analysis of digital maturity components in rail transportation industry: a text mining approach

The assessment of digital maturity in rail transportation, a crucial infrastructure for sustainable development, has gained increasing importance. this research employs text mining to systematically analyze scientific literature exploring digital maturity components in the rail industry. 87 scientific articles published between 2016 and 2025 from reputable international databases were analyzed using advanced text mining techniques, including sentiment analysis, k-means clustering, lda topic modeling, and n-gram algorithm in python. results identify five key areas: emerging technologies, digitalization challenges, cybersecurity, practical applications, and environmental sustainability as main transformation axes. sentiment analysis reveals predominantly positive attitudes (65%) towards this transformation, with 15% negative and 20% neutral responses. the findings recommend rail industry leaders adopt an integrated approach to digital transformation management, emphasizing cybersecurity infrastructure, environmental sustainability, and digital skills development.