Models of human navigation in information networks based on decentralized search
|Models of human navigation in information networks based on decentralized search|
|Author(s)||Helic D., Strohmaier M., Granitzer M., Scherer R.|
|Published in||HT 2013 - Proceedings of the 24th ACM Conference on Hypertext and Social Media|
|Keyword(s)||Decentralized search, Exploitation, Exploration, Navigation (Extra: Decentralized searches, Exploitation, Human behaviors, Human navigation, Information networks, Navigational paths, User behaviors, Wikipedia, Computer simulation, Experiments, Hypertext systems, Information services, Natural resources exploration, Navigation, Social networking (online), Social sciences, User interfaces, Behavioral research)|
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Models of human navigation in information networks based on decentralized search is a 2013 conference paper written in English by Helic D., Strohmaier M., Granitzer M., Scherer R. and published in HT 2013 - Proceedings of the 24th ACM Conference on Hypertext and Social Media.
Models of human navigation play an important role for understanding and facilitating user behavior in hypertext systems. In this paper, we conduct a series of principled experiments with decentralized search - an established model of human navigation in social networks - and study its applicability to information networks. We apply several variations of decentralized search to model human navigation in information networks and we evaluate the outcome in a series of experiments. In these experiments, we study the validity of decentralized search by comparing it with human navigational paths from an actual information network - Wikipedia. We find that (i) navigation in social networks appears to differ from human navigation in information networks in interesting ways and (ii) in order to apply decentralized search to information networks, stochastic adaptations are required. Our work illuminates a way towards using decentralized search as a valid model for human navigation in information networks in future work. Our results are relevant for scientists who are interested in modeling human behavior in information networks and for engineers who are interested in using models and simulations of human behavior to improve on structural or user interface aspects of hypertextual systems. Copyright 2013 ACM.
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