ABSTRACT
Navigating information spaces is an essential part of our everyday lives, and in order to design efficient and user-friendly information systems, it is important to understand how humans navigate and find the information they are looking for. We perform a large-scale study of human wayfinding, in which, given a network of links between the concepts of Wikipedia, people play a game of finding a short path from a given start to a given target concept by following hyperlinks. What distinguishes our setup from other studies of human Web-browsing behavior is that in our case people navigate a graph of connections between concepts, and that the exact goal of the navigation is known ahead of time. We study more than 30,000 goal-directed human search paths and identify strategies people use when navigating information spaces. We find that human wayfinding, while mostly very efficient, differs from shortest paths in characteristic ways. Most subjects navigate through high-degree hubs in the early phase, while their search is guided by content features thereafter. We also observe a trade-off between simplicity and efficiency: conceptually simple solutions are more common but tend to be less efficient than more complex ones. Finally, we consider the task of predicting the target a user is trying to reach. We design a model and an efficient learning algorithm. Such predictive models of human wayfinding can be applied in intelligent browsing interfaces.
- L. Adamic and E. Adar. How to search a social network. Social Networks, 27(3):187--203, 2005.Google ScholarCross Ref
- E. Adar, J. Teevan, and S. T. Dumais. Large scale analysis of Web revisitation patterns. In CHI, 2008. Google ScholarDigital Library
- M. J. Bates. The design of browsing and berrypicking techniques for the online search interface. Online Review, 13(5):407--424, 1989.Google ScholarCross Ref
- M. Bilenko and R. W. White. Mining the search trails of surfing crowds: Identifying relevant websites from user activity. In WWW, 2008. Google ScholarDigital Library
- E. H. Chi, P. Pirolli, K. Chen, and J. Pitkow. Using information scent to model user information needs and actions and the Web. In CHI, 2001. Google ScholarDigital Library
- P. S. Dodds, R. Muhamad, and D. J. Watts. An experimental study of search in global social networks. Science, 301(5634):827--829, 2003.Google ScholarCross Ref
- D. Downey, S. T. Dumais, and E. Horvitz. Models of searching and browsing: Languages, studies, and applications. In IJCAI, 2007. Google ScholarDigital Library
- D. Helic, M. Strohmaier, C. Trattner, M. Muhr, and K. Lerman. Pragmatic evaluation of folksonomies. In WWW, 2011. Google ScholarDigital Library
- P. Killworth, C. McCarty, H. Bernard, and M. House. The accuracy of small world chains in social networks. Social Networks, 28(1):85--96, 2006.Google ScholarCross Ref
- J. M. Kleinberg. Navigation in a small world. Nature, 406(6798):845--845, 2000.Google ScholarCross Ref
- D. Liben-Nowell, J. Novak, R. Kumar, P. Raghavan, and A. Tomkins. Geographic routing in social networks. PNAS, 102(33):11623--11628, 2005.Google ScholarCross Ref
- C. D. Manning, P. Raghavan, and H. Schütze. Introduction to Information Retrieval. Cambridge University Press, 2008. Google ScholarCross Ref
- S. Milgram. The small-world problem. Psychology Today, 2(1):60--67, 1967.Google Scholar
- J. Muramatsu and W. Pratt. Transparent Queries: Investigating users' mental models of search engines. In SIGIR, 2001. Google ScholarDigital Library
- V. L. O'Day and R. Jeffries. Orienteering in an information landscape: How information seekers get from here to there. In CHI, 1993. Google ScholarDigital Library
- C. Olston and E. H. Chi. ScentTrails: Integrating browsing and searching on the Web. TCHI, 10(3):177--197, 2003. Google ScholarDigital Library
- P. Pirolli and S. K. Card. Information foraging. Psychological Review, 106(4):643--675, 1999.Google ScholarCross Ref
- A. J. Sellen, R. Murphy, and K. L. Shaw. How knowledge workers use the Web. In CHI, 2002. Google ScholarDigital Library
- Ö. Şimşek and D. Jensen. Navigating networks by using homophily and degree. PNAS, 105(35):12758--12762, 2008.Google ScholarCross Ref
- A. Singla, R. W. White, and J. Huang. Studying trailfinding algorithms for enhanced web search. In SIGIR, 2010. Google ScholarDigital Library
- J. Teevan, C. Alvarado, M. S. Ackerman, and D. R. Karger. The perfect search engine is not enough: A study of orienteering behavior in directed search. In CHI, 2004. Google ScholarDigital Library
- R. H. Trigg. Guided tours and tabletops: Tools for communicating in a hypertext environment. TOIS, 6(4):398--414, 1988. Google ScholarDigital Library
- R. West. Wikispeedia. Website, 2009. http://www.wikispeedia.net (accessed Feb. 2012).Google Scholar
- R. West, J. Pineau, and D. Precup. Wikispeedia: An online game for inferring semantic distances between concepts. In IJCAI, 2009. Google ScholarDigital Library
- J. Weston, S. Bengio, and N. Usunier. Large scale image annotation: Learning to rank with joint word-image embeddings. Machine Learning, 81(1):21--35, 2010. Google ScholarDigital Library
- R. W. White and J. Huang. Assessing the scenic route: Measuring the value of search trails in Web logs. In SIGIR, 2010. Google ScholarDigital Library
- Wikipedia. 2007 Wikipedia Selection for schools. Website, 2007. http://schools-wikipedia.org (accessed Aug. 2008).Google Scholar
Index Terms
- Human wayfinding in information networks
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