Design of an Infometric Model for Algorithmic Distribution of Science, Innovation, and Economic Information in Small Language Communities

Digital platforms play a key role in the distribution of information, with algorithms filtering, ranking, and amplifying news before it becomes visible to users. This study contributes to the discussion on the role of media in linking science, technology, and economic development by offering an empirical model for the quantitative measurement of algorithmic influence on media pluralism in small language communities. This paper develops and applies info-metric methods to measure concentration and diversity in the algorithmic distribution of news and enables a comparison of two different algorithmic logics in the context of media mediation between science, technological innovation, and the economy. The aim of the study is to determine whether there is a concentration of visibility of content related to science, technological innovation, and the economy, and whether the level of digital pluralism differs between the aggregative logic of Google News and the social platform Facebook. The research examines the distribution of algorithmic visibility of media sources and quantitatively assesses the balance of their representation in the domains of science, technological innovation, and the economy, while comparing patterns of concentration and pluralism between hierarchical ranking and network amplification. Info-metric methods are applied to measure concentration and pluralism in the algorithmic distribution of news. The analysis includes a stratified sample of relevant Croatian mainstream and alternative media outlets. Over a period of 30 days, the rank positions of the first ten results in the categories of (1) science, (2) technological innovation, and (3) the economy on Google News were systematically recorded, along with the engagement levels of the same content on Facebook. Visibility was measured using a rank-position index and engagement share per media outlet. Source concentration and diversity were measured using the Herfindahl–Hirschman Index (HHI) and Shannon entropy. The results show statistically significant concentration of visibility in the topics of the economy and technological innovation, while science demonstrates a higher level of pluralism. The design of the info-metric model of information distribution indicates that the algorithmic distribution of news has a significant impact on the media mediation of the relationship between science, technology, and economic development, particularly in small language communities.