In the sports industry, artificial intelligence has become a powerful tool for sports managers interested in getting private sponsorships and for DMOs interested in branding a place. In this scenario, two main objectives guide this chapter (1) to generate a ranking of the leading Spanish marathons based on their presence on the four most important social networks in Spain (Facebook, Twitter, Instagram, and YouTube) and (2) to measure the engagement on social networks generated by the first of the marathons identified in the ranking. The official profiles of the accounts of the 10 marathons with the highest number of finishers in 2022 in Spain have been monitored on the social networks listed (Facebook, Twitter, Instagram, and YouTube). As the results show, a marathon can generate high network engagements. The destination's image can be highly favoured thanks to small local events (such as marathons) capable of generating a lot of movement on social networks. However, not all social networks work equally well in promoting sporting events capable of generating engagement.
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The sports industry is increasingly gaining momentum in many countries because of its exciting role in boosting tourism. Many tourist destinations increasingly rely on sporting events to help attract tourists. The analysis of social networks linked to sporting events with artificial intelligence allows public managers of tourist destinations and private companies that sponsor them to know the public's perceptions of the sporting services offered (sporting races in this case), understanding how often and in what context brands are mentioned (marathons in this case) and the engagement they can generate. In addition, AI can be used to identify which content on social networks is receiving the most attention, making it possible to predict the future popularity of certain types of sporting events over others. This information is helpful in boosting tourist destinations that host marathons and for private brands that sponsor them and want to achieve visibility. Moreover, and from an account manager's point of view, integrating AI and Social Blade can improve the capacity of accounts and their managers. Thus, this integration can be used for optimising the social media presence, helping to improve their benchmarking (adaptation and improvement of strategies according to the competitors’ strategies), and improving the method for making predictions. At the time of writing this chapter, predictions are based on a simple linear regression method. However, using supervised or self-supervised neural networks can greatly improve these predictions and, therefore, can provide useful information for the channels managers.
Within sporting events, this research will focus on one specific sporting activity: marathons. Their growing prominence over the last decades is unquestionable (Zouni, Markogiannaki, Georgaki, 2021), as they are local events that do not require the preparation and investment of other major global sporting mega-events, such as the Olympiads or the World Cup. Despite this, given that these are recurring events, hosting this type of sporting activity can be a source of competitive advantage for a territory. It is not for nothing that in Spain, the ten largest Spanish cities have a marathon in their sports calendar (Pérez and Serrano, 2020). The marathon is the premier event in long-distance athletics. It is a race format that is standardized in its distance at a global level, covering 42 km and 195 m, facilitating comparisons. It can indeed be run on different surfaces, e.g. on asphalt or in the mountains.
As Naraine and Wanless (2020) have remarked, at no point has there been the volume, variety, and, consequently, the value of data being produced with velocity by organizations, customers, and other stakeholders. As these authors explain, in the sports industry, artificial intelligence has become a powerful tool for sports managers who must make crucial decisions at the right time with the correct information. Henceforth, the importance of developing intelligent information collection, analysis and management mechanisms to enable successful responses. In this vein, Pérez and Serrano (2020) remark that social networks have gone from being a digital platform to generating wealth for countries and businesses. At this point, monitoring the social media activity using of events is necessary to maximize its benefits for diverse stakeholders. The AI-based computer systems in charge of monitoring social networks show the user what is happening on the different platforms, speed up reaction times and facilitate strategic decision-making.
In the described scenario, this work pursues, as a generic objective, to show the main results of the first Barometer of Social Networks and Marathons in Spain, created to establish a simple and limited but representative picture of the projection in social networks of the leading marathons in Spain. Knowing and managing this volume of information in time is relevant to infer the role that the social networks of sporting events can play in the economic development of a territory. On the one hand, their proper management favors, at a public level, the use of sporting events in creating a city brand. On the other hand, it allows, at a private level, to attract sponsoring brands interested in leading events with a high level of dissemination on social networks.