Lin Yi-ling, Trattner Christoph, Brusilovsky Peter , He Daqing
The impact of image descriptions on user tagging behavior: A study of the nature and functionality of crowdsourced tags
JASIST, Wiley, 2015
Crowdsourcing has been emerging to harvest social wisdom from thousands of volunteers to
perform series of tasks online. However, little research has been devoted to exploring the impact
of various factors such as the content of a resource or crowdsourcing interface design to user
tagging behavior. While images’ titles and descriptions are frequently available in image digital
libraries, it is not clear whether they should be displayed to crowdworkers engaged in tagging.
This paper focuses on offering an insight to the curators of digital image libraries who face this
dilemma by examining (i) how descriptions influence the user in his/her tagging behavior and (ii)
how this relates to the (a) nature of the tags, (b) the emergent folksonomy, and (c) the findability
of the images in the tagging system. We compared two different methods for collecting image
tags from Amazon’s Mechanical Turk’s crowdworkers – with and without image descriptions.
Several properties of generated tags were examined from different perspectives: diversity,
specificity, reusability, quality, similarity, descriptiveness, etc. In addition, the study was carried
out to examine the impact of image description on supporting users’ information seeking with a
tag cloud interface. The results showed that the properties of tags are affected by the
crowdsourcing approach. Tags from the “with description” condition are more diverse and more
specific than tags from the “without description” condition, while the latter has a higher tag reuse
rate. A user study also revealed that different tag sets provided different support for search.
Tags produced “with description” shortened the path to the target results, while tags produced
without description increased user success in the search task