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Twitter financial community modeling using agent based simulation

Yang, Steve Y., Liu, Anqi ORCID: and Mo, Sheung Yin Kevin 2014. Twitter financial community modeling using agent based simulation. Presented at: 2014 Computational Intelligence for Financial Engineering & Economics (CIFEr), London, UK, 27-28 March 2014. 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr). IEEE, 10.1109/CIFEr.2014.6924055

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With the empirical evidence that Twitter influences the financial market, there is a need for a bottom-up approach focusing on individual Twitter users and their message propagation among a selected Twitter community with regard to the financial market. This paper presents an agent-based simulation framework to model the Twitter network growth and message propagation mechanism in the Twitter financial community. Using the data collected through the Twitter API, the model generates a dynamic community network with message propagation rates by different agent types. The model successfully validates against the empirical characteristics of the Twitter financial community in terms of network demographics and aggregated message propagation pattern. Simulation of the 2013 Associated Press hoax incident demonstrates that removing critical nodes of the network (users with top centrality) dampens the message propagation process linearly and critical node of the highest betweenness centrality has the optimal effect in reducing the spread of the malicious message to lesser ratio of the community.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: H Social Sciences > HG Finance
H Social Sciences > HM Sociology
Q Science > QA Mathematics
Publisher: IEEE
ISBN: 9781479923809
ISSN: 2380-8454
Date of First Compliant Deposit: 5 February 2018
Last Modified: 23 Oct 2022 12:51

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