Special Topic: Computational Methods in Psychological Science

With the advent of big data and advances in computing technologies, there has been an emerging trend of data-driven, exploratory research within the psychological sciences. This methods-focused course will provide a foundational overview of computational techniques in analysing big data. By referencing recent psychological research, students will be equipped with practical skills for working with large datasets. This includes applied skills for simple data mining, social network analysis, machine learning, and natural language processing. This course will also cover the risks of working with large datasets (e.g., bias and marginalisation), and ethical issues concerning the transparency, ownership, and openness of data. Note that coursework relies heavily on the R programming environment, but prior experience is not required. Some examples of research questions that we can examine in the course: 1. What can the r/socialanxiety subreddit tell us about the experiences of individuals with social anxiety? 2. Are Kiwis more similar to Aussies or Americans? 3. What features of music are associated with popular songs on Spotify?