• Corpus ID: 560571

ANALYSIS OF THE FOLKSONOMY OF FREESOUND

@inproceedings{Font2012ANALYSISOT,
  title={ANALYSIS OF THE FOLKSONOMY OF FREESOUND},
  author={Frederic Font and Xavier Serra},
  year={2012}
}
User generated content shared in online communities is often described using collaborative tagging systems where users assign labels to content resources. As a result, a folksonomy emerges that relates a number of tags with the resources they label and the users that have used them. In this paper we analyze the folksonomy of Freesound, an online audio clip sharing site which contains more than two million users and 150,000 user-contributed sound samples covering a wide variety of sounds. By… 

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References

SHOWING 1-10 OF 21 REFERENCES
Folksonomy-based Tag Recommendation for Online Audio Clip Sharing
TLDR
This paper proposes four algorithm variants for tag recommendation based on tag co-occurrence in the Freesound folksonomy and shows how specific strategies for selecting the appropriate number of tags to be recommended can significantly improve algorithms’ performance.
Categorising social tags to improve folksonomy-based recommendations
Emergent Community Structure in Social Tagging Systems
TLDR
This work leverage the social aspects of collaborative tagging and introduces a notion of resource distance based on the collective tagging activity of users, and collects data from a popular system and performs experiments showing that this definition of distance can be used to build a weighted network of resources with a detectable community structure.
Can all tags be used for search?
TLDR
This paper is the first to present an in-depth study of tagging behavior for very different kinds of resources and systems - Web pages, music, and images - and compares the results with anchor text characteristics, and provides statistics on tag distributions in all three tagging environments.
HT06, tagging paper, taxonomy, Flickr, academic article, to read
TLDR
A model of tagging systems, specifically in the context of web-based systems, is offered to help illustrate the possible benefits of these tools and a simple taxonomy of incentives and contribution models is provided to inform potential evaluative frameworks.
Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies
TLDR
The Simultaneous Cut (SimCut) method has the advantage that it can group related tags and cluster the nodes simultaneously and can be easily and efficiently implemented.
Usage patterns of collaborative tagging systems
TLDR
A dynamic model of collaborative tagging is presented that predicts regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given URL.
Identifying overlapping communities in folksonomies or tripartite hypergraphs
TLDR
This paper proposes an algorithm to detect overlapping communities in folksonomies by customizing a recently proposed edge-clustering algorithm (that is originally for traditional graphs) for use on hypergraphs.
A Graph-Based Clustering Scheme for Identifying Related Tags in Folksonomies
TLDR
A novel scheme for graph-based clustering with the goal of identifying groups of related tags in folksonomies by efficiently exploring the two-dimensional core parameter space, and successively expands the identified cores by maximizing a local subgraph quality measure.
Evaluating tagging behavior in social bookmarking systems: metrics and design heuristics
TLDR
This paper analyzes over two years of data from CiteULike, a social bookmarking system for tagging academic papers, and proposes six tag metrics-tag growth, tag reuse, tag non-obviousness, tag discrimination, tag frequency, and tag patterns-to understand the characteristics of a socialBookmarking system.
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