120 credits including 20 credits in computer science and 25 credits in mathematics or statistics. A second course in computer programming. Introduction to Data Science, alternatively both Data Mining I and an introductory course in machine learning. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Sources, types, and features of social data. The social data mining process: role of computational methods and validity. Social network analysis: social structures and processes. Feature-rich social networks. Computational text analysis: text preprocessing, word frequencies, topic modelling (classic and deep learning-based). Analysis of social visual data (classic and deep learning-based).
