Understanding experts' and novices' expertise judgment of Twitter users

Q. Vera Liao, Claudia Wagner, Peter Pirolli, Wai Tat Fu

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


Judging topical expertise of micro-blogger is one of the key challenges for information seekers when deciding which information sources to follow. However, it is unclear how useful different types of information are for people to make expertise judgments and to what extent their background knowledge influences their judgments. This study explored differences between experts and novices in inferring expertise of Twitter users. In three conditions, participants rated the level of expertise of users after seeing (1) only the tweets, (2) only the contextual information including short biographical and user list information, and (3) both tweets and contextual information. Results indicated that, in general, contextual information provides more useful information for making expertise judgment of Twitter users than tweets. While the addition of tweets seems to make little difference, or even add nuances to novices' expertise judgment, experts' judgments were improved when both content and contextual information were presented.

Original languageEnglish (US)
Title of host publicationConference Proceedings - The 30th ACM Conference on Human Factors in Computing Systems, CHI 2012
Number of pages4
StatePublished - 2012
Externally publishedYes
Event30th ACM Conference on Human Factors in Computing Systems, CHI 2012 - Austin, TX, United States
Duration: May 5 2012May 10 2012

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


Other30th ACM Conference on Human Factors in Computing Systems, CHI 2012
Country/TerritoryUnited States
CityAustin, TX


  • Expertise judgment
  • Recommendation system
  • Twitter

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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