Uncovering hidden patterns of meanings: the case of the most successful Spanish radio sports programs on Twitter

IAMCR Madrid

Nowadays, sports programs have become spaces of great influence due to the status acquired by sports and everything that surrounds it. These types of journalistic programmes use the microblogging network to get closer to their fans and increase their visibility.
Spanish radio discovered social networks in the 2009-10 season (Peña and Pascual, 2013: 124) and soon became a new tool “to strengthen and build a renewed relationship with its audience providing it with a virtual meeting and socializing space” (Ramos del Cano, 2014: 1). Thus, “the community of a particular radio network is no longer only composed of its listeners, but this it is enriched with the addition of the ‘social audience’” (Videla and Piñeiro, 2013: 86).

In recent years, the microblogging network has become a tool that is generally used in sports journalism and affects the collection, publication and coverage of sports news (Butler et al., 2013; English, 2014). Twitter has grown into a meeting space where journalists can promote stories (Schultz and Sheffer, 2010), monitor news and discuss topics with the users interested in the latest sports news (Sherwood and Nicholson, 2013).

This paper analyses the profiles of the 5 most listened to radio sports programs on the Twitter platform. NodeXL software, one of the main open source analysis programs for networks (Hansen et al., 2010), is used to discover hidden patterns of meanings creating a semantic and a hashtag network. This software is also used to study the flow of information within the network and to identify which are the most important profiles. To do this, in this research we analyze the 3,200 most recent messages posted in the profiles of each of the most listened-to radio sports programmes (N=16.000).

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