Understanding Health Information Intent via Crowdsourcing: Challenges and Opportunities
Author(s)
Lu, Di
Lu, Yihan
Jeng, Wei
Farzan, Rosta
Lin, Yu-Ru
Issue Date
2015-03-15
Keyword(s)
human information behavior
health informtics
Abstract
Social Q&A sites have been emerging as a platform for people to seek information and social supports around health topics. Identifying users’ information needs from the questions can significantly help social Q&A sites serve their users better. Prior research had attempted to understand askers’ intentions and implicit needs by classifying hidden intent from questions, while the non-trivial categorization was only able to be conducted with a limited size of data. In this study, we aim to develop a scalable categorization method that can categorize the askers’ intent in a large set of health-related questions via crowdsourcing. We conducted a preliminary experiment on Amazon Mechanical Turk to evaluate our categorization method. Our results suggests both challenges and opportunities for understanding health information intent via crowdsourcing.
Publisher
iSchools
Series/Report Name or Number
iConference 2015 Proceedings
Type of Resource
text
Language
English
Permalink
http://hdl.handle.net/2142/73704
Copyright and License Information
Copyright 2015 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
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