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<p>With its various real-life applications, predicting community evolution is a challenging task in the field of social network analysis. In this paper, we analyze communities’ evolution prediction accuracy in dynamic social networks. The proposed approach combines several key concepts of the process: (1) a tailored network splitting that results in snapshots of different periods rather than a static one, (2) an event detection method for simultaneously detecting and tracking community structures in dynamic social networks, and (3) the change rates of communities’ features that characterize them over time instead of absolute values of features. Our experiments on four real-world social networks confirm that community evolution prediction can be achieved with a very high accuracy by using both tailored network splitting as a first step of prediction process and change rates of features.</p>

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Prediction of Community Evolution with Com_Tracker Using Tailored Network Splitting and Community Features’ Change Rates

  • 期刊论文

  • 发表日期：

    2025年3月28日

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  • Narimene Dakiche,
  • Fatima Benbouzid-Si Tayeb,
  • Karima Benatchba,
  • Yahya Slimani

摘要

With its various real-life applications, predicting community evolution is a challenging task in the field of social network analysis. In this paper, we analyze communities’ evolution prediction accuracy in dynamic social networks. The proposed approach combines several key concepts of the process: (1) a tailored network splitting that results in snapshots of different periods rather than a static one, (2) an event detection method for simultaneously detecting and tracking community structures in dynamic social networks, and (3) the change rates of communities’ features that characterize them over time instead of absolute values of features. Our experiments on four real-world social networks confirm that community evolution prediction can be achieved with a very high accuracy by using both tailored network splitting as a first step of prediction process and change rates of features.