Guzmán, E.M., Zhang, Z. orcid.org/0000-0002-8587-8618 and Ahmed, W. (2021) Towards understanding a football club’s social media network: an exploratory case study of Manchester United. Information Discovery and Delivery, 49 (1). pp. 71-83. ISSN 2398-6247
Abstract
Purpose
The purpose of this work is to study how different stakeholders of a football club engage with interactions online through Twitter. It analyses the football club’s Twitter network to discover influential actors and the topic of interest in their online communication.
Design/methodology/approach
The authors analysed the social networks derived from over two million tweets collected during football matches played by Manchester United. The authors applied social network analysis to discover influencers and sub-communities and performed content analysis on the most popular tweets of the prominent influencers.
Findings
Sub-communities can be formed around current affairs that are irrelevant to football, perhaps due to opportunistic attempts of using the large networks and massive attention during football matches to disseminate information. Furthermore, the popularity of tweets featuring different topics depends on the types of influencers involved.
Practical implications
The methods can help football clubs develop a deeper understanding of their online social communities. The findings can also inform football clubs on how to optimise their communication strategies by using various influencers.
Originality/value
Compared to previous research, the authors discovered a wide range of influencers and denser networks characterised by a smaller number of large clusters. Interestingly, this study also found that bots appeared to become influential within the network.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Year Emerald Group Publishing. This is an author-produced version of a paper subsequently published in Information Discovery and Delivery. This version is distributed under the terms of the Creative Commons Attribution-NonCommercial Licence (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You may not use the material for commercial purposes. |
Keywords: | Information retrieval; World Wide Web; Social media; Network analysis; Information networks; Online computing; Manchester United; Football; Content analysis |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Mar 2021 16:47 |
Last Modified: | 22 Mar 2021 17:13 |
Status: | Published |
Publisher: | Emerald |
Refereed: | Yes |
Identification Number: | 10.1108/idd-08-2020-0106 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:172453 |