Looking for Genre: The Use of Structural Features During Search Tasks with Wikipedia

Malcolm Clark, Ian Ruthven, Patrik O'Brian Holt, Dawei Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


This paper reports on our task-based observational, logged, questionnaire study and analysis of ocular behavior pertaining to the interaction of structural features of text in Wikipedia using eye tracking. We set natural and realistic tasks searching Wikipedia online focusing on examining which features and strategies (skimming or scanning) were the most important for the participants to complete their tasks. Our research, carried out on a group of 30 participants, highlighted their interactions with the structural areas within Wikipedia articles, the visual cues and features perceived during the searching of the Wiki text. We collected questionnaire and ocular behavior (fixation metrics) data to highlight the ways in which people view the features in the articles. We found that our participants' extensively interacted with layout features, such as tables, titles, bullet lists, contents lists, information boxes, and references. The eye tracking results showed that participants used the format and layout features and they also highlighted them as important. They were able to navigate to useful information consistently, and they were an effective means of locating relevant information for the completion of their tasks with some success. This work presents results which contribute to the long-term goals of studying the features for genre and theoretical perception research.
Original languageEnglish
Title of host publicationProceedings of the 4th Information Interaction in Context Symposium
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Print)9781450312820
Publication statusPublished - 2012

Publication series

NameIIIX '12


  • perception
  • skimming
  • scanning
  • text
  • genre
  • Wikipedia
  • Eye tracking
  • Features


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