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Erjia Yan School of Library and Information Science, Indiana University, Bloomington, IL, USA dingying@indiana.eduejacob@indiana.edu

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Ying Ding School of Library and Information Science, Indiana University, Bloomington, IL, USA dingying@indiana.eduejacob@indiana.edu

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Elin K. Jacob School of Library and Information Science, Indiana University, Bloomington, IL, USA dingying@indiana.eduejacob@indiana.edu

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Abstract

Two layers of enriched information are constructed for communities: a paper-to-paper network based on shared author relations and a paper-to-paper network based on shared word relations. k-means and VOSviewer, a modularity-based clustering technique, are used to identify publication clusters in the two networks. Results show that a few research topics such as webometrics, bibliometric laws, and language processing, form their own research community; while other research topics contain different research communities, which may be caused by physical distance.

  • Allen, C. (2004). Life with alacrity: The Dunbar number as a limit to group sizes. Retrieved 19 April 2010 from http://www.lifewithalacrity.com/2004/03/the_dunbar_numb.html.

    • Search Google Scholar
    • Export Citation
  • Åström, F 2010 The visibility of information science and library science research in bibliometric mapping of the LIS field. The Library Quarterly 80 2 143159 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blei, DM, Ng, AY, Jordan, MI 2003 Latent Dirichlet allocation. Journal of Machine Learning Research 3:9931033.

  • Blei, D. M., & Lafferty, J. D. (2007). A corrected model of science. Annals of Applied Statistics, 1, 1735.

  • Clauset, A, Newman, MEJ, Moore, C 2004 Finding community structure in very large network. Physical Review E 70:066111 .

  • Ding, Y. (2011). Community detection: Topological vs. topical. Journal of Informetrics. doi: .

  • Donetti, L, Munoz, MA 2004 Detecting network communities: A new systematic and efficient algorithm. Journal of Statistical Mechanics: Theory and Experiment 2004:P10012 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunbar, R 1998 Grooming, gossip, and the evolution of language Harvard University Press Boston.

  • Farkas, I, Ábel, D, Palla, G, Vicsek, T 2007 Weighted network modules. New Journal of Physics 9 6 180209 .

  • Fortunato, S 2010 Community detection in graphs. Physics Reports 486 3–5 75174 .

  • Girvan, M, Newman, MEJ 2002 Community structure in social and biological networks. Proceedings of the National Academy of Sciences of the United States of America 99 12 78217826 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hofmann, T. (1999). Probabilistic latent semantic indexing. In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 5057), 15-19 Aug 1999, Berkeley, CA.

    • Search Google Scholar
    • Export Citation
  • Leskovec, J., Lang, K. J., Dasgupta, A., & Mahoney, M. W. (2008). Community structure in large networks: Natural cluster sizes and the absence of large well-defined clusters. Retrieved 21 Mar 2010 from http://arxiv.org/abs/0810.1355.

    • Search Google Scholar
    • Export Citation
  • Li, D., He, B., Ding, Y., Tang, J., Sugimoto, C., Qin, Z., et al. (2010). Community-based topic modeling for social tagging. In The 19th ACM International Conference on Information and Knowledge Management (CIKM2010) (pp. 15651568), 26-30 Oct 2010, Toronto, Canada.

    • Search Google Scholar
    • Export Citation
  • Morris, SA B Van der Veer Martens 2008 Modeling and mapping of research specialties. Annual Review of Information Science and Technology 42 1 213295 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, MEJ 2001 The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences of the United States of America 98 2 404409 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, MEJ 2006 Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America 103 23 85778582 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Newman, M, Girvan, M 2004 Finding and evaluating community structure in networks. Physical Review E 69:026113 .

  • Nisonger, TE, Davis, CH 2005 The perception of library and information science journals by LIS education deans and ARL library directors: A replication of the Kohl-Davis study. College & Research Libraries 66:341377.

    • Search Google Scholar
    • Export Citation
  • Persson, O 1994 The Intellectual base and research fronts of JASIS 1986–1990. Journal of the American Society for Information Science 45 1 3138 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Radicchi, F, Castellano, C, Cecconi, F, Loreto, V, Parisi, D 2004 Defining and identifying communities in networks. Proceedings of the National Academy of Sciences of the United States of America 101 9 26582663 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Richardson, T, Mucha, PJ, Porter, MA 2009 Spectral tripartitioning of networks. Physical Review E 80:036111 .

  • Steyvers, M., Smyth, P., Rosen-Zvi, M., & Griffiths, T. (2004). Probabilistic author-topic models for information discovery. In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 306315). New York: ACM Press.

    • Search Google Scholar
    • Export Citation
  • Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., & Su, Z. (2008). ArnetMiner: Extraction and mining of academic social networks. In Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 990998), Las Vegas.

    • Search Google Scholar
    • Export Citation
  • Waltman, L NJ van Eck Noyons, ECM 2010 A unified approach to mapping and clustering of bibliometric networks. Journal of Informetrics 4 4 629635 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Waltman, L., Yan, E., & van Eck, N. J. (2011). A recursive field-normalized bibliometric performance indicator: An application to the field of library and information science. Scientometrics, 89 (1), 301314.

    • Search Google Scholar
    • Export Citation
  • White, HD 2003 Pathfinder networks and author cocitation analysis: A remapping of paradigmatic information scientists. Journal of the American Society for Information Science 54 5 423434 .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • White, HD, Mccain, KW 1998 Visualizing a discipline: An author co-citation analysis of information science, 1972–1995. Journal of the American Society for Information Science 49 4 327355.

    • Search Google Scholar
    • Export Citation
  • Yan, E., Ding, Y., & Zhu, Q. (2010). Mapping library and information science in China: A coauthorship network analysis. Scientometrics, 83 (1), 115131.

    • Search Google Scholar
    • Export Citation
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Scientometrics
Language English
Size B5
Year of
Foundation
1978
Volumes
per Year
1
Issues
per Year
12
Founder Akadémiai Kiadó
Founder's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 0138-9130 (Print)
ISSN 1588-2861 (Online)