Study of evolving co-authorship network: identification of growth patterns of collaboration using SNA measures

Department

Department of Computer Science

Was this content written or created while at IBA?

Yes

Document Type

Conference Paper

Publication Date

3-29-2017

Author Affiliation

  • Samreen Kazi is PhD Scholar at the Department of Computer Science, Institute of Business Administration, Karachi
  • Quratulain Rajput is Assistant Professor at Institute of Business Administration, Karachi
  • Shakeel Ahmed Khoja is Professor at Institute of Business Administration, Karachi

Conference Name

2017 IEEE 11th International Conference on Semantic Computing (ICSC)

Conference Location

San Diego, CA, USA

Conference Dates

30 January-1 February 2017

ISBN/ISSN

85018248462 (Scopus)

First Page

488

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Abstract / Description

In the recent past, macro-level measures of the network have become more popular within complex social networks such as detection of patterns of growth in social network, a community structure or a Heavy-tailed degree distribution. These measures have been reinvented to gain more insight into structural properties due to the fact that many mathematical models do not show these features. This article has studied complex co-authorship network via same classic approach for finding the corresponding properties like authorship patterns, trends of collaboration, the evolution of core component and ranking authors. In this article, we have also analyzed network diameter, clustering coefficient and degree distribution in time span of 50 years and suggested that these measures can be useful indicators for the patterns of connectivity, identifying small world phenomena and identifying the scale-free property of network.

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