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Rumor Source Identification on Social Networks: A Combined Network Centrality Approach

  • 2021
  • OriginalPaper
  • Chapter
Published in:
Authors
Abhijit Das
Anupam Biswas
Published in
Progress in Advanced Computing and Intelligent Engineering
Publisher
Springer Singapore

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Abstract

This chapter delves into the critical issue of rumor source identification on social networks, highlighting the significant impact of malicious rumors on society. It introduces the combined network centrality approach (CNCA), a novel method that leverages the susceptible-infected (SI) model and integrates betweenness centrality and rumor centrality to improve the probability of accurate source detection. The study compares CNCA with existing methods such as rumor centrality, betweenness centrality, and Jordan centrality, demonstrating its superior performance through extensive simulations on real-world datasets. The chapter concludes by suggesting future research directions, emphasizing the potential of combining other centrality measures to further enhance rumor source identification in complex social networks.
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previous chapter Developing a Framework for Generating Hotel Recommendation
next chapter Sentiment Polarity Detection on Bengali Book Reviews Using Multinomial Naïve Bayes
Title
Rumor Source Identification on Social Networks: A Combined Network Centrality Approach
Authors
Abhijit Das
Anupam Biswas
Copyright Year
2021
Publisher
Springer Singapore
Book
Progress in Advanced Computing and Intelligent Engineering

Print ISBN: 978-981-334-298-9

Electronic ISBN: 978-981-334-299-6

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-33-4299-6_22
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