Analysing the water cooler: Conversation analysis of the University of Canberra Brumbies’
social media users
Olan Scott, Ann Pegoraro, Jerry Watkins
This paper describes a conversation analysis of social media activity by fans of the University of Canberra Brumbies, a professional rugby union team based in the capital of Australia. Although sport only makes up a small percentage of overall television programming, around half of all content posted to Twitter in 2013 was related to sport (Neilsen, 2014). Facebook, Instagram, blogs and other social media are also extensively used by sport organizations, athletes and consumers. Therefore it is increasingly important for sport organizations and athletes to prioritise these platforms in their marketing, communications, public relations, and management strategies (Hambrick, Simmons, Greenhalgh, & Greenwell, 2010); as social media give these actors an unfiltered voice in an increasingly cluttered marketplace (Wallace, Wilson, & Miloch, 2011; Scott, Bruffy, & Naylor, in press).
Historically, communication between (sport) organizations and consumers was one-way through the mass media. With the advent and proliferation of social media, the media landscape has been changed like never before (Pegoraro, 2013). Social network sites (SNSs) allow individuals and organizations to “(a) construct a public or semi-public profile within a bounded system, (b) articulate a list of other users with whom they share a connection, and (c) view and traverse their list of connections and those made by others within the system” (Boyd and Ellison, 2007, p. 211). Through the creation of SNSs, the gate-keeping role of the media has diminished as organization and consumers have a vehicle they can use to disseminate an unfiltered message to their key publics (Arsenault and Castells, 2008; Scott, Bradshaw, & Larkin, 2012).
Sport fans are avid users of technology (Kelly, 2013) and express themselves and access information online using multiple devices at the same time. For example, fans may follow their team on television while using their computer, tablet, or smartphone to view real-time statistics of the game or communicate with other fans watching the same contest. This is termed second-screen consumption and can often also include the use of SNSs such as Twitter, Facebook, and Instagram. The popularity of second-screen viewing and simultaneous engagement through social media, justifies the incorporation of SNSs into broader marketing strategy. Many sport fans no longer wait for the media’s post-match analysis; instead social media allows sports fans to create and share their own narrative during the game.
Social media can enhance the communication strategy of sport organizations by creating additional opportunities to connect with the sport consumer. But the substantial time and expertise required to manage successful social media activity – including rapid response to fan posting and multiplatform content moderation – can present a significant barrier for smaller sport organizations. This exploratory study will create a conceptual model for planning the desired performance of social media within the overall communication strategy of a small- to medium-scale sports organization. This model will allow identification of the ‘who’, ‘what’ and ‘how’ of social media activity within the organization’s communicative ecology (Hearn & Foth, 2007). A communicative ecology can be composed of three conceptual layers:
- Who: the social layer of users or people, and the social modes which organise those people e.g. athletes, fans and coaches.
- What: the discursive layer of content of communication e.g. the ideas or themes that distinguish the social interactions within the ecology.
- How: the technological layer of enabling devices and connecting media.
Focusing on the social and discursive layers, this project will test conversation analysis (CA) software as a means to capture and analyse the structure, information content, and inter-mode relationships of sport fan communication in order to inform effective social media strategy. To date, much of the research in social media has had its focus on content analysis of social media consumer posts through content analytic methodologies on Facebook (Evans, 2010; Scott et al., 2012), Twitter (Blaszka, Burch, Frederick, Clavio, & Walsh, 2012; Frederick, Lim, Lim, Clavio, Pedersen, & Burch, 2014; Pegoraro, 2010), and blogs (Clavio & Eagleman, 2011; Kwak, Kim, & Zimmerman, 2010). The proposed study will build upon this line of research by analysing the conversations of publically available Twitter content. The MUSTT (Multiple User-defined Search Terms on Twitter) process refers to the collection of data from Twitter based upon a delineated set of key words for the purposes of academic research. This process enables researchers to extract tweets using search terms similar to the process of seeking newspaper articles from an online database (e.g., Naraine & Dixon, 2014). The MUSTT process of tweet extraction is able to provide useful information that researchers could utilize in addition to the user-generated content itself. This data will only be collected from open, public pages, constituting freely available public data.
Once data are collected using the aforementioned processes, they will be analyzed separately using manual techniques and the thematic analysis software tool, Leximancer. This is a qualitative automated tool which extracts textual data and detects key concepts that are clustered and displayed in a visual concept map (Sotiriadou, Brouwers, & Le, 2014). Given that Leximancer has been reported to be reliable in its reproducibility of results (e.g., Smith & Humphreys, 2006), as well as capable of analyzing large amounts of data (e.g., Penn-Edwards, 2010), it has gradually become more utilized in sport management research in recent years (e.g., Shilbury, 2012). Thus – with scholars indicating that social media research requires methodological enhancements (cf. Hutchins, 2014; Pedersen, 2014; Sanderson, 2014) – Leximancer was chosen to present meaningful analysis in a timely manner while also negating issues pertaining to (intercoder) reliability that a manual parsing of the data would bear.
The main outcome from this study will be a strategic communication model which forms the basis of applied research collaboration with the University of Canberra Brumbies rugby union team. Social media data collection and analysis via MUSTT and Leximancer will be supported by in-depth interviews with University of Canberra Brumbies staff marketing and social media staff, which will provide insight into the team’s existing communication strategy and the intended contribution of social media to this strategy. It is intended that the strategic communication model produced by this study will be useful to other small- to medium-scale sport organizations which seek to understand and track the social media conversations of fans.
This paper will be presented at the 2015 NASSM conference held in Ottawa, Canada