On the Importance of Hyperlinks: A Network Science Approach

  • Rodolfo Baggio
  • Magda Antonioli Corigliano
Conference paper


Hyperlinks are the essence of the World Wide Web. Their importance is very high due to their ability to provide a visitor with a wealth of good quality information and for the role they play in the ranking of sites by modern search engines. This paper provides a network science approach to provide evidence to the importance of hyperlinking. We examine the webgraph of a tourism destination using graph theoretic methods to highlight the effects that the topological structure has on its navigability. Moreover, through a series of simulations performed on the representation of the real web network we show how a modest increase in the number of links may improve the visibility and the navigability of the destination’s webspace.


Web navigation hyperlinks complex networks random walks 


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  1. Adamic, L. A., & Adar, E. (2001). You are what you link. Proceedings of the 10th International World Wide Web Conference, Hong Kong.Google Scholar
  2. Adamic, L. A., & Adar, E. (2003). Friends and Neighbors on the Web. Social Networks, 25(3), 211–230.Google Scholar
  3. Adamic, L. A., Lukose, R. M., Puniyani, A. R., & Huberman, B. A. (2001). Search in Power-Law Networks. Physical Review E, 64, 46135–46143.Google Scholar
  4. Albert, R., & Barabási, A.-L. (2002). Statistical mechanics of complex networks. Review of Modern Physics, 74, 47–91.Google Scholar
  5. Baggio, R. (2006). Complex systems, information technologies and tourism: a network point of view. Information Technology and Tourism, 8(1), 15–29.Google Scholar
  6. Baggio, R. (2007). The Web Graph of a Tourism System. Physica A, 379(2), 727–734.Google Scholar
  7. Baggio, R., Antonioli Corigliano, M., & Tallinucci, V. (2007). The websites of a tourism destination: a network analysis. In M. Sigala, L. Mich & J. Murphy (Eds.), Information and Communication Technologies in Tourism 2007Proceedings of the International Conference in Ljubljana, Slovenia (pp. 279–288). Wien: Springer.Google Scholar
  8. Benkler, Y. (2006). The Wealth of Networks — How Social Production Transforms Markets and Freedom. New Haven and London: Yale University Press.Google Scholar
  9. Berkhin, P. (2005). A survey on PageRank computing. Internet Mathematics, 1, 73–120.Google Scholar
  10. Berners-Lee, T. (1989). Information Management: A Proposal. Geneva, CH: CERN. Retrieved January, 2008, from Scholar
  11. Biever, C. (2004). Rival engines finally catch up with Google. New Scientist, 184(2474), 23.Google Scholar
  12. Bramwell, B., & Lane, B. (2000). Tourism Collaboration and Partnerships: Politics Practice and Sustainability. Clevedon, UK: Channel View Publications.Google Scholar
  13. Brin, S., & Page, L. (1998). The Anatomy of a Large-Scale Hypertextual (Web) Search Engine. Computer Networks and ISDN Systems, 30(1–7), 107–117.Google Scholar
  14. Broder, A. Z., Kumar, S. R., Maghoul, F., Raghavan, P., Rajagopalan, S., Stata, R., Tomkins, A., & Wiener, J. L. (2000). Graph structure in the web. Computer Networks, 33(1–6), 309–320.Google Scholar
  15. Conklin, J. (1987). Hypertext: An Introduction and Survey. IEEE Computer, 20(9), 17–40.Google Scholar
  16. da Fontoura Costa, L., Rodrigues, A., Travieso, G., & Villas Boas, P. R. (2007). Characterization of complex networks: A survey of measurements. Advances in Physics, 56(1), 167–242.Google Scholar
  17. da Fontoura Costa, L., Sporns, O., Antiqueira, L., das Graças Volpe Nunes, M., & Oliveira, O. N. J. (2007). Correlations between structure and random walk dynamics in directed complex networks. Applied Physics Letters, 91, art.:054107.Google Scholar
  18. Dall’Asta, L., Alvarez-Hamelin, I., Barrat, A., Vázquez, A., & Vespignani, A. (2005). Statistical theory of Internet exploration. Physical Review E, 71, art.:036135.Google Scholar
  19. Deo, N., & Gupta, P. (2001). Graph-Theoretic Web Algorithms: An Overview. In T. Böhme & H. Unger (Eds.), Lecture Notes in Computer Science (Vol. 2026, pp. 91–102). Berlin: Springer.Google Scholar
  20. Dill, S., Kumar, S. R., McCurley, K., Rajagopalan, S., Sivakumar, D., & Tomkins, A. (2002). Self similarity in the web. ACM Transactions on Internet Technology (TOIT), 2(3–August), 205–223.Google Scholar
  21. Flake, G. W., Lawrence, S., Giles, C. L., & Coetzee, F. M. (2002). Self-Organization of the Web and Identification of Communities. IEEE Computer, 35(3), 66–71.Google Scholar
  22. Gibson, D., Kleinberg, J., & Raghavan, P. (1998). Inferring Web communities from link topology. Proceedings of the 9th ACM Conference on Hypertext and Hypermedia, 225–234.Google Scholar
  23. Henzinger, M. R., Heydon, A., Mitzenmacher, M., & Najork, M. (1999). Measuring index quality using random walks on the Web. Computer Networks, 31(11), 1291–1303.Google Scholar
  24. Kleinberg, J. M. (2006). Complex networks and decentralized search algorithms. Proceedings of the International Congress of Mathematicians, Madrid, Spain.Google Scholar
  25. Langville, A. N., & Meyer, C. D. (2005). Deeper inside PageRank. Internet Mathematics, 1, 335–380.Google Scholar
  26. Langville, A. N., & Meyer, C. D. (2006). Google’s PageRank and beyond. Princeton: Princeton University Press.Google Scholar
  27. Latapy, M., & Pons, P. (2006). Computing communities in large networks using random walks. Journal of Graph Algorithms and Applications, 10(2), 191–218.Google Scholar
  28. Leidner, R. (2004). The European Tourism Industry. A multi-sector with dynamic markets. Structures, developments and importance for Europe’s economy. Luxembourg: Office for Official Publications of the European Communities.Google Scholar
  29. Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69, 26113.Google Scholar
  30. Page, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank citation ranking: Bringing order to the Web (Working Paper No. SIDL-WP-1999-0120): Standford Digital Library Project, Stanford University, CA.Google Scholar
  31. Pan, B., & Fesenmaier, D. R. (2006). Online Information Search: Vacation Planning Process. Annals of Tourism Research, 33(3), 809–832.Google Scholar
  32. Park, H. W. (2003). Hyperlink Network Analysis: A New Method for the Study of Social Structure on the Web. Connections, 25(1), 49–61.Google Scholar
  33. Park, H. W., & Thelwall, M. (2003). Hyperlink Analyses of the World Wide Web: A Review. Journal of Computer Mediated Communication [On-line], 8(4). Retrieved March 2006, from Scholar
  34. Pastor-Satorras, R., & Vespignani, A. (2004). Evolution and structure of the Internet — A Statistical Physics Approach. Cambridge, UK: Cambridge University Press.Google Scholar
  35. Skopal, T., Snášel, V., Svátek, V., & Krátký, M. (2003). Searching the Internet Using Topological Analysis of Web Pages. Proceedings of the 2003 International Conference on Communications in Computing (CIC’03), Las Vegas, NV, 271–277.Google Scholar
  36. Tallinucci, V., & Testa, M. (2006). Marketing per le isole. Milano Franco Angeli.Google Scholar
  37. Vaughan, L., Gao, Y., & Kipp, M. (2006). Why are hyperlinks to business Websites created? A content analysis. Scientometrics, 67(2), 291–300.Google Scholar
  38. Vise, D., & Malseed, M. (2005). The Google Story: Inside the Hottest Media and Technology Business of Our Time. New York: Delacorte Press.Google Scholar
  39. Walker, J. (2002). Links and power: the political economy of linking on the Web. Proceedings of the 2002 ACM Hypertext Conference, Baltimore, MD, 72–73.Google Scholar
  40. Yang, S.-Y. (2005). Exploring complex networks by walking on them. Physical Review E, 71, art.:016107.Google Scholar

Copyright information

© Springer-Verlag/Wien 2009

Authors and Affiliations

  • Rodolfo Baggio
    • 1
  • Magda Antonioli Corigliano
    • 1
  1. 1.Master in Economics and TourismBocconi UniversityMilanItaly

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