title: Confirmation bias in web-based search: a randomized online study on the effects of expert information and social tags on information search and evaluation.
abstract: BACKGROUND
  The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective.
  
  
  OBJECTIVE
  The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts' evaluations.
  
  
  METHODS
  A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts' blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants' treatment recommendation after information search.
  
  
  RESULTS
  Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; t173=7.67, P<.001, d=0.81) when rating treatment efficacy prior to the experiment. Accordingly, participants exhibited biased information search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (F2,168=10.61, P<.001, partial eta squared=0.112), blog post selection (F2,168=6.55, P=.002, partial eta squared=0.072), and treatment efficacy ratings (F2,168=8.48, P<.001, partial eta squared=0.092), compared to bias-supporting tag clouds (n=56) and balanced tag clouds (n=57). Challenging (n=93) explicit expert information as presented in blog posts, compared to supporting expert information (n=81), decreased the bias in information search with regard to blog post selection (F1,168=4.32, P=.04, partial eta squared=0.025). No significant effects were found for treatment recommendation (Ps>.33).
  
  
  CONCLUSIONS
  We conclude that the psychotherapy bias is most effectively attenuated-and even eliminated-when popular tags implicitly point to blog posts that challenge the widespread view. Explicit expert information (in a blog entry) was less successful in reducing biased information search and evaluation. Since tag clouds have the potential to counter biased information processing, we recommend their insertion.
authors.affiliation: Knowledge Media Research Center, Tuebingen, Germany. s.schweiger@iwm-kmrc.de.
authors.forename: Stefan
authors.initials: S
authors.lastname: Schweiger
authors.forename: Aileen
authors.initials: A
authors.lastname: Oeberst
authors.forename: Ulrike
authors.initials: U
authors.lastname: Cress
mesh_terms: D001294:Attitude to Health; D015982:Bias; D057218:Blogging; D003863:Depression / Q000188:drug therapy / Q000628:therapy*; D005260:Female; D006801:Humans; D057226:Information Seeking Behavior; D008297:Male; D008875:Middle Aged; D011613:Psychotherapy; D016896:Treatment Outcome
keywords: Web-based systems; collaborative tagging; folksonomy; human information processing; pharmacotherapy; prejudice; psychotherapy; taxonomy