Social Media Conversations About High Engagement Sports Team Brands

S. Chadwick, A. Fenton, Richard Dron, W. Ahmed
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引用次数: 3

Abstract

This study conducts an analysis of social media discussions related to high engagement sports brands. More specifically, our study examined the English Premier League (EPL); it sought to retrieve data systematically over the same day, weekly, for a period of five months. After this process, we had built 20 datasets and NodeXL was utilized to analyse the data. After we had this data, we were able to use qualitative observations to identify key users and conversations that formed around the EPL as well as the connections between the conversations that arose from the brand’s posts and the people involved in them. We also analyzed the quantitative data underpinning our network visualisations to provide further insights. The most obvious initial finding was that when the EPL tweets, it prompts a large volume of conversations directly related to these tweets. However, we also noted that EPL tweets also help instigate further, sometimes unrelated, tweets and conversations. More specifically, we identified that the visualized network of conversations was of a broadcast form, which is characterized by messages being generated by a central account (the EPL) and shared by a number of decentralized users. Based on our analysis, we propose guidance around (S)ocial media presence, (C)rafting the message, Planned (i)ntervention, (S)pontaneous follow-up, and (M)essage mortality to form the SCISM framework. This framework is likely to be of interest to brands that wish to promote, sustain and benefit from their instigation of social media.
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关于高参与度运动队品牌的社交媒体对话
本研究分析了与高参与度体育品牌相关的社交媒体讨论。更具体地说,我们的研究考察了英超联赛(EPL);它试图在五个月的时间里,每周在同一天系统地检索数据。在此过程之后,我们构建了20个数据集,并使用NodeXL对数据进行分析。在我们获得这些数据后,我们能够使用定性观察来识别关键用户和围绕EPL形成的对话,以及品牌帖子引发的对话与参与其中的人之间的联系。我们还分析了支撑我们网络可视化的定量数据,以提供进一步的见解。最明显的初步发现是,当EPL发推文时,它会引发大量与这些推文直接相关的对话。然而,我们也注意到,EPL推文也有助于煽动进一步的、有时是不相关的推文和对话。更具体地说,我们发现可视化的对话网络是一种广播形式,其特征是消息由中央账户(EPL)生成,并由许多分散的用户共享。基于我们的分析,我们提出了关于(S)社交媒体存在、(C)信息传递、计划的(i)干预、(S)即时随访和(M)信息死亡率的指导意见,以形成SCISM框架。这个框架可能会引起那些希望推广、维持社交媒体并从中受益的品牌的兴趣。
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来源期刊
CiteScore
3.90
自引率
31.20%
发文量
25
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