Abstract
In earlier papers we characterised the notion of diachronic topic-based communities –i.e., communities of people who work on semantically related topics at the same time. These communities are important to enable topic-centred analyses of the dynamics of the research world. In this paper we present an innovative algorithm, called Research Communities Map Builder (RCMB), which is able to automatically link diachronic topic-based communities over subsequent time intervals to identify significant events. These include topic shifts within a research community; the appearance and fading of a community; communities splitting, merging, spawning other communities; and others. The output of our algorithm is a map of research communities, annotated with the detected events, which provides a concise visual representation of the dynamics of a research area. In contrast with existing approaches, RCMB enables a much more fine-grained understanding of the evolution of research communities, with respect to both the granularity of the events and the granularity of the topics. This improved understanding can, for example, inform the research strategies of funders and researchers alike. We illustrate our approach with two case studies, highlighting the main communities and events that characterized the World Wide Web and Semantic Web areas in the 2000 – 2010 decade.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Yan, E., Ding, Y., Milojević, S., Sugimoto, C.R.: Topics in dynamic research communities: An exploratory study for the field of information retrieval. Journal of Informetrics 6(1), 140–153 (2012)
Van Eck, N.J., Waltman, L.: Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2), 523–538 (2010)
Upham, S.P., Rosenkopf, L., Ungar, L.H.: Innovating knowledge communities. Scientometrics 83(2), 525–554 (2010)
Yan, E., Ding, Y., Jacob, E.: Overlaying communities and topics. Scientometrics 90(2), 499–513 (2012)
Zhao, Z., Feng, S., Wang, Q., Huang, J.Z., Williams, G.J., Fan, J.: Topic oriented community detection through social objects and link analysis in social networks. Knowledge-Based Systems 26, 164–173 (2012)
Osborne, F., Motta, E.: Mining Semantic Relations between Research Areas. In: Cudré-Mauroux, P., et al. (eds.) ISWC 2012, Part I. LNCS, vol. 7649, pp. 410–426. Springer, Heidelberg (2012)
Ding, Y.: Community detection: topological vs. topical. Journal of Informetrics 5(4), 498–514 (2011)
Upham, S.P., Small, H.: Emerging research fronts in science and technology: patterns of new knowledge development. Scientometrics 83(1), 15–38 (2010)
Osborne, F., Scavo, G., Motta, E.: Identifying diachronic topic-based research communities by clustering shared research trajectories. In: Presutti, V., d’Amato, C., Gandon, F., d’Aquin, M., Staab, S., Tordai, A. (eds.) ESWC 2014. LNCS, vol. 8465, pp. 114–129. Springer, Heidelberg (2014)
Osborne, F., Motta, E., Mulholland, P.: Exploring Scholarly Data with Rexplore. In: Proceedings of the 12th International Semantic Web Conference (2013)
Flake, G.W., Lawrence, S., Giles, C.L., Coetzee, F.M.: Self-organization and identification of web communities. Computer 35(3), 66–70 (2002)
Smyth Guimera, R., Amaral, L.A.N.: Functional cartography of complex metabolic networks. Nature 433(7028), 895–900 (2005)
Racherla, P., Hu, C.: A social network perspective of tourism research collaborations. Annals of Tourism Research 37(4), 1012–1034 (2010)
Hofmann, T.: Probabilistic latent semantic indexing. In: The 22nd Conference on Research and Development in Information Retrieval (pp, Berkeley, CA, pp. 50–57 (1999)
Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. Journal of Machine Learning Research 3, 993–1033 (2003)
Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., Su, Z.: ArnetMiner: extraction and mining of academic social networks. In: Proceeding of KDD 2008, pp. 990–998 (2008)
Peroni, S., Shotton, D.: FaBiO and CiTO: ontologies for describing bibliographic resources and citations. In: Web Semantics: Science, Services and Agents on the WWW, vol. 17 (2012)
Bezdek, J.C., Ehrlich, R., Full, W.: FCM: The fuzzy c-means clustering algorithm. Computers and Geosciences 10(2), 191–203 (1984)
Olsson, D.M., Nelson, L.S.: The Nelder-Mead simplex procedure for function minimization. Technometrics 17(1), 45–51 (1975)
Neill, D.B., Moore, A.W., Sabhnani, M., Daniel, K.: Detection of emerging space-time clusters. In: Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining, pp. 218–227. ACM (2005)
Sethi, I.K., Patel, N.V.: Statistical approach to scene change detection. In: Symposium on Electronic Imaging: Science & Technology. SPIE (1995)
Chiu, S.L.: Fuzzy model identification based on cluster estimation. Journal of Intelligent and Fuzzy Systems 2(3), 267–278 (1994)
Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5), 28–37 (2001)
Hendler, J.: Where are all the Intelligent Agents? A Letter from the Editor in Intelligent Systems IEEE (May/June 2007)
Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.G.: DBpedia: A nucleus for a web of open data. In: Aberer, K., et al. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)
Pérez, J., Arenas, M., Gutierrez, C.: Semantics and Complexity of SPARQL. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 30–43. Springer, Heidelberg (2006)
Wu, K.L., Yang, M.S.: A cluster validity index for fuzzy clustering. Pattern Recognition Letters 26(9), 1275–1291 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Osborne, F., Scavo, G., Motta, E. (2014). A Hybrid Semantic Approach to Building Dynamic Maps of Research Communities. In: Janowicz, K., Schlobach, S., Lambrix, P., Hyvönen, E. (eds) Knowledge Engineering and Knowledge Management. EKAW 2014. Lecture Notes in Computer Science(), vol 8876. Springer, Cham. https://doi.org/10.1007/978-3-319-13704-9_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-13704-9_28
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13703-2
Online ISBN: 978-3-319-13704-9
eBook Packages: Computer ScienceComputer Science (R0)