Exploratory Experiment on Co-Authorship Network using Social Network Analysis Metrics and Measures

  • Authors

    • Pritheega Magalingam
    • Ganthan Narayana Samy
    • Nurazean Maarop
    • Wan Nazirul Hafeez Wan Safie
    • Muhammad Khairul Rijal
    • Lim Yee Fang
    • Abdullah Sakib
    • Muhammad Yassin
    2018-11-30
    https://doi.org/10.14419/ijet.v7i4.35.23108
  • Degree Centrality, Betweenness Centrality, Ego Network, Community Detection, Clique.

  • This paper contributes in understanding and gaining meaningful insight about the relationship among the scientist in the co-authorship network using social network analysis. We argue that the relationship analysis is not always a straightforward process. In the past one single measure, for example, the egocentric or centrality measure was used to describe the scientific collaboration patterns separately. In this paper, various analysis such as centrality analysis, ego network, community detection, largest clique and word frequency have been used to examine and interpret the collaboration among the authors. This research is not dominated by known researchers but involves an overall exploration of the network. Our research is mainly guided by the creation of research issues, assessing the type of dataset and the objectives for presenting the co-authorship relationships. It is important to identify the motive of the selected measures in order to achieve the predefined objective. Specific methodology and procedures are designed to solve each research issue respectively. This study reveals that the network interpretation should not be solely based on one network measure, but an explorative analysis results need to be considered because it allows exploring the hidden information through the changes in the network structure, topology patterns and nodes’ position.

  • References

    2. style='mso-bidi-font-size:8.0pt'>
    3. style='mso-spacerun:yes'> ADDIN EN.REFLIST
    4. field-separator'>[1] A. Abbasi, K. S. K. Chung, and L. Hossain, "Egocentric analysis of co-authorship network structure, position and performance," Information Processing & Management, vol. 48, no. 4, pp. 671-679, 2012.

      [2] T. Ahmed, A. Ahmed, M. Ali, and M. Kamran, "Analysis of co-authorship in computer networks using centrality measures," in Communication, Computing and Digital Systems (C-CODE), International Conference on, 2017, pp. 54-57: IEEE.

      [3] S. Allesina, A. Bodini, and C. Bondavalli, "Ecological subsystems via graph theory: the role of strongly connected components," Oikos, vol. 110, no. 1, pp. 164-176, 2005.

      [4] V. Arnaboldi, R. I. Dunbar, A. Passarella, and M. Conti, "Analysis of co-authorship ego networks," in International Conference and School on Network Science, 2016, pp. 82-96: Springer.

      [5] V. D. Blondel, J.-L. Guillaume, R. Lambiotte, and E. Lefebvre, "Fast unfolding of communities in large networks," Journal of statistical mechanics: theory and experiment, vol. 2008, no. 10, p. P10008, 2008.

      [6] P. Bonacich, "Power and centrality: A family of measures," American journal of sociology, vol. 92, no. 5, pp. 1170-1182, 1987.

      [7] J. Cong and M. L. Smith, "A parallel bottom-up clustering algorithm with applications to circuit partitioning in VLSI design," in Proceedings of the 30th international Design Automation Conference, 1993, pp. 755-760: ACM.

      [8] J. F. Delgado-Garcia, A. H. Laender, and W. Meira, "Analyzing the Coauthorship Networks of Latin American Computer Science Research Groups," in Web Congress (LA-WEB), 2014 9th Latin American, 2014, pp. 77-81: IEEE.

      [9] S. Fortunato, "Community detection in graphs," Physics reports, vol. 486, no. 3-5, pp. 75-174, 2010.

      [10] L. C. Freeman, "Centrality in social networks conceptual clarification," Social networks, vol. 1, no. 3, pp. 215-239, 1978.

      [11] N. Gaskó, R. I. Lung, and M. A. Suciu, "A new network model for the study of scientific collaborations: Romanian computer science and mathematics co-authorship networks," Scientometrics, vol. 108, no. 2, pp. 613-632, 2016.

      [12] T. Grünert, S. Irnich, H.-J. Zimmermann, M. Schneider, and B. Wulfhorst, "Finding all k-cliques in k-partite graphs, an application in textile engineering," Computers & operations research, vol. 29, no. 1, pp. 13-31, 2002.

      [13] H. Guércio, V. Ströele, J. M. N. David, R. Braga, and F. Campos, "Topological analysis in scientific social networks to identify influential researchers," in Computer Supported Cooperative Work in Design (CSCWD), 2017 IEEE 21st International Conference on, 2017, pp. 287-292: IEEE.

      [14] A.-W. Harzing, "Publish or perish," 2007.

      [15] M. U. Ilyas and H. Radha, "Identifying influential nodes in online social networks using principal component centrality," in Communications (ICC), 2011 IEEE International Conference on, 2011, pp. 1-5: IEEE.

      [16] E. Y. Li, C. H. Liao, and H. R. Yen, "Co-authorship networks and research impact: A social capital perspective," Research Policy, vol. 42, no. 9, pp. 1515-1530, 2013.

      [17] P. Magalingam, S. Davis, and A. Rao, "Using shortest path to discover criminal community," Digital Investigation, vol. 15, pp. 1-17, 2015.

      [18] P. Magalingam, A. Rao, and S. Davis, "Identifying a criminal's network of trust," in Signal-Image Technology and Internet-Based Systems (SITIS), 2014 Tenth International Conference on, 2014, pp. 309-316: IEEE.

      [19] M. E. Newman, "Modularity and community structure in networks," Proceedings of the national academy of sciences, vol. 103, no. 23, pp. 8577-8582, 2006.

      [20] M. E. J. Newman, Phys. Rev. E 74, 036104, 2006.

      [21] Q. Niu, A. Zeng, Y. Fan, and Z. Di, "Robustness of centrality measures against network manipulation," Physica A: Statistical Mechanics and its Applications, vol. 438, pp. 124-131, 2015.

      [22] S. Papadopoulos, Y. Kompatsiaris, A. Vakali, and P. Spyridonos, "Community detection in social media," Data Mining and Knowledge Discovery, vol. 24, no. 3, pp. 515-554, 2012.

      [23] M. C. Paull and S. H. Unger, "Minimizing the number of states in incompletely specified sequential switching functions," IRE Transactions on Electronic Computers, no. 3, pp. 356-367, 1959.

      [24] P. Pons and M. Latapy, "Computing communities in large networks using random walks," in International symposium on computer and information sciences, 2005, pp. 284-293: Springer.

      [25] M. Rosvall and C. T. Bergstrom, "Maps of random walks on complex networks reveal community structure," Proceedings of the National Academy of Sciences, vol. 105, no. 4, pp. 1118-1123, 2008.

      [26] V. Spirin and L. A. Mirny, "Protein complexes and functional modules in molecular networks," Proceedings of the National Academy of Sciences, vol. 100, no. 21, pp. 12123-12128, 2003.

      [27] L. Sun and I. Rahwan, "Coauthorship network in transportation research," Transportation Research Part A: Policy and Practice, vol. 100, pp. 135-151, 2017.

      [28] K. Sutaria, D. Joshi, C. Bhensdadia, and K. Khalpada, "An adaptive approximation algorithm for community detection in social network," in Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on, 2015, pp. 785-788: IEEE.

      [29] X. Zhang et al., "Overlapping community identification approach in online social networks," Physica A: Statistical Mechanics and its Applications, vol. 421, pp. 233-248, 2015.

      [30] Z. Zhao, S. Feng, Q. Wang, J. Z. Huang, G. J. Williams, and J. Fan, "Topic oriented community detection through social objects and link analysis in social networks," Knowledge-Based Systems, vol. 26, pp. 164-173, 2012.

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    6. KO;mso-bidi-language:AR-SA'>

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    Magalingam, P., Samy, G. N., Maarop, N., Wan Safie, W. N. H., Rijal, M. K., Fang, L. Y., Sakib, A., & Yassin, M. (2018). Exploratory Experiment on Co-Authorship Network using Social Network Analysis Metrics and Measures. International Journal of Engineering & Technology, 7(4.35), 782-790. https://doi.org/10.14419/ijet.v7i4.35.23108