Abstract
This paper explores visiting metrics and some of the more important general network properties of Fitcolab online social network (OSN). The wide array of statistics was explored in order to obtain general insight that will not only be useful by itself but would also serve as the starting platform for more focused research endeavors that are to be based on the same experimental network. Longitudinal OSN usage patterns are studied for number of visits, average duration of visits and number of active users. Network structural characteristics analyzed included reachability, average distance, diameter, clustering coefficient, in/out degree distributions. Longitudinal analyses of a number of structural characteristics were also carried out. Partial interpretation of the results followed.
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References
Memic, H.: Fitcolab Experimental Online Social Networking System. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ICCCI 2010, Part II. LNCS (LNAI), vol. 6422, pp. 31–40. Springer, Heidelberg (2010)
Kaushik, A.: Web Analytics: An Hour a Day. Wiley Publishing, Indiana (2007)
Sostre, P., LeClaire, J.: Web Analytics for Dummies. Wiley, Hoboken (2007)
Burby, J., Atchison, S.: Actionable Web Analytics: Using Data to Make Smart Business Decisions. Wiley, Chichester (2007)
Baur, M., Schank, T.: Dynamic Graph Drawing in Visone. Technical University Karlsruhe, Karlsruhe (2008), http://i11www.iti.uni-karlsruhe.de/extra/publications/bs-dgdv-08.pdf
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Memic, H. (2010). General Network Properties of Friendship Online Social Network. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6422. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16732-4_5
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DOI: https://doi.org/10.1007/978-3-642-16732-4_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16731-7
Online ISBN: 978-3-642-16732-4
eBook Packages: Computer ScienceComputer Science (R0)