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    Social Media Conversations About High Engagement Sports Team Brands

    Chadwick, Simon, Fenton, Alex, Dron, Richard ORCID logoORCID: https://orcid.org/0000-0002-1464-4232 and Ahmed, Wasim (2021) Social Media Conversations About High Engagement Sports Team Brands. IIM Kozhikode Society and Management Review, 10 (2). pp. 178-191. ISSN 2277-9752

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    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.

    Impact and Reach


    Activity Overview
    6 month trend
    6 month trend

    Additional statistics for this dataset are available via IRStats2.


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