Mapping the Digital Media Landscape in Bulgaria: Analysis of Web Publications

This study explores the thematic structure and editorial focus of the digital media land-scape in Bulgaria by analyzing one year of online news publications from eight major media outlets. The data were collected through a custom-built web scraping application developed in Java, which enabled the automated extraction and processing of full-text ar-ticles from publicly accessible news websites. The structured dataset, generated during the scraping process, records word-level occurrences in both article titles and bodies, along with publication dates and URLs. By applying lexical frequency analysis and temporal tracking, the study identifies the most frequently used words, their monthly distribution, and platform-specific usage patterns. The findings reveal clear distinctions in editorial focus between public broadcasters, private national media, and international outlets. Ad-ditionally, the analysis highlights how title construction and word prominence vary de-pending on platform type and media strategy. The study demonstrates the potential of web scraping and computational text analysis as scalable tools for investigating media systems in small and transitional democracies.