Abstract
With the rapid development of Internet, micro-blog service has become the fastest growing Internet application, where URLs play an important role in the social network. However, the studies on analyzing the URL resources especially for Chinese micro-blog system are extremely scarce. In this paper, we construct a corpus which contains the dissemination and classification information about URLs in Sina Weibo. Then we focus on the typical questions who publishes the URLs, what the URLs point to and how the URLs are disseminated and answer all the questions above by analyzing a recent Sina Weibo corpus. We find that verified users tend to publish about twice the amount of URLs as non-verfied users; Video URLs are more easily to disseminate in Sina Weibo. Our findings provide insights on downstream IR applications such as search engine and recommender systems effectively.
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References
Suh, B., Hong, L., Pirolli, P., et al.: Want to be retweeted? large scale analytics on factors impacting retweet in twitter network. In: 2010 IEEE Second International Conference on Social computing (socialcom), pp. 177–184. IEEE (2010)
Liu, Y., Kliman-Silver, C., Mislove, A.: The tweets they are a-changin: evolution of twitter users and behavior. In: International AAAI Conference on Weblogs and Social Media (ICWSM), vol. 13, p. 55 (2014)
Antoniades, D., Polakis, I., Kontaxis, G., et al.: we. b: The web of short URLs. In: Proceedings of the 20th International Conference on World Wide Web, pp. 715–724. ACM (2011)
Kandylas, V., Dasdan, A.: The utility of tweeted URLs for web search. In: Proceedings of the 19th International Conference on World Wide Web, pp. 1127–1128. ACM (2010)
Wang, Y., Tao, H., Cao, J., Wu, Z.: Understanding user behavior through URL analysis in sina tweets. In: Huang, Z., Liu, C., He, J., Huang, G. (eds.) WISE 2013. LNCS, vol. 8182, pp. 98–108. Springer, Heidelberg (2014). doi:10.1007/978-3-642-54370-8_9
Odijk, D., White, R.W., Hassan Awadallah, A., et al.: Struggling and success in web search. In: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp. 1551–1560. ACM (2015)
Ritter, A., Etzioni, O., Clark, S.: Open domain event extraction from twitter. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1104–1112. ACM (2012)
Spina, D., Gonzalo, J., Amigó, E.: Discovering filter keywords for company name disambiguation in twitter. Expert Syst. Appl. 40(12), 4986–5003 (2013)
Cheng, X., Dale, C., Liu, J.: Statistics and social network of youtube videos. In: 16th International Workshop on Quality of Service, IWQoS 2008, pp. 229–238. IEEE (2008)
Lee, S., Kim, J.: Warningbird: a near real-time detection system for suspicious urls in twitter stream. IEEE Trans. Dependable Secure Comput. 10(3), 183–195 (2013)
Klien, F., Strohmaier, M.: Short links under attack:geographical analysis of spam in a URL shortener network. In: Proceedings of the 23rd ACM Conference on Hypertext and Social Media, pp. 83–88. ACM (2012)
Acknowledgments
This work is supported by the National Natural Science Foundation of China (grant Nos. 61402466 and 61572494) and the Strategic Priority Research Program of the Chinese Academy of Sciences (grant No. XDA06030200).
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Wan, Y., Li, P., Li, R., Zhou, M., Ye, Y., Wang, B. (2016). Towards Understanding URL Resources in Recent Sina Weibo. In: Cellary, W., Mokbel, M., Wang, J., Wang, H., Zhou, R., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2016. WISE 2016. Lecture Notes in Computer Science(), vol 10041. Springer, Cham. https://doi.org/10.1007/978-3-319-48740-3_4
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DOI: https://doi.org/10.1007/978-3-319-48740-3_4
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