了解一家足球俱乐部的社交媒体网络:对曼联的探索性案例研究

IF 2.1 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE Information Discovery and Delivery Pub Date : 2021-01-21 DOI:10.1108/IDD-08-2020-0106
Erick Mendez Guzman, Ziqi Zhang, W. Ahmed
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引用次数: 3

摘要

目的这项工作的目的是研究足球俱乐部的不同利益相关者如何通过推特进行在线互动。它分析了足球俱乐部的推特网络,以发现有影响力的演员以及他们在线交流中感兴趣的话题。设计/方法/方法作者分析了来自曼联足球比赛期间收集的200多万条推文的社交网络。作者应用社交网络分析来发现影响者和子社区,并对知名影响者最受欢迎的推文进行内容分析。FindingsSub社区可以围绕与足球无关的时事形成,这可能是由于利用大型网络和足球比赛期间的大量关注来传播信息的机会主义尝试。此外,以不同主题为特色的推文的受欢迎程度取决于所涉及的影响者的类型。实际含义这些方法可以帮助足球俱乐部更深入地了解他们的在线社交社区。研究结果还可以为足球俱乐部提供如何通过使用各种影响者来优化沟通策略的信息。原创性/价值与之前的研究相比,作者发现了广泛的影响者和更密集的网络,其特征是数量较少的大型集群。有趣的是,这项研究还发现,机器人似乎在网络中变得有影响力。
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Towards understanding a football club’s social media network: an exploratory case study of Manchester United
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.
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来源期刊
Information Discovery and Delivery
Information Discovery and Delivery INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
5.40
自引率
4.80%
发文量
21
期刊介绍: Information Discovery and Delivery covers information discovery and access for digital information researchers. This includes educators, knowledge professionals in education and cultural organisations, knowledge managers in media, health care and government, as well as librarians. The journal publishes research and practice which explores the digital information supply chain ie transport, flows, tracking, exchange and sharing, including within and between libraries. It is also interested in digital information capture, packaging and storage by ‘collectors’ of all kinds. Information is widely defined, including but not limited to: Records, Documents, Learning objects, Visual and sound files, Data and metadata and , User-generated content.
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