The dynamic features of delicious, flickr, and YouTube

  • Authors:

  • Nan Lin;Daifeng Li;Ying Ding;Bing He;Zheng Qin;Jie Tang;Juanzi Li;Tianxi Dong

  • Affiliations:

  • School of International Business Administration, Shanghai University of Finance and Economics, Shanghai, China;School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China;School of Library and Information Science, Indiana University, Bloomington, IN;School of Library and Information Science, Indiana University, Bloomington, IN;School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China;Department of Computer Science and Technology, Tsinghua University, Beijing, China;Department of Computer Science and Technology, Tsinghua University, Beijing, China;Rawls College of Business, Texas Tech University, Lubbock, TX

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2012

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Abstract

This article investigates the dynamic features of social tagging vocabularies in Delicious, Flickr, and YouTube from2003 to 2008. Three algorithms are designed to study the macro- and micro-tag growth as well as the dynamics of taggers' activities, respectively. Moreover, we propose a Tagger Tag Resource Latent Dirichlet Allocation (TTRLDA) model to explore the evolution of topics emerging from those social vocabularies. Our results show that (a) at the macro level, tag growth in all the three tagging systems obeys power law distribution with exponents lower than 1; at the micro level, the tag growth of popular resources in all three tagging systems follows a similar power law distribution; (b) the exponents of tag growth vary in different evolving stages of resources; (c) the growth of number of taggers associated with different popular resources presents a feature of convergence over time; (d) the active level of taggers has a positive correlation with the macro-tag growth of different tagging systems; and (e) some topics evolve into several subtopics over time while others experience relatively stable stages in which their contents do not change much, and certain groups of taggers continue their interests in them.