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Comparing Recommendations Made by Online Systems and Friends

Comparing Recommendations Made by Online Systems and Friends,Rashmi R. Sinha,Kirsten Swearingen

Comparing Recommendations Made by Online Systems and Friends   (Citations: 89)
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The quality of recommendations and usability of six online rec ommender systems (RS) was examined. Three book RS (Amazon.com, RatingZone & Sleeper) and three movie RS (Amazon.com, MovieCritic, Reel.com) were evaluated. Quality of recommendations was explored by comparing recommendations made by RS to recommendatio ns m ade by the user's friends. Results showed that the user's friends consistently provided better recommendations than RS. However, users did find items recommended by online RS useful: recommended items were often "new" and "unexpected", while the items recommended by friends mostly served as reminders of previously identified interests. Usability evaluation of the RS showed that users did not mind providing more input to the system in order to get better recommendations. Also users trusted a system more if it recommended items that they had previously liked.
Conference: DELOS Workshops , 2001
Cumulative Annual
    • ...Sinha and Swearingen (2001) and Swearingen and Sinha (2001) show that users trust recommendations from friends more than from systems...

    G. Canforaet al. Managing Trust in Social Networks

    • ...Research has pointed out that people tend to rely more on recommendations from people they trust (friends) than on online recommender systems which generate recommendations based on anonymous people similar to them [57]...
    • ...Finally, Sinha and Swearingen [57, 58] have shown that users prefer more transparent systems, and that people tend to rely more on recommendations from people they trust (‘friends’) than on online recommender systems which generate recommendations based on anonymous people similar to them...

    Patricia Victoret al. Trust and Recommendations

    • ...The recommendations of friends also are more trustworthy than those of the system [28].In addition, Golbeck showed that users prefer recommendations from trusted people [6].One of reasons why users prefer friends’ recommendationscan be found in Singla& Richardson’s study [27]...

    Danielle H. Leeet al. Improving recommendations using WatchingNetworks in a social tagging s...

    • ...Several studies suggest incorporating explicit social network information in CF systems to improve the quality of recommendation in domains such as movies and books (e.g., [3,12,30]), music [20], clubs [14], and news stories [21]...

    Ido Guyet al. Social media recommendation based on people and tags

    • ...recommenders most useful when they recommend unexpected items [4]; highlighting the...

    Rana Forsatiet al. Effective page recommendation algorithms based on distributed learning...

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