The course focuses on content analysis as a method to gain knowledge about current and historical social issues by analyzing observations of communication and media messages. Some of the computational content analysis techniques most commonly used within the social sciences, such as natural language processing and computer vision, are presented and practiced, and their connection to the field of artificial intelligence and machine learning is discussed. The focus lies on applying these methods and techniques and presenting the results through data visualizations.

Teaching includes lectures and teacher assisted exercises in practical computational content analysis and data visualization (computer lab work). 

Assessment is based on content analysis techniques for texts and images that are examined separately in two “data visualization reports” presented at seminars. The research reports should also include some contextual information, e.g. reflections on ethical aspects of the analysis techniques employed. Each report is examined individually and is worth 50% of the course grade.

For more information please contact: master [at] sam [dot] lu [dot] se