Hierarchal Structure of Community and Link Analysis

  • Seema Mishra
  • G. C. Nandi
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 276)


Discovering the hierarchy of organizational structure in a dynamic social network can unveil significant patterns which can help in network analysis. In this paper, we formulated a methodology to establish the most influential person in a temporal communication network from the perspective of frequency of interactions which works on hierarchal structure. With the help of frequency of interactions, we have calculated the individual score of each person from Page Rank algorithm. Subsequently, a graph is generated that showed the influence of each individual in the network. Rigorous experiments we performed using Enron data set to establish a fact that our proposed methodology correctly identifies the influential persons over the temporal network. We have used Enron Company’s email data set that describes how employees of company interacted with each other. We could analyze from our methodology and verify from the facts in the Company’s dataset since after bankruptcy, the result of interactions and behaviors of the individual of the network are absolutely known. Our result shows that the proposed methodology is generic and can be applied to other data sets of communication to identify influential at particular instances.


Dynamic social network analysis social network analysis hierarchal structure 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Seema Mishra
    • 1
  • G. C. Nandi
    • 1
  1. 1.Indian Institute of Information TechnologyAllahabadIndia

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