Now a day's popularity of video sharing site is increased. People can watch videos from sites and also interested in relevant links videos which are suggested by social video sharing sites. To increase popularity of video external links concept is used. Now in video sharing sites through external links video or audio contents can be embedded into external web sites. User can copy the URL(uniform resource locater) of that embedded link and post on their own blog or website. In this paper intention is study of relevancy of videos and & increase the popularity and measure the quantification. With the results collected from two major video sharing sites like YouTube & Youku. Then observed that these links have a various impact on popularity. Overall, videos which are collected from external links are analyzed also accuracy & popularity is measured.

1. YouTube. [Online]. Available: http://www. youtube. com.
2. Youku [Online]. Available: http://www. youku. com. The data sets of external links from YouTube and Youku.
3. Q. Ruan, H. Lin and H. Tan. Research on the approach to optimize book exhibition based on mining association rules. International Journal of Advancements in Computing Technology, 2012. 4(16): pp. 500-507.
4. H. He. Analysis ofAssociation Rules in Book Circulation. Library Journal, 2011. 7(30): pp. 63-68.
5. Aggarwal, C. C. , Li, Y. , Wang, J. and Wang, J. (2009) Frequent pattern mining with uncertain data, International Conference on Knowledge Discovery and Data Mining, Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACMPp. 29-38, ISBN-978-3-642-13657-3.
6. W. Chen, J. Chu, and J. Luan, "Collaborative filtering for orkut communities: Discovery of user latent behavior," in Proc. ACM WWW'09, Madrid, Spain, Apr. 20–24, 2009.
7. M. Cha, H. Kwak, P. Rodriguez, Y. Ahn, and S. Moon, "I tube, you tube, everybody tubes: Analyzing the world's largest user generated content video system," in Proc. ACM IMC'07, San Diego, CA, Oct. 24–26, 2007.
8. S. Mitra, M. Agrawal, A. Yadav, N. Carlsson, D. Eager, and A. Mahanti, "Characterizing web-based video sharing workload," ACM Trans. Web, vol. 5, no. 2, May 2011.
9. J. Leskovec, D. Huttenlocher, and J. Kleinberg, "Predicting positive and negative links in online social networks," in Proc. ACM WWW'10, Raleigh, NC, Apr. 26–30, 2010.
10. X. Y. Yang, Z. Liu and Y. Fu. MapReduce as a programming model for association rules algorithm on Hadoop. 3rd International Conference on Information Sciences and Interaction Sciences (ICIS 2010). 2010. Chengdu, China.
11. J. Cryans, S. Ratte and R. Champagne. Adaptation of apriori to MapReduce to build a warehouse of relations between named entities across the web. 2nd International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2010). 2010. Menuires, France.
12. M. Lin, P. Lee and S. Hsueh. Apriori-based frequent itemset mining algorithms on MapReduce. 6th International Conference on Ubiquitous Information Management.

Video Sharing Youtube Youku External Links Frequent Item Set Data Mining.