Presenting an optimal method for identifying communities in the Instagram’s social network with clustering method

The IJNCPS's Authors that presented the article:

  • Fateme Panabad Department of Computer Engineering,Ahvaz Branch, Islamic Azad University Ahvaz,Iran
  • Seyyed Mohammad Safi Department of Computer Engineering, Ahvaz Branch, Islamic Azad University Ahvaz,Iran
Keywords: social networks, recognizing societies, community identification, community identification algorithms, clustering method


In today's world, social networks play an essential role in expanding information.One of themost important issues is identification of communities in these networks.In previous methods, the identification of communities was such that the number of “Like” feedbacksfor each member in one group was determined regardless the number of member posts, and any member with more likes was identified as a more effective member.In the proposed method, the number of feedbacks to each member's post is determined by separating the posts of each member.As a result, the important posts are identified. Thus, the generated graph provides more comprehensive information about the communications of individuals. The new graph is then grouped by community identification methods such as Girvan Newman, CNM, Wakita Tsurumi and the final result will be presented as the final optimal result by voting on the results of the three above-mentioned methods.


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