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Pro-Environmental Campaigns via Social Media: Analysing Awareness and Behaviour Patterns

Fernandez, Miriam; Piccolo, Lara S.G.; Maynard, Diana; Wippoo, Meia; Meili, Christoph and Alani, Harith (2017). Pro-Environmental Campaigns via Social Media: Analysing Awareness and Behaviour Patterns. Journal of Web Science (In Press).

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Abstract

Changing people’s behaviour with regards to energy consumption is often regarded as key to mitigating climate change. To this end, endless campaigns have been run by governments and environmental organisations to engage and raise awareness of the public, and to promote behaviour change. Nowadays, many such campaigns expand to social media, in the hope of increasing their reach and impact. However, in spite of persistent e↵orts, public engagement with these campaigns tends to be rather underwhelming. This demonstrates the need for adopting new strategies in designing and executing these campaigns. To the best of our knowledge, these campaigns often overlook existing theories and studies on user engagement and behaviour change. To close this gap, this paper uses Robinson’s Five Doors Theory of behaviour change [26] to analyse online user behaviour towards climate change. With this approach, users’ behavioural stages can be automatically identified from their contributions on social media. We apply this approach to analyse the behaviour of participants in three global campaigns on Twitter; United Nations COP21, Earth Hour 2015, and Earth Hour 2016. Our results provide guidelines on how to improve communication during these online campaigns to increase public engagement and participation.

Item Type: Journal Item
ISSN: 2332-4031
Project Funding Details:
Funded Project NameProject IDFunding Body
A Decarbonisation Platform for Citizen Empowerment and Translating Collective Awareness into Behavioural ChangeNot SetNot Set
Keywords: behaviour analysis; social media; climate change
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 51172
Depositing User: Miriam Fernandez
Date Deposited: 03 Oct 2017 13:28
Last Modified: 20 Dec 2017 16:53
URI: http://oro.open.ac.uk/id/eprint/51172
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