Extraction, Visualisation and Analysis of Co- Authorship Based Academic Social Networks

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-23 Number-2
Year of Publication : 2015
Authors : Tasleem Arif
  10.14445/22312803/IJCTT-V23P118

MLA

Tasleem Arif "Extraction, Visualisation and Analysis of Co- Authorship Based Academic Social Networks". International Journal of Computer Trends and Technology (IJCTT) V23(2):85-91, May 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In an online social network environment we establish relationships by sharing status, by way of likes, or tweets and retweets. However, these relationships are casual whereas the relationship established through co-authorship is much more formalized. Through this co-authorship relationship, researchers form academic social networks. In order to study these networks the co-authorship data has to obtained and used. Digital libraries like DBLP, Microsoft Academic Search, etc. provide a rich source of co-authorship information on the Internet. In addition to these digital libraries institutional websites also prove to be a rich source of co-authorship information of people working with that institution. Analysis of this co-authorship relationship provides a whole lot of information about authors and research activities carried out in an institution. In this paper we use social network analysis metrics to study these academic social networks obtained from the underlying co-authorship relationship. We obtained and analyzed social network both at institutional as well as individual author level to understand their research collaborations. It was observed that at the institutional level people have very few collaborations with people within their organization.

References
[1] H.W. Chang, and M.H. Huang, Cohesive subgroups in the international collaboration network in astronomy and astrophysics. Scientometrics, Vol. 101, No.3, pp. 1587-1607, 2014.
[2] D. Zhao and A. Strotmann, The knowledge base and research front of information science 2006–2010: An author cocitation and bibliographic coupling analysis. Journal of the Association for Information Science and Technology, Vol. 65, No. 5, pp. 995–1006, 2014.
[3] T. Arif, R. Ali, and M. Asger, Scientific co-authorship social networks: A case study of computer science scenario in India. International Journal of Computer Applications, Vol. 52, No. 12, pp. 38-45, 2012.
[4] G. Vidican, W. L. Woon, and S. Madnick, Measuring innovation using bibliometric techniques: The case of solar photovoltaic industry. Working Paper CISL# 2009-05, Massachusetts Institute of Technology, Cambridge, MA 02142, 2009.
[5] V.I. Torvik, M. Weeber, D.R. Swanson, and N.R. Smalheiser, A probabilistic similarity metric for Medline records: A model for author name disambiguation: Research articles. Journal of the American Society for Information Science and Technology, Vol. 56, No. 2, pp. 140–158, 2005.
[6] N.R. Smalheiser and V.I. Torvik, Author name disambiguation. Annual Review of Information Science and Technology,Vol. 43, No. 1, pp. 1–43, 2009.
[7] A.A. Ferreira, G.A. Gonçalves, and H.F.A. Laender, A brief survey of automatic methods for author name disambiguation. ACM SIGMOD Record, Vol. 41, No. 2, pp. 15-26, 2012.
[8] T. Arif, R. Ali, and M. Asger, Author name disambiguation using vector space model and hybrid similarity measures. In Proceedings of 7th International Conference on Contemporary Computing-IC3‘2014, Noida, India: IEEE. pp. 135-140, 2014.
[9] F. Ma, Y. Li, and B. Chen, Study of the collaboration in the field of the Chinese humanities and social sciences. Scientometrics, May 2014.
[10] M. Coscia, F. Giannotti, and R. Pensa, Social Network Analysis as Knowledge Discovery process: A case study on Digital Bibliography. In Proceedings of 2009 Advances in Social Network Analysis and Mining, pp. 279-283, 2009.
[11] M. E. Newman, The structure of scientific collaboration networks. Proceedings of the National Academy of Sciences, Vol. 98, No. 2, pp. 404–409, 2001.
[12] H. Hou, H. Kretschmer and Z. Liu, The structure of scientific collaboration networks in scientometrics. Scientometrics, Vol. 75, No. 2, pp. 189–202, 2008.
[13] C. Chelmis, and V.K. Prasanna, 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, 2011.
[14] D.J. Watts and S.H. Strogatz, Collective dynamics of ‘smallworld’ networks. Nature, Vol. 393, No. 6684, pp. 440–442, 1998.
[15] S. Milgram, The Small World Problem. Psychology Today, Vol. 2, No. 1, pp. 60-67, 1967.
[16] D. Fisher, Using egocentric networks to understand communication. IEEE Internet Computing, Vol. 9, No.5, pp. 20-28, 2005.

Keywords
Extraction & Visualisation, Academic Social Network, Co-authorship, Digital Libraries.