Abstract
Data reflecting social and business relations has often form of network of connections between entities (called social network). In such network important and influential users can be identified as well as groups of strongly connected users. Finding such groups and observing their evolution becomes an increasingly important research problem. Analyzing the evolution of communities is useful in many applications such as marketing, politics or public security domains. One of the significant problems is to develop method incorporating not only information about connections between entities but also information obtained from text written by the users. Method presented in this chapter combine social network analysis and text mining in order to understand groups evolution. Presented approach to the group evolution process takes many aspects of the group analysis into consideration. Due to proposed method the subjects discussed within the groups are known. We noticed that subjects discussed within groups play significant roles in group evolutions.
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Gliwa, B., Zygmunt, A., Bober, P. (2015). Analysis of Content of Posts and Comments in Evolving Social Groups. In: Mach-Król, M., M. Olszak, C., Pełech-Pilichowski, T. (eds) Advances in ICT for Business, Industry and Public Sector. Studies in Computational Intelligence, vol 579. Springer, Cham. https://doi.org/10.1007/978-3-319-11328-9_3
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