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Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate

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Title: Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate
Authors: Amor, B
Vuik, S
Callahan, R
Darzi, A
Yaliraki, SN
Barahona, M
Item Type: Chapter
Abstract: With the rise of social media as an important channel for the debate and discussion of public affairs, online social networks such as Twitter have become important platforms for public information and engagement by policy makers. To communicate effectively through Twitter, policy makers need to understand how influence and interest propagate within its network of users. In this chapter we use graph-theoretic methods to analyse the Twitter debate surrounding NHS Englands controversial care.data scheme. Directionality is a crucial feature of the Twitter social graph - information flows from the followed to the followers - but is often ignored in social network analyses; our methods are based on the behaviour of dynamic processes on the network and can be applied naturally to directed networks. We uncover robust communities of users and show that these communities reflect how information flows through the Twitter network. We are also able to classify users by their differing roles in directing the flow of information through the network. Our methods and results will be useful to policy makers who would like to use Twitter effectively as a communication medium.
Editors: Adams, N
Heard, N
Issue Date: 22-Mar-2016
URI: http://hdl.handle.net/10044/1/32881
ISBN: 978-1-60558752-3
Publisher: World Scientific
Start Page: 111
End Page: 136
Journal / Book Title: Dynamic Networks and Cyber-Security
Copyright Statement: Electronic version of a chapter published in Dynamic Networks and Cyber-Security © 2016 World Scientific Publishing Company.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/I017267/1
Keywords: Physics and society
Social and information networks
Notes: 27 pages, 6 figures, to appear in 'Dynamic Networks and Cyber-Security'
Appears in Collections:Department of Surgery and Cancer
Biological and Biophysical Chemistry
Applied Mathematics and Mathematical Physics
Institute of Global Health Innovation
Faculty of Natural Sciences