Data journalism in sports media and web visibility: evaluation using the SEOVisFrame framework

Abstract

Data visualizations, which have established themselves as tools with great narrative potential, face the challenge of being visible in the algorithmic environments of search engines. Scholarly literature has paid limited attention to their search engine optimisation (SEO), which restricts their reach and impact. This study examines the relationship between the narrative and technical features of data visualisations in sports journalism and their level of optimisation for search engines, using the SEOVisFrame methodological framework. The study aims to: a) validate the applicability of the framework; b) assess the compliance of an international sample of visualisations with SEO indicators; c) identify best and worst SEO practices; d) analyse differences according to media type or country of origin; and e) compare the findings with those of previously evaluated generalist journalistic products. An evaluation was conducted using the SEOVisFrame framework on 98 award-winning visualisations published between 2021 and 2023. The framework includes 33 indicators grouped into five dimensions: content SEO, technical SEO, SEO for graphic components, EEAT factors, and off-page SEO. Technical SEO showed the highest compliance rate (84.26 %), followed by content SEO (69.42 %). In contrast, EEAT factors (24.27 %) and off-page SEO (12.51 %) revealed significant shortcomings. Best practices focused on technical performance and basic semantic structure, while major weaknesses were identified in accessibility, transparency, and external authority.