The Dynamic Features of Delicious, Flickr and YouTub Nan Lin1, Daifeng Li2, Ying Ding3, Bing He3, Zheng Qin2 , Jie Tang4, Juanzi Li4,Tianxi Dong5 1School of International Business Administration, 3School of Library and Information Science Shanghai University of Finance and Economics Indiana University, Bloomington, IN, USA Shanghai, China {dingying, binghe} @Indiana.edu
[email protected] 4Department of Computer Science and Technology, 2 School of Information Management and Engineering, Tsinghua University, Beijing, China, Shanghai University of Finance and Economics
[email protected] Shanghai, China 5Rawls College of Business,
[email protected] Texas Tech University, TX, USA.
[email protected] [email protected] Abstract – This article investigates the dynamic features of social tagging vocabularies in Delicious, Flickr and YouTube from 2003 to 2008. Three algorithms are designed to study the macro and micro tag growth as well as dynamics of taggers’ activities respectively. Moreover, we propose a Tagger Tag Resource LDA (TTR-LDA) model to explore the evolution of topics emerging from those social vocabularies. Our results show that (1) at the macro level, tag growth in all the three tagging systems obeys power-law distribution with exponents lower than one; at the micro level, the tag growth of popular resources in all three tagging systems follows a similar power-law distribution; (2) the exponents of tag growth vary in different evolving stages of resources; (3) the growth of number of taggers associated with different popular resources presents a feature of convergence over time; (4) the active level of taggers has a positive correlation with the macro-tag growth of different tagging systems; and (5) some topics evolve into several sub-topics 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.