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Predicting adolescent social networks to stop smoking in secondary schools

Fetta, Angelico, Harper, Paul ORCID:, Knight, Vincent ORCID: and Williams, Janet 2018. Predicting adolescent social networks to stop smoking in secondary schools. European Journal of Operational Research 265 (1) , pp. 263-276. 10.1016/j.ejor.2017.07.039

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Social networks are increasingly being investigated in the context of individual behaviours. Research suggests that friendship connections have the ability to influence individual actions, change personal opinions and subsequently impact upon personal wellbeing. This paper explores the effect of individual friendship selection decisions, and the impact they may have on the overall evolution of a social network. Using data from a large smoking cessation programme in secondary schools, an agent based simulation aiming to predict the evolution of the adolescent social networks is created. The simulation uses existing friendship selection algorithms from link prediction literature, along with a new approach to link prediction, termed PageRank-Max. This new algorithm is based upon the optimisation of an individuals eigen-centrality, and is found to be more successful than existing methods at predicting the future state of an adolescent social network. This research highlights the importance of eigen-centrality in adolescent friendship decisions, and the use of agent-based simulation to conduct behavioural investigations. Furthermore, it provides a proof-of-concept for targeted interventions driven by social network analysis, demonstrating the utility of using emerging sources of social network data for public heath interventions such as with tobacco use which is a major global health challenge.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: Q Science > QA Mathematics
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Additional Information: This is an open access article under the CC BY license. ( )
Publisher: Elsevier
ISSN: 0377-2217
Funders: Engineering and Physical Sciences Research Council (EPSRC)
Date of First Compliant Deposit: 7 August 2017
Date of Acceptance: 11 July 2017
Last Modified: 06 May 2023 02:39

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