Computational text analysis reveals rising demand for data science and programming skills across media job postings, highlighting the technological reconfiguration of journalistic roles.
The rapid advancement of artificial intelligence and information communication technologies has profoundly disrupted traditional professional structures, transforming how journalistic work is organized and understood. This study examines how journalism has adapted to these technological shifts through the emergence of new job roles and skills. Drawing from a communicative perspective, the research frames job advertisements as organizational artifacts that signal adaptation and reconfiguration of professional boundaries. Using a longitudinal dataset from 2010 through 2020 encompassing more than 400,000 job postings across the U.S. media sector, this study employs computational text analysis and clustering to trace evolving patterns in job titles and skill requirements. Findings reveal a significant rise in computational and data-driven competencies including analytics, programming, and data science within journalism roles, suggesting the integration of technological expertise into the profession’s core identity. Results highlight how organizations discursively construct new professions and communicate adaptation in response to ongoing change. By analyzing job roles as sites of organizational meaning-making, this work contributes to understanding the adaptation of new skills into existing professions and offers insight into the broader dynamics of transformation in the digital age.
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Weber et al. (2026) studied this question.
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