Mapping and measuring neighbourhood social media groups. The case of facebook
Social media is a pervasive part of everyday life. Neighbourhood social media are important community orientated structures that serve as digital platforms where local residents can connect with neighbours, exchange information, and share resources. The current study details an analytic framework to systematically capture, measure and map neighbourhood social media (Facebook groups) presence for a large metropolitan region, Brisbane, Australia. Further through modelling we reveal how socially organised communities acquire a higher number of neighbourhood-based social media groups while socially disorganised communities tend to have social media groups associated with crime or crime watch. We also unveil important spatial patterns with more neighbourhood-based social media groups located in coastal areas that are associated with tourism, leisure activities and recreational pursuits. Our findings demonstrate that neighbourhood-based social media is an important component of community social infrastructure and can support collective capacity to respond to problems. Our hope is that our approach can be replicated in other situational and cultural contexts to assemble a growing set of comparative studies through which the spatial distribution of locality-based social media can be assessed. • Locality-based social media groups are common communication platforms. • Affluent neighbourhoods have more locality-based community social media groups. • Coastal and tourist localities have more numerous and larger groups. • Disadvantaged localities more likely to have crime watch groups.
Authors
- Jonathan Corcoran (ORCID: https://orcid.org/0000-0003-3565-6061)
- Sam Hames
- Renee Zahnow (ORCID: https://orcid.org/0000-0001-5796-9443)
- Jeremy Verrier
Institutions
- The University of Queensland (AU)
Publication Details
- Journal
- Applied Geography
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1016/j.apgeog.2024.103415
- Citations
- 6
- Primary Topic
- Social Media and Politics
- Type
- article
- Field-Weighted Citation Impact
- 5.74