User Factors in Recommender Systems: Case Studies in e-Commerce, News Recommending, and e-Learning ; Käyttäjänäkökulmia suosittelujärjestelmiin: Tapaustutkimuksia e-kaupasta, uutisten suosittelusta ja e-oppimisesta

[1]  John Riedl,et al.  Tagsplanations: explaining recommendations using tags , 2009, IUI.

[2]  Jonah Berger,et al.  Positive Effects of Negative Publicity: When Negative Reviews Increase Sales , 2009, Mark. Sci..

[3]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[4]  Boi Faltings,et al.  Mechanisms for Making Crowds Truthful , 2014, J. Artif. Intell. Res..

[5]  Lars Schmidt-Thieme,et al.  Tag-aware recommender systems by fusion of collaborative filtering algorithms , 2008, SAC '08.

[6]  Joseph A. Konstan,et al.  Technologies for managing and sharing local information , 2007 .

[7]  Paul Dourish,et al.  Introduction to the special section on recommender systems , 2005, TCHI.

[8]  Bart P. Knijnenburg,et al.  Understanding the effect of adaptive preference elicitation methods on user satisfaction of a recommender system , 2009, RecSys '09.

[9]  Geng Cui,et al.  Terms of Use , 2003 .

[10]  Dwayne D. Gremler,et al.  Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? , 2004 .

[11]  Federica Cena,et al.  The impact of rating scales on user's rating behavior , 2011, UMAP'11.

[12]  Jingjing Zhang.  Anchoring effects of recommender systems , 2011, RecSys '11.

[13]  Sean M. McNee,et al.  Making recommendations better: an analytic model for human-recommender interaction , 2006, CHI Extended Abstracts.

[14]  Friedrich W. Hesse,et al.  I will do it, but i don't like it: user reactions to preference-inconsistent recommendations , 2011, CHI.

[15]  Kristina Höök,et al.  Social navigation: techniques for building more usable systems , 2000, INTR.

[16]  Ling Liu,et al.  Do online reviews affect product sales? The role of reviewer characteristics and temporal effects , 2008, Inf. Technol. Manag..

[17]  Ebru Kiliç-Çakmak,et al.  Learning strategies and motivational factors predicting information literacy self-efficacy of e-learners , 2010 .

[18]  Joseph A. Konstan,et al.  Introduction to recommender systems , 2008, SIGMOD Conference.

[19]  John Riedl,et al.  E-Commerce Recommendation Applications , 2004, Data Mining and Knowledge Discovery.

[20]  Jérôme Dinet,et al.  Information search activity: An overview , 2012 .

[21]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[22]  Ulrike Gretzel,et al.  Persuasion in Recommender Systems , 2006, Int. J. Electron. Commer..

[23]  Bart P. Knijnenburg,et al.  Each to his own: how different users call for different interaction methods in recommender systems , 2011, RecSys '11.

[24]  A. Rubinstein.  Modeling Bounded Rationality , 1998 .

[25]  Wai-Tat Fu,et al.  Semantic imitation in social tagging , 2010, TCHI.

[26]  F. Maxwell Harper,et al.  Social Comparisons to Motivate Contributions to an Online Community , 2007, PERSUASIVE.

[27]  Mimi Recker,et al.  What do you recommend? Implementation and analyses of collaborative information filtering of web resources for education , 2003 .

[28]  Kirsten Swearingen,et al.  Interaction Design for Recommender Systems , 2002 .

[29]  Juha Leino,et al.  Case Study: Material Additions, Ratings, and Comments in a Course Setting , 2012 .

[30]  Hendrik Drachsler,et al.  Recommender Systems in Technology Enhanced Learning , 2011, Recommender Systems Handbook.

[31]  H. Simon,et al.  The sciences of the artificial (3rd ed.) , 1996 .

[32]  Andrew Thatcher,et al.  Information-seeking behaviours and cognitive search strategies in different search tasks on the WWW , 2006 .

[33]  S. Rybak.  Likes and Dislikes , 1996 .

[34]  Gordon I. McCalla,et al.  A Multidimensional Paper Recommender: Experiments and Evaluations , 2009, IEEE Internet Computing.

[35]  Esma Aïmeur,et al.  Harnessing Learner's Collective Intelligence: A Web2.0 Approach to E-Learning , 2008, Intelligent Tutoring Systems.

[36]  Kate Ehrlich,et al.  Pointing the way: active collaborative filtering , 1995, CHI '95.

[37]  M. Geuens,et al.  The Individual Consistency of Acquiescence and Extreme Response Style in Self-Report Questionnaires , 2010 .

[38]  Li Chen,et al.  A user-centric evaluation framework for recommender systems , 2011, RecSys '11.

[39]  Federica Cena,et al.  Synthesis of Collective Tag-Based Opinions in the Social Web , 2011, AI*IA.

[40]  Neil J. Hurley,et al.  Detecting noise in recommender system databases , 2006, IUI '06.

[41]  Abhinandan Das,et al.  Google news personalization: scalable online collaborative filtering , 2007, WWW '07.

[42]  Mouzhi Ge,et al.  Understanding Recommendations by Reading the Clouds , 2011, EC-Web.

[43]  Nigel Bevan,et al.  What is the difference between the purpose of usability and user experience evaluation methods , 2009 .

[44]  Jiahui Liu,et al.  Personalized news recommendation based on click behavior , 2010, IUI '10.

[45]  Mor Naaman,et al.  HT06, tagging paper, taxonomy, Flickr, academic article, to read , 2006, HYPERTEXT '06.

[46]  Lars Schmidt-Thieme,et al.  Collaborative Tag Recommendations , 2007, GfKl.

[47]  John Riedl,et al.  Recommender systems in e-commerce , 1999, EC '99.

[48]  Bart P. Knijnenburg.  Conducting user experiments in recommender systems , 2012, RecSys.

[49]  Nor Aniza Abdullah,et al.  Learning materials recommendation using good learners’ ratings and content-based filtering , 2010 .

[50]  James D. Hollan,et al.  Edit wear and read wear , 1992, CHI.

[51]  Rashmi R. Sinha,et al.  The role of transparency in recommender systems , 2002, CHI Extended Abstracts.

[52]  John Riedl,et al.  Recommender systems: from algorithms to user experience , 2012, User Modeling and User-Adapted Interaction.

[53]  B. Kushner.  Descartes' error. , 1998, Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus.

[54]  Ion Juvina,et al.  Predicting user preferences: from semantic to pragmatic metrics of Web navigation behavior , 2004 .

[55]  Franca Garzotto,et al.  User-Centric vs. System-Centric Evaluation of Recommender Systems , 2013, INTERACT.

[56]  Robin D. Burke,et al.  Hybrid Web Recommender Systems , 2007, The Adaptive Web.

[57]  Tsvi Kuflik,et al.  Evaluating rating scales personality , 2012, UMAP.

[58]  Hendrik Drachsler,et al.  Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning , 2009, J. Digit. Inf..

[59]  Robert F. Easley,et al.  A SURVEY OF RECOMMENDATION SYSTEMS IN ELECTRONIC COMMERCE , 2001 .

[60]  Catholijn M. Jonker,et al.  Towards Compositional Design and Evaluation of Preference Elicitation Interfaces , 2011, HCI.

[61]  Kari-Jouko Räihä,et al.  User Experiences and Impressions of Recommenders in Complex Information Environments , 2008, IEEE Data Eng. Bull..

[62]  Kipling D. Williams,et al.  PROCESSES Social Loafing: A Meta-Analytic Review and Theoretical Integration , 2022 .

[63]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[64]  I. Vermeir,et al.  The influence of need for closure on consumer's choice behaviour , 2002 .

[65]  Oded Nov,et al.  Why do people tag? , 2010, Commun. ACM.

[66]  Franca Garzotto,et al.  Looking for "Good" Recommendations: A Comparative Evaluation of Recommender Systems , 2011, INTERACT.

[67]  Valerie J. Trifts,et al.  Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids , 2000 .

[68]  P. K. Kannan,et al.  E-Service: New Directions in Theory and Practice , 2002 .

[69]  Robert E. Kraut,et al.  Motivating participation by displaying the value of contribution , 2006, CHI.

[70]  Juha Leino,et al.  Recommending additional study materials: binary ratings vis-à-vis five-star ratings , 2013, BCS HCI.

[71]  Pieter H. Hartel,et al.  Privacy in Recommender Systems , 2013, Social Media Retrieval.

[72]  T Kippenberger.  Giving it away for free , 2000 .

[73]  Pierre Sens,et al.  Stream Processing of Healthcare Sensor Data: Studying User Traces to Identify Challenges from a Big Data Perspective , 2015, ANT/SEIT.

[74]  Fatih Gedikli.  Rating items by rating tags , 2010 .

[75]  Gordon I. McCalla,et al.  Beyond Learners' Interest: Personalized Paper Recommendation Based on Their Pedagogical Features for an e-Learning System , 2004, PRICAI.

[76]  Vannevar Bush,et al.  As we may think , 1945, INTR.

[77]  Bradley N. Miller,et al.  GroupLens: applying collaborative filtering to Usenet news , 1997, CACM.

[78]  Izak Benbasat,et al.  Research Note: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites , 2006, Inf. Syst. Res..

[79]  John Riedl,et al.  Is seeing believing?: how recommender system interfaces affect users' opinions , 2003, CHI '03.

[80]  Mark P. Graus,et al.  Understanding choice overload in recommender systems , 2010, RecSys '10.

[81]  Amnon Meisels,et al.  Ensemble methods for improving the performance of neighborhood-based collaborative filtering , 2009, RecSys '09.

[82]  Stefania Kalogeraki.  The Divergence Hypothesis in Modernization Theory Across Three European Countries: the UK, Sweden and Greece , 2009 .

[83]  Jürgen Buder,et al.  Learning with personalized recommender systems: A psychological view , 2012, Comput. Hum. Behav..

[84]  Peter Brusilovsky,et al.  Social Navigation Support in a Course Recommendation System , 2006, AH.

[85]  Antonia Stefani,et al.  Behavioral Patterns in Hypermedia Systems: A Short Study of E-commerce vs. E-learning Practices , 2006, Adaptive and Personalized Semantic Web.

[86]  Jun Yang,et al.  Experiential goods with network externalities effects: An empirical study of online rating system , 2010 .

[87]  Lázaro Rodríguez Ariza,et al.  Blended learning in higher education: Students' perceptions and their relation to outcomes , 2011, Comput. Educ..

[88]  Shawn P. Curley,et al.  Do Recommender Systems Manipulate Consumer Preferences? A Study of Anchoring Effects , 2013, Inf. Syst. Res..

[89]  D. Garrison,et al.  Blended learning: Uncovering its transformative potential in higher education , 2004, Internet High. Educ..

[90]  Kristina Lerman,et al.  Information Contagion: An Empirical Study of the Spread of News on Digg and Twitter Social Networks , 2010, ICWSM.

[91]  Christian Gütl,et al.  E-Learning practices and Web 2.0 , 2007 .

[92]  Vance L. Martin,et al.  Latent Factor Models , 2012 .

[93]  David Schuff,et al.  What Makes a Helpful Review? A Study of Customer Reviews on Amazon.com , 2010 .

[94]  Roberto Turrin,et al.  Do Metrics Make Recommender Algorithms? , 2009, 2009 International Conference on Advanced Information Networking and Applications Workshops.

[95]  Paul A. Pavlou,et al.  Overcoming the J-shaped distribution of product reviews , 2009, CACM.

[96]  Liviu Iftode,et al.  News Posting by Strategic Users in a Social Network , 2009, WINE.

[97]  John Riedl,et al.  Tagommenders: connecting users to items through tags , 2009, WWW '09.

[98]  Loren G. Terveen,et al.  Crafting the initial user experience to achieve community goals , 2008, RecSys '08.

[99]  M. Matteucci,et al.  An Evaluation Methodology for Collaborative Recommender Systems , 2008, 2008 International Conference on Automated Solutions for Cross Media Content and Multi-Channel Distribution.

[100]  Andreas Hotho,et al.  Tag Recommendations in Folksonomies , 2007, LWA.

[101]  Sean M. McNee,et al.  Interfaces for Eliciting New User Preferences in Recommender Systems , 2003, User Modeling.

[102]  D. Kahneman.  Thinking, Fast and Slow , 2011 .

[103]  Alfred Kobsa,et al.  Privacy-Enhanced Web Personalization , 2007, The Adaptive Web.

[104]  Juan M. Fernández-Luna,et al.  Top-N news recommendations in digital newspapers , 2012, Knowl. Based Syst..

[105]  Alfred Kobsa,et al.  A pragmatic procedure to support the user-centric evaluation of recommender systems , 2011, RecSys '11.

[106]  Paul A. Pavlou,et al.  Can online reviews reveal a product's true quality?: empirical findings and analytical modeling of Online word-of-mouth communication , 2006, EC '06.

[107]  Matthew K. O. Lee,et al.  What drives consumers to spread electronic word of mouth in online consumer-opinion platforms , 2012, Decis. Support Syst..

[108]  Bernardo A. Huberman,et al.  Usage patterns of collaborative tagging systems , 2006, J. Inf. Sci..

[109]  Mark Rosenstein,et al.  Recommending and evaluating choices in a virtual community of use , 1995, CHI '95.

[110]  N. Schwarz.  Metacognitive Experiences in Consumer Judgment and Decision Making , 2004 .

[111]  Marina Krakovsky.  All the news that's fit for you , 2011, CACM.

[112]  Chrysanthos Dellarocas,et al.  Harnessing Crowds: Mapping the Genome of Collective Intelligence , 2009 .

[113]  John Riedl,et al.  Explaining collaborative filtering recommendations , 2000, CSCW '00.

[114]  Greg Linden,et al.  Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .

[115]  Michael S. Bernstein,et al.  Enhancing directed content sharing on the web , 2010, CHI.

[116]  John Riedl,et al.  An algorithmic framework for performing collaborative filtering , 1999, SIGIR '99.

[117]  R. Garland.  The Mid-Point on a Rating Scale: Is it Desirable? , 1991 .

[118]  Jae Kyeong Kim,et al.  A literature review and classification of recommender systems research , 2012, Expert Syst. Appl..

[119]  Sanda Erdelez,et al.  Sharing tools on newspaper Web sites: an exploratory study , 2000, Online Inf. Rev..

[120]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[121]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

[122]  H. Simon,et al.  A Behavioral Model of Rational Choice , 1955 .

[123]  Sandra Clara Gadanho,et al.  Addressing uncertainty in implicit preferences , 2007, RecSys '07.

[124]  Till Plumbaum,et al.  Users and noise: the magic barrier of recommender systems , 2012, UMAP.

[125]  Ioannis Konstas,et al.  On social networks and collaborative recommendation , 2009, SIGIR.

[126]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[127]  Izak Benbasat,et al.  The Effects of Personalizaion and Familiarity on Trust and Adoption of Recommendation Agents , 2006, MIS Q..

[128]  Bart P. Knijnenburg,et al.  Explaining the user experience of recommender systems , 2012, User Modeling and User-Adapted Interaction.

[129]  Andreas Thor,et al.  Adaptive website recommendations with AWESOME , 2005, The VLDB Journal.

[130]  Dan Frankowski,et al.  Collaborative Filtering Recommender Systems , 2007, The Adaptive Web.

[131]  Pradeep Racherla,et al.  Perceived 'usefulness' of online consumer reviews: An exploratory investigation across three services categories , 2012, Electron. Commer. Res. Appl..

[132]  Sally I. McClean,et al.  Collaborative Filtering: The Aim of Recommender Systems and the Significance of User Ratings , 2010, ECIR.

[133]  Sarabjot Singh Anand,et al.  Personalised Tag Recommendation , 2009 .

[134]  Paul Dourish,et al.  Running Out of Space: Models of Information Navigation , 1999 .

[135]  Olga C. Santos,et al.  Users' Experience with a Recommender System in an Open Source Standard-Based Learning Management System , 2008, USAB.

[136]  John Riedl,et al.  tagging, communities, vocabulary, evolution , 2006, CSCW '06.

[137]  Catherine Berrut,et al.  Improving new user recommendations with rule-based induction on cold user data , 2007, RecSys '07.

[138]  Lee Rainie.  A Biography of the Pew Research Center’s Internet & American Life Project , 2012 .

[139]  Vijay Mahajan,et al.  The Economic Leverage of the Virtual Community , 2001, Int. J. Electron. Commer..

[140]  Yi-Fen Chen,et al.  Herd behavior in purchasing books online , 2008, Comput. Hum. Behav..

[141]  J. Alió,et al.  Beauty is truth, truth beauty. , 2005, Journal of refractive surgery.

[142]  Alexandru Tupan,et al.  Triangulation , 1997, Comput. Vis. Image Underst..

[143]  Juha Leino,et al.  Searches and Recommendations: Item-finding in Complex Information Environments , 2008 .

[144]  Kristina Höök,et al.  Social Navigation and Seamful Design (特集 ソーシャルナビゲーション) , 2004 .

[145]  Elizabeth Sillence,et al.  Please advise: using the Internet for health and financial advice , 2007, Comput. Hum. Behav..

[146]  Boon Chong Lim,et al.  Word-of-mouth: The use of source expertise in the evaluation of familiar and unfamiliar brands , 2014 .

[147]  Andreas Dieberger,et al.  Supporting social navigation on the World Wide Web , 1997, Int. J. Hum. Comput. Stud..

[148]  Marc Hassenzahl,et al.  User experience - a research agenda , 2006, Behav. Inf. Technol..

[149]  Graham I. Johnson,et al.  User experience at NCR: an organisational overview , 2010, BCS HCI.

[150]  Pearl Pu,et al.  Recommenders' influence on buyers' decision process , 2009, RecSys '09.

[151]  Rajiv Vaidyanathan,et al.  Eliciting Online Customers’ Preferences: Conjoint vs Self-Explicated Attribute-Level Measurements , 2003 .

[152]  Andrina Granic,et al.  User sensitive research in e-learning: exploring the role of individual user characteristics , 2011, Universal Access in the Information Society.

[153]  Kristina Lerman,et al.  Dynamics of collaborative document rating systems , 2007, WebKDD/SNA-KDD '07.

[154]  Rong Hu,et al.  Enhancing recommendation diversity with organization interfaces , 2011, IUI '11.

[155]  Catholijn M. Jonker,et al.  Designing interfaces for explicit preference elicitation: a user-centered investigation of preference representation and elicitation process , 2011, User Modeling and User-Adapted Interaction.

[156]  Valentin Robu,et al.  The complex dynamics of collaborative tagging , 2007, WWW '07.

[157]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[158]  Federica Cena,et al.  Towards a Customization of Rating Scales in Adaptive Systems , 2010, UMAP.

[159]  A. Bryman,et al.  The Sage Encyclopedia of Social Science Research Methods (three volumes) , 2003 .

[160]  Bamshad Mobasher,et al.  Introduction to intelligent techniques for Web personalization , 2007, TOIT.

[161]  Taghi M. Khoshgoftaar,et al.  A Survey of Collaborative Filtering Techniques , 2009, Adv. Artif. Intell..

[162]  Steve SangKi Han,et al.  Qtag: tagging as a means of rating, opinion-expressing, sharing and visualizing , 2007, SIGDOC '07.

[163]  Sean M. McNee,et al.  Getting to know you: learning new user preferences in recommender systems , 2002, IUI '02.

[164]  Kari-Jouko Räihä,et al.  Case amazon: ratings and reviews as part of recommendations , 2007, RecSys '07.

[165]  Franca Garzotto,et al.  User effort vs. accuracy in rating-based elicitation , 2012, RecSys.

[166]  Ram D. Gopal,et al.  Empirical Analysis of the Impact of Recommender Systems on Sales , 2010, J. Manag. Inf. Syst..

[167]  Gediminas Adomavicius,et al.  Context-aware recommender systems , 2008, RecSys '08.

[168]  Franca Garzotto,et al.  Investigating the Persuasion Potential of Recommender Systems from a Quality Perspective: An Empirical Study , 2012, TIIS.

[169]  Li Chen,et al.  Evaluating recommender systems from the user’s perspective: survey of the state of the art , 2012, User Modeling and User-Adapted Interaction.

[170]  Sean M. McNee,et al.  Being accurate is not enough: how accuracy metrics have hurt recommender systems , 2006, CHI Extended Abstracts.

[171]  Izak Benbasat,et al.  E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact , 2007, MIS Q..

[172]  Juha Leino,et al.  Case study: recommending course reading materials in a small virtual learning community , 2012, Int. J. Web Based Communities.

[173]  Li Chen,et al.  Understanding buyers' social information needs during purchase decision process , 2010, ICEC '10.

[174]  Kristina Höök,et al.  Designing and evaluating kalas: A social navigation system for food recipes , 2005, TCHI.

[175]  Kirsten Swearingen,et al.  Beyond Algorithms: An HCI Perspective on Recommender Systems , 2001 .

[176]  Barry Smyth,et al.  Collecting community wisdom: integrating social search & social navigation , 2007, IUI '07.

[177]  Petri Nokelainen,et al.  Practical Considerations of Motivation and Computer-supported Collaborative Learning , 2003 .

[178]  Dianne Cyr,et al.  The role of social presence in establishing loyalty in e-Service environments , 2007, Interact. Comput..

[179]  Monic Sun,et al.  How Does the Variance of Product Ratings Matter? , 2010, Manag. Sci..

[180]  Paul Dourish,et al.  Re-place-ing space: the roles of place and space in collaborative systems , 1996, CSCW '96.

[181]  Andreas W. Neumann,et al.  Motivating and Supporting User Interaction with Recommender Systems , 2007, ECDL.

[182]  Peter Comber,et al.  BBC News Online , 2002 .

[183]  Piet Van Mieghem,et al.  Are friends overrated? A study for the social news aggregator Digg.com , 2012, Comput. Commun..

[184]  Gordon I. McCalla,et al.  Utilizing Artificial Learners to Help Overcome the Cold-Start Problem in a Pedagogically-Oriented Paper Recommendation System , 2004, AH.

[185]  F. Maxwell Harper,et al.  An Economic Model of User Rating in an Online Recommender System , 2005, User Modeling.

[186]  Xin Li,et al.  Using Social Psychology to Motivate Contributions to Online Communities , 2005, J. Comput. Mediat. Commun..

[187]  Jimmy J. Lin,et al.  WTF: the who to follow service at Twitter , 2013, WWW.

[188]  R. Gottlieb,et al.  The New Yorker , 1987 .

[189]  Lior Rokach,et al.  Taxonomy for characterizing ensemble methods in classification tasks: A review and annotated bibliography , 2009, Comput. Stat. Data Anal..

[190]  John Riedl,et al.  How many bits per rating? , 2012, RecSys.

[191]  John Riedl,et al.  Shilling recommender systems for fun and profit , 2004, WWW '04.

[192]  Loren Terveen,et al.  Beyond Recommender Systems: Helping People Help Each Other , 2001 .

[193]  Boi Faltings,et al.  Understanding user behavior in online feedback reporting , 2007, EC '07.

[194]  J. Bobadilla,et al.  Recommender systems survey , 2013, Knowl. Based Syst..

[195]  John Riedl,et al.  How oversight improves member-maintained communities , 2005, CHI.

[196]  Peter Brusilovsky,et al.  Adaptive Navigation Support , 2007, The Adaptive Web.

[197]  Sean M. McNee,et al.  Improving recommendation lists through topic diversification , 2005, WWW '05.

[198]  A. Ant Ozok,et al.  Design guidelines for effective recommender system interfaces based on a usability criteria conceptual model: results from a college student population , 2010, Behav. Inf. Technol..

[199]  Nava Tintarev,et al.  Rate it again: increasing recommendation accuracy by user re-rating , 2009, RecSys '09.

[200]  John Riedl,et al.  Do You Trust Your Recommendations? An Exploration of Security and Privacy Issues in Recommender Systems , 2006, ETRICS.

[201]  Tim Harford,et al.  The Undercover Economist , 2005 .

[202]  N. Schwarz.  Self-reports: How the questions shape the answers. , 1999 .

[203]  Kari-Jouko Räihä,et al.  All the News That's Fit to Read: Finding and Recommending News Online , 2011, INTERACT.

[204]  Shilad Sen,et al.  Rating: how difficult is it? , 2011, RecSys '11.

[205]  Olga C. Santos,et al.  Modeling recommendations for the educational domain , 2010, RecSysTEL@RecSys.

[206]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[207]  Cliff Lampe,et al.  The Benefits of Facebook "Friends: " Social Capital and College Students' Use of Online Social Network Sites , 2007, J. Comput. Mediat. Commun..

[208]  Tomi Heimonen,et al.  Improving Evaluation Honesty and User Experience in E-learning by Increasing Evaluation Cost and Social Presence , 2013, INTERACT.