2011Unpublished venueRequires access

Community Evolution in Dynamic Social Networks -- Challenges and Problems

Mansoureh Takaffoli

Open publisher page 12 citations

Abstract

Information networks that describe the relationship between individuals are called social networks and are usually modeled by a graph structure. Social network analysis is the study of these information networks which leads to uncover patterns of interaction among the entities. Most social networks are dynamic, and studying the evolution of these networks over time could provide insight into the changes that occurred in the iteration patterns and also the future trends of the networks. Furthermore, in a dynamic scenario, communities, which are groups of densely interconnected nodes, are affected by changes in the underlying population. The analysis of communities and their evolutions can help determine the characteristics and structural properties of the network. Here, we provide a brief overview of the existing research in the area of dynamic social network analysis, their limitations, and the challenges that are exists for further analysis.

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What this paper is about

Information networks that describe the relationship between individuals are called social networks and are usually modeled by a graph structure. Social network analysis is the study of these information networks which leads to uncover patterns of interaction among the entities. Most social networks are dynamic, and studying the evolution of these networks over time could provide insight into the changes that occurred in the iteration patterns and also the future trends of the networks. Furthermore, in a dynamic scenario, communities, which are groups of densely interconnected nodes, are affected by changes in the underlying population. The analysis of communities and their evolutions can help determine the characteristics and structural properties of the network. Here, we provide a brief overview of the existing research in the area of dynamic social network analysis, their limitations, and the challenges that are exists for further analysis.

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OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Information networks that describe the relationship between individuals are called social networks and are usually modeled by a graph structure. Social network analysis is the study of these information networks which leads to uncover patterns of interaction among the entities. Most social networks are dynamic, and studying the evolution of these networks over time could provide insight into the changes that occurred in the iteration patterns and also the future trends of the networks. Furthermore, in a dynamic scenario, communities, which are groups of densely interconnected nodes, are affected by changes in the underlying population. The analysis of communities and their evolutions can help determine the characteristics and structural properties of the network. Here, we provide a brief overview of the existing research in the area of dynamic social network analysis, their limitations, and the challenges that are exists for further analysis.

Key concepts: Dynamic network analysis, Computer science, Social network analysis, Evolving networks, Network science, Social network (sociolinguistics), Data science, Network analysis

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