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Reseach Article

Scientific Co-authorship Social Networks: A Case Study of Computer Science Scenario in India

by Tasleem Arif, Rashid Ali, M. Asger
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 52 - Number 12
Year of Publication: 2012
Authors: Tasleem Arif, Rashid Ali, M. Asger
10.5120/8257-1790

Tasleem Arif, Rashid Ali, M. Asger . Scientific Co-authorship Social Networks: A Case Study of Computer Science Scenario in India. International Journal of Computer Applications. 52, 12 ( August 2012), 38-45. DOI=10.5120/8257-1790

@article{ 10.5120/8257-1790,
author = { Tasleem Arif, Rashid Ali, M. Asger },
title = { Scientific Co-authorship Social Networks: A Case Study of Computer Science Scenario in India },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 52 },
number = { 12 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 38-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume52/number12/8257-1790/ },
doi = { 10.5120/8257-1790 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:52:05.892012+05:30
%A Tasleem Arif
%A Rashid Ali
%A M. Asger
%T Scientific Co-authorship Social Networks: A Case Study of Computer Science Scenario in India
%J International Journal of Computer Applications
%@ 0975-8887
%V 52
%N 12
%P 38-45
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Co-authorship is one of the most tangible and well documented forms of research collaboration. Data mining techniques and social network analysis can be used to extract and study these collaborations. Social network analysis provides an insight into the connections between groups of individuals. It is these connections that channel flow of information and the sharing of knowledge. In order to understand flow of information and interpret collaboration, co-authorship can be used as a measure to study intra and inter organization collaborations. In this paper, we analyze the collaboration scenario in Computer Science in India, and access how researchers in few of the best Indian Institutes of Technology (IITs) collaborate and relate to each other. We construct and visualize scientific co-authorship social network graphs of these institutions. We also compare and contrast network metrics for these institutes and experimentally deduce that these networks like other social networks exhibit "small world" properties.

References
  1. Merriam-Webster's Collegiate Dictionary (1999). Tenth Edition. Springfield, MA: Merriam-Webster, Incorporated.
  2. Stroele, V. , Oliveira, J. , Zimbrao, G. and Souza, M. J. "Mining and Analyzing Multirelational Social Networks. " In Proceedings of 12th International Conference on Computational Science and Engineering, Vancouver, Canada, 2009, pp 711-716.
  3. Patel, N. "Collaboration in the professional growth of American sociology. " Social Science Information, 6, 1973, pp. 77-92.
  4. Glanzel, W. and Schubert, A. "Analysing Scientific Networks Through Co-authorship. " Handbook of Quantitative Science and Technology Research, 2004, Kluwer Academic Publishers.
  5. Wasserman, S. and Faust, K. "Social Network Analysis: Methods and Applications. " Cambridge University Press, New York City, New York, 1994, U. S. A.
  6. Newman, MEJ. "Co-authorship networks and patterns of scientific collaboration. " In Proceedings of the National Academy of Sciences, 101(1), 2001, pp. 5200-5.
  7. Davis, G. F. and Greve, H. R. "Corporate Elite Networks and Governance Changes in the 1980s. " The American Journal of Sociology, 103(1), 1997, pp. 1-37.
  8. Stuart, T. E. "Network Positions and Propensities to Collaborate: An Investigation of Strategic Alliance Formation in a High-technology Industry. " Administrative Science Quarterly, 43(3), 1998, pp. 668-98.
  9. Chakrabarti, S. "Mining the Web: Discovering Knowledge from Hypertext Data. " Morgan Kaufmann Publishers, USA, 2003.
  10. Tang, J. , Zhang, D. , and Yao, L. "Social Network Extraction of Academic Researchers. " In Proceedings of International Conference on Data Mining-ICDM'07, Nebraska, USA, October 2007, pp 292-301.
  11. Tomobe, H. , Matsuo, Y. and Hasida, K. "Social Network Extraction of Conference Participants. " In Proceedings of 12th International Conference on World Wide Web-WWW'03, Budapest, Hungary, May 2003.
  12. Kautz, H. , Selman, B. , and Shah, M. "The Hidden Web. " American Association for Artificial Intelligence magazine, 18(2), 1997, pp 27–35.
  13. Mika, P. "Flink: Semantic web technology for the extraction and analysis of social networks. " Journal of Web Semantics, 3(2), 2005, pp 211-223.
  14. Newman, MEJ. "Scientific collaboration Networks-II. Shortest paths, weighted networks, and centrality. " Physical Review E, Volume 64,016132
  15. Newman, MEJ. "The structure of scientific collaboration networks. " PNAS, January, 2001, 98(2), pp 404-409
  16. Newman, MEJ. "Co-authorship networks and patterns of scientific collaboration. " In Proceedings of the National Academy of Sciences, 101(90001), 2004, pp. 5200-5205.
  17. Newman, MEJ. "Scientific Collaboration Networks-I. Network Construction and Fundamental Results. " Physical Review E, 64(1):16131, 2001.
  18. Moody, J. "The structure of a social science collaboration network: Disciplinary Cohesion from 1963 to 1999. " American Sociological Review, 69(2), 2004, pp. 213-238.
  19. Liu, X. , Bollen, J. Nelson, M. L. and Van de Sompel. H. "Coauthorship networks in the digital library research community. " Information Pro-cessing & Management, 41(6), 2005, pp. 1462-1480.
  20. Sharma, M. and Urs, S. R. , "Network Dynamics of Scholarship: A Social Network Analysis of Digital Library Community. " In Proceeding of the 2nd PhD Workshop on Information and Knowledge Management, New York, NY, USA, 2008, pp. 101-104.
  21. Elmacioglu, E. and Lee, D. "On six degrees of separation in dblp-db and more. " SIGMOD Rec. , 34(2), 2005, pp. 33-40.
  22. Ma, L. , Goharian, G. and Chowdhury, A. "Automatic data extraction template generated web pages. " In Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 03), Las Vegas, Nevada, USA, 2003, pp. 642–648.
  23. Milgram, S. "The Small World Problem. " Psychology Today, 2(1), 1967, pp. 60-67.
  24. Newman, M. E. J. "Community centrality. " Phys. Reviews 74 (2006).
  25. Chelmis, C. and Prasanna, V. K. "Social Networking Analysis: A State of the Art and the Effect of Semantics. " In Proceedings of 3rd IEEE Conference on Social Computing (SocialCom), Boston, MA, 2011, pp. 531-536.
  26. http://en. wikipedia. org/wiki/Centrality
  27. http://en. wikipedia. org/wiki/Clustering_coefficient
  28. Watts, D. J. and Strogatz, S. H. "Collective dynamics of 'small-world' networks. " Nature, 393(6684), June 1998, pp. 440–442.
  29. Hansen, D. , Shneiderman, B. , and Smith, M. A. "Analyzing Social Media Networks with NodeXL: Insights from a Connected World. " Morgan Kaufmann, Burlington, MA, USA, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Co-authorship Networks Visualization IIT