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Patterns in Interactive Tagging Networks

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Patterns in Interactive Tagging Networks

  1. 1. Pa#erns   in  Interac*ve  Tagging  Networks   Y.  Yamaguchi  1  M.  Yoshida  2   C.  Faloutsos  3    H.  Kitagawa  1     1  U.  Tsukuba      2  Toyohashi  U.  Tech  3  CMU   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   1  
  2. 2. Resource tagging networks 15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   2  
  3. 3. What happens if users can tag other users? 15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   3  
  4. 4. Twitter lists Sports   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   4   A  
  5. 5. Lists as tags Sports   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   5   A  
  6. 6. TwiNer  users  can  tag  each  other   Interactive tagging network 15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   6  
  7. 7. What happens if users can tag other users? 15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   7  
  8. 8. What  is  the  difference  between   the  two  types  of  tagging  networks?   (RQ1) Contrast   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   8  
  9. 9. Data 7M  users     1.8M  tags   20M  edges   30K  users   2.8M  resources   300K  tags   11M  edges   52K  users   2.6M  resources   450K  tags   14M  edges   Available  hNp://dx.doi.org/10.5281/zenodo.16267   We  collected  From  exis5ng  study   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   9  
  10. 10. Broad  &  narrow  folksonomy  [Helic+,  2012]   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   10   Broad  folksonomy   Narrow  folksonomy   Tags  for   popular  resources   Tags  for     own  resources   Q.  Which  does  TwiNer  belong  to?  
  11. 11. A. Broad folksonomy on T   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   11   Log-­‐log   plot  
  12. 12. Categorizers  &  Describers  [Korner+,  2010]   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   12   …   Categorizers   Describers   …   One  tag   for  many  resources   One  tag   for  one  resource   Q.  Which  type  are  TwiNer  users?  
  13. 13. Tagging Behaviors |Tu| :  The  number  of  tags  user  u  used     |Ru| :  The  number  of  resources  user  u  tagged   e.g.)   t   u   s   |Tu|  =  3   |Ru|  =  2   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   13  
  14. 14. A. Many categorizers on T 15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   14   30.41   Log-­‐log  plot  
  15. 15. What  is  the  difference  between   the  two  types  of  tagging  networks?   (RQ1) Contrast - answer   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   15   Broad   Categorizers   Narrow   Describers   Broad   Describers  
  16. 16. How  do  users  reciprocate   in  interac*ve  tagging  network?   (RQ2) Tagging reciprocity   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   16  
  17. 17. Mul*plicity   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   17   ?   ?   Q.  Which  is  more  likely   to  be  reciprocated?  
  18. 18. A. Large multiplicity is more likely to be reciprocated 15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   18   Log-­‐scale   growth  
  19. 19. Type  of  tags   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   19   ?   Q.  What  type  of  tag  is   more  likely  to  be  reciprocated?     Friend   ?   Sports  
  20. 20. A. Friendship-related tags are more likely to be reciprocated *  Overall  RP:  0.046   RP@t: Recipr.  prob.  for  tag  t   Lift: (RP@t)  /  (Overall  RP)   *   *   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   20  
  21. 21. (RQ2) Tagging reciprocity - answer   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   21   1.  Large multiplicity is more likely to be reciprocated 2.  Friendship-related tags are more likely to be reciprocated How  do  users  reciprocate   in  interac*ve  tagging  network?  
  22. 22. Conclusion (RQ1) Contrast: ü Broad  and  narrow  folksonomy   ü Categorizers  and  describers (RQ2) Tagging reciprocity: ü Large  mul5plicity  à  reciprocated   ü Friendship-­‐related  à  reciprocated   15/05/27   Yuto  Yamaguchi  -­‐  ICWSM15   22   Please  see  the  paper   for  other  discoveries  

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