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Abstract
The purpose of this study was to identify segments within the social media networks of major professional sport organizations. Relational data were collected from the Twitter accounts of four major professional sport organizations based in Toronto, Canada. Users within these networks were subsequently parsed based upon their Twitter behavior (e.g., likes, retweets, and follows) and their demographic information using an automated cluster analysis. After revealing characteristics of each segment, the findings highlight both sport focused (e.g., hockey, basketball) and non-sport focused (e.g., mothers, music lovers) subgroups which, in some cases, appear in multiple professional sport team networks. The findings provide the antecedents to social media interaction and suggest managers within professional sport organizations consider this information before forging new or enhanced relationship marketing activities as well as cross-promotional campaigns with additional brands.
Keywords: Twitter, relationship marketing, social networking, big data, Canadian sport
http://doi.org/10.32731/SMQ.284.122019.04
In the social media space, engaging with fans and other stakeholders (e.g., facilities, governments) can be challenging for a sport organization. Multiple conversations on several social platforms occur simultaneously, which yields significant "noise" (Stavros, Meng, Westberg, & Farrelly, 2014), with some discussions (such as those in a sport context) even yielding hundreds of thousands of messages over a span of a few hours (cf., Naraine, Pegoraro, François, & Parent, 2016). Engaging in such a noisy space can also prove difficult given the network of users in a sport-based conversation fluctuates considerably (Hambrick & Pegoraro, 2014). To mitigate these fluctuations, an alternative engagement strategy is to focus on users who seek organizationally driven or focused content, such as those actively following the sport organization. While this strategy may be utilized to enhance the association stakeholders have for an organization (Heere & James, 2007), its application in the social media space poses a challenge.
For professional sport organizations particularly, engaging with fans in their own network can be problematic due to its large size (i.e., millions of followers) and the potential for a limited understanding of these users' social media traits and associations. Certainly, these organizations would recognize some of the higher profile users within their network; it has been well-documented that salient sport stakeholders, including elite athletes (Geurin-Eagleman & Burch, 2016), sponsors (Abeza, Pegoraro, Naraine, Séguin, & O'Reilly, 2014), and governing...