An evaluation of Flickrs distributed classification system, from the perspective of its members, and as an image retrieval tool in comparison with a controlled vocabulary
Samuel Piker

TL;DR
This study evaluates Flickr's distributed classification system from members' perspectives and compares its effectiveness as an image retrieval tool against a controlled vocabulary, highlighting strengths and limitations of tagging for search and browsing.
Contribution
It provides empirical insights into why users tag images and systematically compares tag-based retrieval with traditional controlled vocabularies in a real-world setting.
Findings
Tags are generally accepted despite flaws due to their usefulness.
Flickr's tagging system is more flexible and better at capturing subtle concepts than controlled vocabularies.
Tags work best when used within groups sharing common interests.
Abstract
The profusion of online digital images presents new challenges for image indexing. Images have always been problematic to describe and catalogue due to lack of inherent textual data and ambiguity of meaning. An alternative to time-consuming professionally-applied metadata has been sought in the form of tags, simple keywords that form a flat structure known as distributed classification, or more popularly as a folksonomy. This research aims to increase understanding of why people tag and how effective they find it for searching, using as the focus. Open-ended questionnaires were sent out to members of the photo-sharing website Flickr, with the opportunity to post comments to an online discussion space. There is also a systematic comparison between a tag-based system and a more traditional controlled vocabulary, to test out the claims made regarding the suitability of tagging for…
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Taxonomy
TopicsSemantic Web and Ontologies · Fuzzy Logic and Control Systems · Image Retrieval and Classification Techniques
