Markines, B.; Cattuto, C. & Menczer, F.: Social spam detection.. In: Fetterly, D. & Gyöngyi, Z. (Hrsg.):
AIRWeb. 2009ACM International Conference Proceeding Series , S. 41-48
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Benz, D. & Hotho, A.: Position Paper: Ontology Learning from Folksonomies.. In: Hinneburg, A. (Hrsg.):
LWA 2007: Lernen - Wissen - Adaption, Halle, September 2007, Workshop Proceedings (LWA). Martin-Luther-University Halle-Wittenberg, 2007, S. 109-112
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Cattuto, C.; Loreto, V. & Pietronero, L.: Collaborative Tagging and Semiotic Dynamics. In:
PNAS 104 (2007), S. 1461
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Collaborative tagging has been quickly gaining ground because of its ability to recruit the activity of web users into effectively organizing and sharing vast amounts of information. Here we collect data from a popular system and investigate the statistical properties of tag co-occurrence. We introduce a stochastic model of user behavior embodying two main aspects of collaborative tagging: (i) a frequency-bias mechanism related to the idea that users are exposed to each other's tagging activity; (ii) a notion of memory - or aging of resources - in the form of a heavy-tailed access to the past state of the system. Remarkably, our simple modeling is able to account quantitatively for the observed experimental features, with a surprisingly high accuracy. This points in the direction of a universal behavior of users, who - despite the complexity of their own cognitive processes and the uncoordinated and selfish nature of their tagging activity - appear to follow simple activity patterns.
Cattuto, C.; Schmitz, C.; Baldassarri, A.; Servedio, V. D. P.; Loreto, V.; Hotho, A.; Grahl, M. & Stumme, G.: Network Properties of Folksonomies. In:
AI Communications 20 (2007), Nr. 4, S. 245 - 262
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Grahl, M.; Hotho, A. & Stumme, G.: Conceptual Clustering of Social Bookmarking Sites.
7th International Conference on Knowledge Management (I-KNOW '07). Graz, Austria: Know-Center, 2007, S. 356-364
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Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of the system, but it does not allow a conceptual drill-down, e. g., along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented with ranked lists of users and resources most related to each cluster. The rankings are computed using our FolkRank algorithm. We have evaluated our approach on large scale data from the del.icio.us bookmarking system.
Heymann, P.; Koutrika, G. & Garcia-Molina, H.: Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges.. In:
IEEE Internet Computing 11 (2007), Nr. 6, S. 36-45
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Jäschke, R.; Marinho, L. B.; Hotho, A.; Schmidt-Thieme, L. & Stumme, G.: Tag Recommendations in Folksonomies. In: Kok, J. N.; Koronacki, J.; de Mántaras, R. L.; Matwin, S.; Mladenic, D. & Skowron, A. (Hrsg.):
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings. Springer, 2007 (Lecture Notes in Computer Science 4702), S. 506-514
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Kolari, P.; Finin, T.; Yesha, Y.; Yesha, Y.; Lyons, K.; Perelgut, S. & Hawkins, J.: On the Structure, Properties and Utility of Internal Corporate Blogs.
Proceedings of the International Conference on Weblogs and Social Media (ICWSM 2007). 2007
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Koutrika, G.; Effendi, F. A.; Gyöngyi, Z.; Heymann, P. & Garcia-Molina, H.: Combating spam in tagging systems.
AIRWeb '07: Proceedings of the 3rd international workshop on Adversarial information retrieval on the web. New York, NY, USA: ACM Press, 2007, S. 57-64
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Nauman, M. & Khan, S.: Using PersonalizedWeb Search for Enhancing Common Sense and Folksonomy Based Intelligent Search Systems. In:
wi 0 (2007), S. 423-426
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Sinclair, J. & Cardew-Hall, M.: The folksonomy tag cloud: When is it useful?. In:
Journal of Information Science (2007), S. 016555150607808
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Wurst, M. & Morik, K.: Distributed feature extraction in a p2p setting: a case study. In:
Future Gener. Comput. Syst. 23 (2007), Nr. 1, S. 69-75
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Capocci, A.; Servedio, V. D. P.; Colaiori, F.; Buriol, L. S.; Donato, D.; Leonardi, S. & Caldarelli, G.: Preferential attachment in the growth of social networks: the case of Wikipedia. In:
CoRR abs/physics/0602026 (2006),
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Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.: Information Retrieval in Folksonomies: Search and Ranking.
Proceedings of the 3rd European Semantic Web Conference . Budva, Montenegro: Springer, 2006 (LNCS 4011), S. 411-426
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Jäschke, R.; Hotho, A.; Schmitz, C.; Ganter, B. & Stumme, G.: TRIAS - An Algorithm for Mining Iceberg Tri-Lattices.
Proc. 6th ICDM conference. Hong Kong: 2006
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Schmitz, C.; Hotho, A.; Jäschke, R. & Stumme, G.: Mining Association Rules in Folksonomies. In: Batagelj, V.; Bock, H.-H.; Ferligoj, A. & Žiberna, A. (Hrsg.):
Data Science and Classification (Proc. IFCS 2006 Conference). Berlin/Heidelberg: Springer, 2006Studies in Classification, Data Analysis, and Knowledge Organization , S. 261-270
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Sen, S.; Lam, S. K.; Rashid, A. M.; Cosley, D.; Frankowski, D.; Osterhouse, J.; Harper, F. M. & Riedl, J.: tagging, communities, vocabulary, evolution.
CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work. New York, NY, USA: ACM, 2006, S. 181-190
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A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.
Stumme, G.: A Finite State Model for On-Line Analytical Processing in
Triadic Contexts. In: Ganter, B. & Godin, R. (Hrsg.):
Proc. 3rd Intl. Conf. on Formal Concept Analysis. Heidelberg: Springer, 2005 (Lecture Notes in Computer Science 3403), S. 315-328
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Heylighen, F.: Bootstrapping knowledge representations: from entailment meshes via semantic nets to learning webs. In:
Kybernetes 30 (2001), Nr. 5/6, S. 691-722
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Lehmann, F. & Wille, R.: A triadic approach to formal concept analysis. In: Ellis, G.; Levinson, R.; Rich, W. & Sowa, J. F. (Hrsg.):
Conceptual structures: applications, implementation and theory. Berlin--Heidelberg--New~York: Springer--Verlag, 1995Lecture Notes in Artificial Intelligence , S. 32-43
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