1. By: Tsoi Ho Keung Supervisor: Dr. Li Chen Co-Supervisor: Prof. Jiming Liu

2. Title  Understanding the Cultural Influence on Tagging Pattern

3. Motivation  Cultural originality determine/affect human behavior  Examples: greeting method, table manner, and you name it…  Cultural differences found in consumer behavior [1]. Western countries have individualism and a low context culture Eastern countries have collectivism and a high context culture  How about tagging behavior? We are interested in exploring whether differences exist in this area. Reference: [1] Chau, P. Y. K., Cole, M., Massey, A. P., Montoya-Weiss, M. and O'Keefe, R. M. 2002. Cultural differences in the online behavior of consumers. Communications of the ACM 45 (10), 138-143.

4. Introduction  What is tag? User-created annotation, in the form of keywords, short-phrases, to describe a resource.  What is the usage of assigning tags? Search, personal management goal  Example systems Flickr, Last.FM, DEL.icio.us, Digg…

5. Experimental Data (requirement)  Two datasets Different target group Tagging-enabled Share common domain  The following websites fulfilled our criteria SongTaste.com Last.FM

6. Experimental Data (sources) SongTasteLast.FM  Target user  Chinese  Popular in China (2.3M registered users)  Song listening available  Let users comment  Different rankings  Tag application  Target user  European  Popular (30M registered users)  Song listening available  Let users comment  Different rankings  Tag application

7. Experimental Data (Dataset) SongTasteLast.FM  200 popular songs(as at 6 th Dec, 09)  6,500 users applied at least 1 tag  Avg. tags applied: 10.3 (SD 74.47)  200 popular songs(as at 6 th Dec, 09)  6,500 users applied at least 1 tag  Avg. tags applied: 62.1 (SD 36.34)

8. Research Questions  RQ1: What is the tag agreement among friends in both cultures?  RQ2: What is the tag agreement among members in both cultures?  RQ3: What is the tag non-obviousness index in oriental users compare with western user?  RQ4: How the tags classes distribution diverse from oriental users to western user?

9. Metrics  Evaluation method from [1] as baseline measurement  t-test assuming unequal variances with a risk level(α) of 0.05 is used for comparing the datasets Reference: [1] U. Farooq, T. G. Kannampallil, Y. Song, C. H. Ganoe, J. M. Carroll, and L. Giles. Evaluating tagging behavior in social bookmarking systems: metrics and design heuristics. In GROUP ’07: Proceedings of the 2007 international ACM conference on Supporting group work, pages 351–360, New York, NY, USA, 2007. ACM.

10. Tag Agreement among Friends & among Members  RQ1: What is the tag agreement among friends in both cultures?  RQ2: What is the tag agreement among members in both cultures?

11. Tag Agreement among Friends & among Members  Symmetric Jaccard Coefficient T user : the set of tags user applied T friend : the set of tags user’s friends applied

12. Tag Agreement among Friends & among Members  Friends Definition In both systems, user can explicitly state who their friends are.  Members Definition Similarly, both systems allow users comment on a song. We define users who shared a common discussion maintain a membership

13. Tag Agreement among Friends & among Members SongTasteLast.FMP value (t-test) Among Friends0.00060.1106 Among Members0.00210.0973 ۚۚ t-Test: Paired Two Sample for Means, p-value less than 0.05 is significant p< 0.05 (t=1.96)

14. Tag non-obviousness  RQ3: What is the tag non-obviousness index in oriental users compare with western user?  Definition: The ratio of tags not appear in the content to the total number of tags of that item To access the usefulness of a tag

15. Tag non-obviousness  Formally, we have to evaluate this property  (t=2.60, p = 0.004) SongTasteLast.FM Non-obviousness93%95%

16. Tag Classes Distribution  RQ4: How the tags classes distribution diverse from oriental users to western user? Another 200 songs common in both systems are considered Classify the tags into different categories Two classification schemes

17. Tag Classes Distribution  Examples of the three categories  Examples of the seven categories

18. Tag Classes Distribution Three Categories p-value Factual0.0002 Personal0.7183 Subjective3.79 x 10 -11 Remarks: These are average percentage

19. Tag Classes Distribution Seven Categories p-value Cat.17.6 x 10 -7 Cat.20.4043 Cat.3NA Cat.40.005 Cat.51 x 10 -9 Cat.60.6235 Cat.70.0064 Remarks: These are average percentage

20. Conclusion  The two cultures exhibit different tagging behavior!!! PropertyDifference What is the tag agreement among friends in both cultures?√ What is the tag agreement among members in both cultures?√ What is the tag non-obviousness index in oriental users compare with western user? √ How the tags classes distribution diverse from oriental users to western user? √

21. What’s next?  Bearing the different tagging patterns in mind, we can.. Develop cultural-aware tag recommender system and; Provide tailor-made tag recommendation based on users’ cultural originality and; much more…

22. Coming Soon…  Cultural-aware Semantic Map based on SOM Tag Recommender

23. Question & Answer  Thank you