Abstract
In this paper we propose a framework for analysing the structure of a large-scale social media network, a topic of significant recent interest. Our study is focused on the Wikipedia category network, where nodes correspond to Wikipedia categories and edges connect two nodes if the nodes share at least one common page within the Wikipedia network. Moreover, each edge is given a weight that corresponds to the number of pages shared between the two categories that it connects. We study the structure of category clusters within the three complete English Wikipedia category networks from 2010 to 2012. We observe that category clusters appear in the form of well-connected components that are naturally clustered together. For each dataset we obtain a graph, which we call the t-filtered category graph, by retaining just a single edge linking each pair of categories for which the weight of the edge exceeds some specified threshold t. Our framework exploits this graph structure and identifies connected components within the t-filtered category graph. We studied the large-scale structural properties of the three Wikipedia category networks using the proposed approach. We found that the number of categories, the number of clusters of size two, and the size of the largest cluster within the graph all appear to follow power laws in the threshold t. Furthermore, for each network we found the value of the threshold t for which increasing the threshold to t + 1 caused the “giant” largest cluster to diffuse into two or more smaller clusters of significant size and studied the semantics behind this diffusion.
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References
Beschastnikh, I., Kriplean, T., McDonald, D.W., ICWSM: Wikipedian self-governance in action: Motivating the policy lens. In: Proceedings of ICWSM (2008)
Buriol, L.S., Castillo, C., Donato, D., Leonardi, S., Millozzi, S.: Temporal analysis of the wikigraph. In: IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006), pp. 45–51. IEEE (2006)
Goel, S., Hofman, J.M., Sirer, M.I.: Who does what on the web: A large-scale study of browsing behavior. In: Proceedings of ICWSM (2012)
Hu, M., Lim, E.-P., Krishnan, R.: Predicting outcome for collaborative featured article nomination in wikipedia. In: Proceedings of ICWSM (2009)
Jurgens, D., Lu, T.-C.: Temporal motifs reveal the dynamics of editor interactions in wikipedia. In: Proceedings of ICWSM (2012)
Kamps, J., Koolen, M.: Is wikipedia link structure different? In: Proceedings of the Second ACM International Conference on Web Search and Data Mining, pp. 232–241. ACM (2009)
Kittur, A., Chi, E.H., Suh, B.: What’s in wikipedia?: mapping topics and conflict using socially annotated category structure. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1509–1512. ACM (2009)
Laniado, D., Tasso, R., Volkovich, Y., Kaltenbrunner, A.: When the wikipedians talk: Network and tree structure of wikipedia discussion pages. In: Proceedings of ICWSM (2011)
Leskovec, J., Huttenlocher, D.P., Kleinberg, J.M.: Governance in social media: A case study of the wikipedia promotion process. In: Proceedings of ICWSM (2010)
Macskassy, S.A.: On the study of social interactions in twitter. In: Proceedings of ICWSM (2012)
Massa, P.: Social networks of wikipedia. In: Proceedings of the 22nd ACM Conference on Hypertext and Hypermedia, pp. 221–230. ACM (2011)
Sadilek, A., Kautz, H.A., Silenzio, V.: Modeling spread of disease from social interactions. In: Proceedings of ICWSM (2012)
Schaeffer, S.E.: Graph clustering. Computer Science Review 1(1), 27–64 (2007)
Schönhofen, P.: Identifying document topics using the wikipedia category network. Web Intelligence and Agent Systems 7(2), 195–207 (2009)
Scott, J.: Social Network Analysis: a handbook. SAGE Publications, London (2011)
Suchecki, K., Salah, A.A.A., Gao, C., Scharnhorst, A.: Evolution of wikipedia’s category structure. Advances in Complex Systems 15(supp. 1) (2012)
Volkovich, Y., Scellato, S., Laniado, D., Mascolo, C., Kaltenbrunner, A.: The length of bridge ties: Structural and geographic properties of online social interactions. In: Proceedings of ICWSM (2012)
Wattenhofer, M., Wattenhofer, R., Zhu, Z.: The youtube social network. In: Proceedings of ICWSM (2012)
Yun, J., Jing, L., Yu, J., Huang, H., Zhang, Y.: Document topic extraction based on wikipedia category. In: 2011 Fourth International Joint Conference on Computational Sciences and Optimization (CSO), pp. 852–856. IEEE (2011)
Zesch, T., Gurevych, I.: Analysis of the wikipedia category graph for nlp applications. In: Proceedings of the TextGraphs-2 Workshop (NAACL-HLT 2007), pp. 1–8 (2007)
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Klaysri, T., Fenner, T., Lachish, O., Levene, M., Papapetrou, P. (2013). Analysis of Cluster Structure in Large-Scale English Wikipedia Category Networks. In: Tucker, A., Höppner, F., Siebes, A., Swift, S. (eds) Advances in Intelligent Data Analysis XII. IDA 2013. Lecture Notes in Computer Science, vol 8207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41398-8_23
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DOI: https://doi.org/10.1007/978-3-642-41398-8_23
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