The Co-authorship Network of Published Articles in Conferences on Web Research Based on Social Network Analysis

Document Type : Original Article


1 Information Technology dept.,Tarbiat Modares University, Tehran, Iran

2 Information Technology dept., Tarbiat Modares University,Tehran, Iran


Collaboration in writing scientific articles with the growth of academic exchanges and social interactions of researchers is increasingly expanding. Scientific collaboration gives researchers the opportunity to combine the capabilities and abilities of different scientific and research disciplines, which cannot be done individually. Co-authorship is the most formal manifestation of intellectual collaboration between authors in the production of scientific research. On the other hand, the study of the trend of scientific activities and its dynamics in any specialized field is one of the most important concerns of researchers in that field. In recent years, the use of the social network analysis approach has been proposed as a suitable solution to map the scientific structure of specialized fields and the co-authorship network of researchers. In this research, the papers published in six web research conferences have been analyzed to discover the scientific network and the co-authorship based on the social network analysis approach. The results of the analysis show that in the period, concepts such as social network analysis, Internet of Things, cloud computing, and deep learning have the largest share in articles. Also, based on the number of communities formed, the authors of the conference papers were more inclined to form small scientific groups in the form of universities or research institutes of their respective organizations.


Main Subjects

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  • keywords of high frequency in six conferences
  • trend of keywords
  • information about the five main communities of the scientific network under study.







Percentage of total network






No. of nodes






No. of edges






Ratio of edge to node






Community density






Keyword (based on betweenness centrality)




Internet of Things


Social Network


Cloud Computing


Semantic Web


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Meysam Alavi was born in Hamadan, Iran. He received his B.Sc. and an M.Sc. degree in Computer Engineering - Software in 2005 and 2010 respectively. Currently, he is an M.Sc. student in Information Technology at Tarbiat Modares University. His research interests include medical image processing, machine learning, data mining, social network analysis

Sayed Ali Lajevardy received his B.Sc in Mechanic Engineering, Amirkabir University, Tehran, Iran in 2008 and received his M.Sc degree in Information Technology, Tarbiat Modares University, Tehran, Iran in 2014. He is PHD senior in Information Technology, Tarbiat Modares University from 2017. His research interests include machine learning, bioinformatics and data gathering.