Gillooly, L, Anagnostopoulos, C and Chadwick, S (2017) Social media-based sponsorship activation – a typology of content. Sport, Business and Management: An International Journal, 7 (3). pp. 293-314. ISSN 2042-678X
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Abstract
Purpose – The purpose of this paper is to thematically categorise sports sponsorship-linked Twitter content and, by drawing on uses & gratifications theory, to map the extent to which these categories cohere with known user motivations for consuming social media. Design/methodology/approach – Qualitative content analysis of a sample of 1,502 tweets by London 2012 Olympic and Paralympic Games sponsors posted between January 2011 and September 2012 was used to develop the typology of sponsorship-linked Twitter content. Findings – From the data, a typology is developed, comprising 17 categories grouped under four main types: informing, entertaining, rewarding and interacting. The majority of sponsor tweets (68 per cent) fell into the informing type, with 17 per cent categorised as interacting. While few (2 per cent) tweets were categorised as entertaining, the link to the sponsored event implies a degree of entertaining content even in ostensibly informative, rewarding or interactional sponsorship-linked tweets. Therefore, the typology categories highlight Twitter content produced by sponsors which engages customers, fostering dialogue alongside providing informative and entertaining content. Practical implications – The typology can inform practitioners’ future sports sponsorship activation planning decisions and can also aid rights holders in tailoring appropriate sponsorship opportunities to potential sponsors, based on an appreciation of the nature of content sought by brand followers. Originality/value – The typology extends existing understanding of the use of social media within sponsorship activation campaigns by thematically categorising content and mapping this against known user motivations for consuming brand-related social media content.
Impact and Reach
Statistics
Additional statistics for this dataset are available via IRStats2.