Trust Modeling in Social Media Tagging

Photo: Terry Johnston, powerbooktrance/Flickr


One important challenge in tagging is to identify most appropriate tags for given content, and at the same time, to eliminate noisy or spam tags. The shared content is sometimes assigned with inappropriate tags for several reasons. First of all, users are human beings and may commit mistakes. Moreover, it is possible to provide wrong tags on purpose for advertisement, self-promotion, or to increase the rank of a particular tag in automatic search engines. Consequently, assigning free-form keywords (tags) to multimedia content has a risk that wrong or irrelevant tags eventually prevent users from the benefits of annotated content. Some studies analyzed the Flickr website and revealed that the tags provided by users are often imprecise and only around 50% of tags are truly related to an image. Beside the tag-content association, spam objects can take other forms, i.e. possibly manifesting as a spam content or a spam user (spammer).

Trust modeling is required to keep a system free of noise and spam. We proposed an approach for user trust modeling in a system for automatic geotag propagation in images. We considered the geotagging scenario, because it is nowadays a very popular application due to the fact that a large portion of Internet images in social networks are related to travel. In tag propagation, trust modeling is especially crucial because propagating a wrong/spam tag can easily damage the integrity and reliability of the whole system. A user trust modeling derived for each user is introduced in the geotagging system by making use of the feedbacks from other users who agree or disagree with a tag associated with an image, so that only reliable geotags are propagated. It was shown that the proposed user trust model can be generalized to photo sharing platforms, such as Panoramio or Flickr.


  • Geotag propagation based on user trust modeling (published in MTAP) [paper] [slides]
  • In tags we trust: Trust modeling in social tagging of multimedia content (published in IEEE SPM) [paper]
  • Spam fighting in social tagging systems (presented at SOCINFO’12) [paper]
  • Geotag propagation with user trust modeling (published in Springer SMR book) [paper]
  • Comparative study of trust modeling for automatic landmark tagging (published in IEEE TIFS) [paper]