The centrality of pivotal points in the evolution of scientific networks

ABSTRACT

In this paper, we describe the development of CiteSpace as an integrated environment for identifying and tracking thematic trends in scientific literature. The goal is to simplify the process of finding not only highly cited clusters of scientific articles, but also pivotal points and trails that are likely to characterize fundamental transitions of a knowledge domain as a whole. The trails of an advancing research field are captured through a sequence of snapshots of its intellectual structure over time in the form of Pathfinder networks. These networks are subsequently merged with a localized pruning algorithm. Pivotal points in the merged network are algorithmically identified and visualized using the betweenness centrality metric. An example of finding clinical evidence associated with reducing risks of heart diseases is included to illustrate how CiteSpace could be used. The contribution of the work is its integration of various change detection algorithms and interactive visualization capabilities to simply users' tasks.

REFERENCES

• 1: Shannon Bradshaw , Andrei Scheinkman , Kristian Hammond, Guiding people to information: providing an interface to a digital library using reference as a basis for indexing, Proceedings of the 5th international conference on Intelligent user interfaces, p.37-43, January 09-12, 2000, New Orleans, Louisiana, United States [doi>10.1145/325737.325774]
• 2: Brandes, U. A faster algorithm for betweenness centrality. Journal of Mathematical Sociology, 25, 2 (2001), 163--177.
• 3: Ulrik Brandes , Steven R. Corman, Visual unrolling of network evolution and the analysis of dynamic discourse, Information Visualization, v.2 n.1, p.40-50, March 2003 [doi>10.1057/palgrave.ivs.9500037]
• 4: Chaomei Chen, Detecting and Mapping Thematic Changes in Transient Networks, Proceedings of the Information Visualisation, Eighth International Conference on (IV'04), p.1023-1034, July 14-16, 2004 [doi>10.1109/IV.2004.44]
• 5: Chen, C. Generalised Similarity Analysis and Pathfinder Network Scaling. Interacting with Computers, 10, 2 (1998), 107--128.
• 6: Chen, C. Information Visualization: Beyond the Horizon. Springer, London, 2004.
• 7: Chen, C. Searching for intellectual turning points: Progressive Knowledge Domain Visualization. Proc. Natl. Acad. Sci. USA, 101 (2004), 5303--5310.
• 8: Chen, C. and Morris, S. Visualizing evolving networks: Minimum spanning trees versus Pathfinder networks. In IEEE Symposium on Information Visualization (Seattle, Washington, 2003), IEEE Computer Society Press, 2003, 67--74.
• 9: Deerwester, S., Dumais, S. T., Landauer, T. K., Furnas, G. W. and Harshman, R. A. Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, 41, 6 (1990), 391--407.
• 10: Erten, C., Harding, P. J., Kobourov, S. G., Wampler, K. and Yee, G. Exploring the computing literature using temporal graph visualization. In Conference on Visualization and Data Analysis (VDA) (2004), 2004.
• 11: Freeman, L. C. A set of measuring centrality based on betweenness. Sociometry, 40 (1977), 35--41.
• 12: Girvan, M. and Newman, M. E. J. Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA, 99 (2002), 7821--7826.
• 13: Granovetter, M. Strength of weak ties. American Journal of Sociology, 8 (1973), 1360--1380.
• 14: Susan Havre , Elizabeth Hetzler , Paul Whitney , Lucy Nowell, ThemeRiver: Visualizing Thematic Changes in Large Document Collections, IEEE Transactions on Visualization and Computer Graphics, v.8 n.1, p.9-20, January 2002 [doi>10.1109/2945.981848]
• 15: Kessler, M. M. Bibliographic coupling between scientific papers. American Documentation, 14 (1963), 10--25.
• 16: Jon Kleinberg, Bursty and hierarchical structure in streams, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, July 23-26, 2002, Edmonton, Alberta, Canada [doi>10.1145/775047.775061]
• 17: Mark T. Maybury , Wolfgang Wahlster, Readings in intelligent user interfaces, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1998
• 18: Steven A. Morris , G. Yen , Zheng Wu , Benyam Asnake, Time line visualization of research fronts, Journal of the American Society for Information Science and Technology, v.54 n.5, p.413-422, March 2003 [doi>10.1002/asi.10227]
• 19: Donald A. Norman, The invisible computer, MIT Press, Cambridge, MA, 1998
• 20: Price, D. D. Networks of scientific papers. Science, 149 (1965), 510--515.
• 21: Radicchi, F., Castellano, C., Cecconi, F., Loreto, V. and Parisi, D. Defining and identifying communities in networks arXiv: cond- mat/ 0309488 v1, 2003.
• 22: Warren Sack, Conversation map: a content-based Usenet newsgroup browser, Proceedings of the 5th international conference on Intelligent user interfaces, p.233-240, January 09-12, 2000, New Orleans, Louisiana, United States [doi>10.1145/325737.325856]
• 23: Gerard Salton , James Allan , Chris Buckley, Automatic structuring and retrieval of large text files, Communications of the ACM, v.37 n.2, p.97-108, Feb. 1994 [doi>10.1145/175235.175243]
• 24: Roger W. Schvaneveldt, Pathfinder associative networks: studies in knowledge organization, Ablex Publishing Corp., Norwood, NJ, 1990
• 25: Small, H. G. A co-citation model of a scientific specialty: A longitudinal study of collagen research. Soc. Stud. Sci., 7 (1977), 139--166.
• 26: Swan, R. and Jensen, D. TimeMines: Constructing timelines with statistical models of word usage. In the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2000), 2000.
• 27: White, H. D., Lin, X., Buzydlowski, J. W. and Chen, C. User-controlled mapping of significant literatures. Proc. Natl. Acad. Sci. USA, 101 (2004), 5297--5302.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.3 Communications Applications
          Subjects: Information browsers

General Terms:
Algorithms, Design, Measurement

Keywords:
betweenness centrality, information visualization, intellectual turning points, knowledge domain visualization, research fronts