Leveraging position bias to improve peer recommendation. Lerman, K. & Hogg, T. PLoS One, 9(6):e98914, 2014.
Leveraging position bias to improve peer recommendation [link]Paper  Leveraging position bias to improve peer recommendation [link]Blog  abstract   bibtex   71 downloads  
With the advent of social media and peer production, the amount of new online content has grown dramatically. To identify interesting items in the vast stream of new content, providers must rely on peer recommendation to aggregate opinions of their many users. Due to human cognitive biases, the presentation order strongly affects how people allocate attention to the available content. Moreover, we can manipulate attention through the presentation order of items to change the way peer recommendation works. We experimentally evaluate this effect using Amazon Mechanical Turk. We find that different policies for ordering content can steer user attention so as to improve the outcomes of peer recommendation.
@ARTICLE{Lerman14plosone,
  AUTHOR =       {Kristina Lerman and Tad Hogg},
  TITLE =        {Leveraging position bias to improve peer recommendation},
  JOURNAL =      {PLoS One},
  YEAR =         {2014},
  volume =       {9},
  number =       {6},
  pages =        {e98914},
  url = {http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0098914},
  urlBlog={http://crowdresearch.org/blog/?p=8881},
  abstract =     {With the advent of social media and peer production, the amount of new online content has grown dramatically. To identify interesting items in the vast stream of new content, providers must rely on peer recommendation to aggregate opinions of their many users. Due to human cognitive biases,  the presentation order strongly affects how people allocate attention to the available content. Moreover, we can manipulate attention through the presentation order of items to change the way peer recommendation works. We experimentally evaluate this effect using Amazon Mechanical Turk.
We find that different policies for ordering content can steer user attention so as to improve the outcomes of peer recommendation.
},
  keywords =     {social-dynamics},
}

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