A Novel Approach to Visualize Co-Authorship and Co-Contribution of Research

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Abstract:

Text visualization method depends on the contents of documents to analyze patterns and abstract characters. However, visualizing the scholar text as an understandable view for users is a challenging. We propose an interactive model to collect, analyse and visualize co-authoring data of publication information. We divide the author to students and advisors. This approach can be used for observe the research performance of students and advisor separately. Especially, we analyse the contribution of each author by presenting the quantity and quality of publications. Meanwhile, the rank of the most important authors is shown in the interface which is designed to access publication details easily. Our conception comes from our experiences designing the Scholar Browser for a university which displays research quality.

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4476-4479

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Thomas, J., and Cook, K., Eds. Illuminating the Path: The Research and Development Agenda for Visual Analytics. IEEE Press, (2005).

Google Scholar

[2] S. Wasserman and K. Faust, Social Network Analysis, Cambridge University Press, Cambridge, (1994).

Google Scholar

[3] Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge University Press.

Google Scholar

[4] Farkas, I., Derenyi, I., Jeong, H., Neda, Z., Oltvai, Z. N., Ravasz, E., et al. (2002). Networks in life: scaling properties and eigenvalue spectra. Physica A, 314, 25–34.

DOI: 10.1016/s0378-4371(02)01181-0

Google Scholar

[5] Newman, M. E. J. (2001a). Scientific collaboration networks: I. Network construction and fundamental results. Physical Review E, 64, 016131.

Google Scholar

[6] Yoshikane. Fuyuki, Nozawa. Takayuki and Tsuji. Keita, Comparative Analysis of Co-authorship Networks Considering Authors' Roles in Collaboration: Differences between the Theoretical and Application Areas, ISSI 2005, July, 2005, vol. 2, pp.509-516.

DOI: 10.1007/s11192-006-0113-1

Google Scholar

[7] M. E. J. Newman, Coauthorship Networks and Patterns of Scientific Collaboration, Proceedings of the National Academy of Sciences, 2004, 101: 5200-5205.

DOI: 10.1073/pnas.0307545100

Google Scholar

[8] Liu, Xiaoming, Johan Bollen, Michael L. Nelson, and Herbert Van de Sompel. Co-authorship networks in the digital library research community., Information processing & management 41, no. 6 (2005): 1462-1480.

DOI: 10.1016/j.ipm.2005.03.012

Google Scholar

[9] Page, Lawrence, Sergey Brin, Rajeev Motwani, and Terry Winograd. The PageRank citation ranking: bringing order to the web., (1999).

Google Scholar

[10] Lempel, Ronny, and Shlomo Moran. The stochastic approach for link-structure analysis (SALSA) and the TKC effect., Computer Networks 33, no. 1 (2000): 387-401.

DOI: 10.1016/s1389-1286(00)00034-7

Google Scholar

[11] Kleinberg, Jon M. Authoritative sources in a hyperlinked environment., Journal of the ACM (JACM) 46, no. 5 (1999): 604-632.

DOI: 10.1145/324133.324140

Google Scholar

[12] Bharat, Krishna, and Monika R. Henzinger. Improved algorithms for topic distillation in a hyperlinked environment., In Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, pp.104-111. ACM, (1998).

DOI: 10.1145/290941.290972

Google Scholar

[13] Chakrabarti, Soumen. Mining the Web: Discovering knowledge from hypertext data. Morgan Kaufmann, (2002).

Google Scholar