Bingham-Hall, John and Law, Stephen (2015) Connected or informed?: local Twitter networking in a London neighbourhood. Big Data and Society, 2 (2). ISSN 2053-9517
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Abstract
This paper asks whether geographically localised, or ‘hyperlocal’, uses of Twitter succeed in creating peer-to-peer neighbourhood networks or simply act as broadcast media at a reduced scale. Literature drawn from the smart cities discourse and from a UK research project into hyperlocal media, respectively, take on these two opposing interpretations. Evidence gathered in the case study presented here is consistent with the latter, and on this basis we criticise the notion that hyperlocal social media can be seen as a community in itself. We demonstrate this by creating a network map of Twitter followers of a popular hyperlocal blog in Brockley, southeast London. We describe various attributes of this network including its average degree and clustering coefficient to suggest that a small and highly connected cluster of visible local entities such as businesses form a clique at the centre of this network, with individual residents following these but not one another. We then plot the locations of these entities and demonstrate that sub-communities in the network are formed due to close geographical proximity between smaller sets of businesses. These observations are illustrated with qualitative evidence from interviews with users who suggest instead that rather than being connected to one another they benefit from what has been described as ‘neighbourhood storytelling’. Despite the limitations of working with Twitter data, we propose that this multi-modal approach offers a valuable way to investigate the experience of using social media as a communication tool in urban neighbourhoods.
Item Type: | Article |
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Official URL: | http://journals.sagepub.com/home/bds |
Additional Information: | © 2015 The Authors © CC BY 3.0 |
Divisions: | LSE Cities |
Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HT Communities. Classes. Races |
Date Deposited: | 15 Mar 2017 09:28 |
Last Modified: | 30 Oct 2024 21:12 |
URI: | http://eprints.lse.ac.uk/id/eprint/69816 |
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