The skills and qualifications of IT professionals are constantly changing and under discussion. In particular, we see the impact of emerging technologies and tools, such as AI, on the labor market and their reflection in the broader scientific community, media and everyday life [2, 4]. Several approaches have discussed how to assess the impact of computer science education from the perspective of education and labor market research [5, 7]. However, in order to uncover the complex dynamics surrounding computer science education, we need to take a closer look at the labor demand as well as the public perception and valuation of IT professionals. Therefore, the poster presents a new method that combines the analysis of online job advertisements (OJA) for computer science occupations at different qualification levels with social media data (Twitter/X and YouTube). As OJA and social media are usually described in unstructured natural language, text mining methods are key to extract information about skills and competencies. We used the Computer Science Ontology (CSO) for annotation [1] and outline further research questions in the wider context of political economy.