Hypergraph model of social tagging networks

Physics – Physics and Society

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

7 pages,7 figures, 32 references

Scientific paper

The past few years have witnessed the great success of a new family of paradigms, so-called folksonomy, which allows users to freely associate tags to resources and efficiently manage them. In order to uncover the underlying structures and user behaviors in folksonomy, in this paper, we propose an evolutionary hypergrah model to explain the emerging statistical properties. The present model introduces a novel mechanism that one can not only assign tags to resources, but also retrieve resources via collaborative tags. We then compare the model with a real-world dataset: \emph{Del.icio.us}. Indeed, the present model shows considerable agreement with the empirical data in following aspects: power-law hyperdegree distributions, negtive correlation between clustering coefficients and hyperdegrees, and small average distances. Furthermore, the model indicates that most tagging behaviors are motivated by labeling tags to resources, and tags play a significant role in effectively retrieving interesting resources and making acquaintance with congenial friends. The proposed model may shed some light on the in-depth understanding of the structure and function of folksonomy.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Hypergraph model of social tagging networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Hypergraph model of social tagging networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Hypergraph model of social tagging networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-455451

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.