The Social Score - Determining the Relative Importance of Webpages Based on Online Social Signals

Marco Buijs, Marco Spruit

2014

Abstract

There are many ways to determine the importance of Webpages, the most successful one being the PageRank algorithm. In this paper we describe an alternative ranking method that we call the Social Score method. The Social Score of a Webpage is based on the number of likes, tweets, bookmarks and other sorts of intensified information from Social Media platforms. By determining the importance of Webpages based on this kind of information, ranking becomes based on a democratic system instead of a system in which only web authors influence the ranking of results. Based on an experiment we conclude that the Social Score is a great alternative to PageRank that could be used as an additional property to take into account in Web Search Engines.

References

  1. Bao, S., Xue, G., Wu, X., Yu, Y., Fei, B., and Su, Z. (2007). Optimizing web search using social annotations. In Proceedings of the 16th international conference on World Wide Web, pages 501-510. ACM.
  2. Berners-Lee, T., Hendler, J., Lassila, O., et al. (2001). The semantic web. Scientific american, 284(5):28-37.
  3. Brin, S. and Page, L. (1998). The anatomy of a large-scale hypertextual web search engine. Computer networks and ISDN systems, 30(1):107-117.
  4. Evans, B. M. and Chi, E. H. (2008). Towards a model of understanding social search. In Proceedings of the 2008 ACM conference on Computer supported cooperative work, pages 485-494. ACM.
  5. Gerlitz, C. and Helmond, A. (2013). The like economy: Social buttons and the data-intensive web. New Media & Society, 15(8):1348-1365.
  6. Golder, S. A. and Huberman, B. A. (2006). Usage patterns of collaborative tagging systems. Journal of Information Science, 32(2):198-208.
  7. Golovchinsky, G., Pickens, J., and Back, M. (2009). A taxonomy of collaboration in online information seeking. arXiv preprint arXiv:0908.0704.
  8. Heymann, P., Koutrika, G., and Garcia-Molina, H. (2008). Can social bookmarking improve web search? In Proceedings of the international conference on Web search and web data mining, pages 195-206. ACM.
  9. Hu, Y., Xin, G., Song, R., Hu, G., Shi, S., Cao, Y., and Li, H. (2005). extraction from bodies of html documents and its application to web page retrieval. In Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, pages 250-257. ACM.
  10. Joachims, T. (2002). Unbiased evaluation of retrieval quality using clickthrough data. In SIGIR Workshop on Mathematical/Formal Methods in Information Retrieval, volume 354. Citeseer.
  11. Manning, C. D., Raghavan, P., and Schütze, H. (2008). Introduction to information retrieval, volume 1. Cambridge University Press Cambridge.
  12. Noll, M. G. and Meinel, C. (2007). Web search personalization via social bookmarking and tagging. In The Semantic Web, pages 367-380. Springer.
  13. Salton, G. and McGill, M. J. (1983). Introduction to modern information retrieval.
  14. Yanbe, Y., Jatowt, A., Nakamura, S., and Tanaka, K. (2007). Can social bookmarking enhance search in the web? In Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries, pages 107-116. ACM.
Download


Paper Citation


in Harvard Style

Buijs M. and Spruit M. (2014). The Social Score - Determining the Relative Importance of Webpages Based on Online Social Signals . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014) ISBN 978-989-758-048-2, pages 71-77. DOI: 10.5220/0005076400710077


in Bibtex Style

@conference{kdir14,
author={Marco Buijs and Marco Spruit},
title={The Social Score - Determining the Relative Importance of Webpages Based on Online Social Signals},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)},
year={2014},
pages={71-77},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005076400710077},
isbn={978-989-758-048-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)
TI - The Social Score - Determining the Relative Importance of Webpages Based on Online Social Signals
SN - 978-989-758-048-2
AU - Buijs M.
AU - Spruit M.
PY - 2014
SP - 71
EP - 77
DO - 10.5220/0005076400710077