Abstract
Action to tackle the complex and divisive issue of climate change will be strongly influenced by public perception. Online social media and associated social networks are an increasingly important forum for public debate and are known to influence individual attitudes and behaviours - yet online discussions and social networks related to climate change are not well understood. Here we construct several forms of social network for users communicating about climate change on the popular microblogging platform Twitter. We classify user attitudes to climate change based on message content and find that social networks are characterised by strong attitude-based homophily and segregation into polarised "sceptic" and "activist" groups. Most users interact only with like-minded others, in communities dominated by a single view. However, we also find mixed-attitude communities in which sceptics and activists frequently interact. Messages between like-minded users typically carry positive sentiment, while messages between sceptics and activists carry negative sentiment. We identify a number of general patterns in user behaviours relating to engagement with alternative views. Users who express negative sentiment are themselves the target of negativity. Users in mixed-attitude communities are less likely to hold a strongly polarised view, but more likely to express negative sentiment towards other users with differing views. Overall, social media discussions of climate change often occur within polarising "echo chambers", but also within "open forums", mixed-attitude communities that reduce polarisation and stimulate debate. Our results have implications for public engagement with this important global challenge.
Original language | English |
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Pages (from-to) | 126-138 |
Number of pages | 13 |
Journal | Global Environmental Change |
Volume | 32 |
Early online date | 11 Apr 2015 |
DOIs | |
Publication status | Published - 1 May 2015 |
Keywords
- Climate change
- Echo chamber
- Opinion leader
- Polarisation
- Social network analysis