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(T-ToCODE): A Framework for Trendy Topic Detection and Community Detection for Information Diffusion in Social Network

  • Reena PagareEmail author
  • Akhil Khare
  • Shankar Chaudhary
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1042)

Abstract

The increased use of social network generates a huge amount of data. Extracting useful information from this huge data available is the need of today. Study and analysis of this data generated provide insight into the behavior of the customers or users and thus will be beneficial to increase the sales of products or understand customers. To achieve the same, we propose a novel framework which will extract trendy topics, identify communities related to these trendy, topics, and also identify influential or seed nodes in communities. The framework intends to find the list of topics which are popular, second, find trend-driven communities, and from these trend-driven communities find nodes which act as seed nodes and thus dominate the spread of information in the community. Analysis of real-world data is done and results are compared with baseline approaches.

Keywords

Community detection Information diffusion Topic detection Trend topics Social network 

Notes

Acknowledgements

The authors declare that they have no conflict of interest. All procedures performed in studies involving human participants were in accordance with the ethical standards. Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.PAHERUdaipurIndia
  2. 2.MVSR COEHyderabadIndia

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