro. A Content-Driven Reputation System for the Wikipedia. WWW 2007. • Sonja Buchegger et al. Reputation Systems for Self-Organized Networks. IEEE Technology and Society. Spring 2008.

  4. Properties and Limitations • Temporal Information Dynamics • Takes time, sparse ratings, early influencers • Effect of visibility of rating, rater’s identity • Polarization • Information Cascades • Non-disclosure

  5. Information Quality and Reputation • Computational Journalism • Journalism as a discipline of verification, providing quality information to public • Importance of reputation in computing credibility and trust

  6. Information Quality Facets • Accurate • Free of mistakes, exact • Reliable and Credible • Consistent, dependable / trustworthy, expert • Valid • Justifiable, logically correct • Techniques • Corroboration / fact-checking / triangulation, falsifying evidence / sources, chains of evidence • Other concepts from journalism: balance, context, evidence, fairness, importance, sources, trust, style

  7. Information Quality Facets • Sources • Documents: name, author, link, publication, trust • Entities: name, expertise, trust • Claims • Claimant, belief, subjectivity, inaccuracy, bad assumptions • Free text comments • Tags: omitted info, context needed, omitted information, stereotyping,

  8. Information Quality in Video • Survey need • 89% reads comments, but 63% think comments are not valuable • Need ability to filter comments • Multimedia: transcript + video + annotations • Much more complex interface • Easy to get cluttered • Granularity

  9. Videolyzer • Video Overview

  10. Videolyzer • Moving towards a ratings SYSTEM • Dynamics of ratings between people • Micro-Vetting • Each rating / comment on the video sent to 1-3 other people in the system for evaluation of ITS quality • Chains of ratings (triangulation / corroboration) • “Rounds of ratings” in a game like fashion • Scoring?

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