Fake news, disinformation, and propaganda influence elections and increase political polarisation. Parliamentary debates, party manifestos, and public engagement provide for informed politics, robust democracy, and improved public policy. Increasingly large volumes of textual data underpin both of these trends. This course covers theoretical concepts of treating text as data in the context of social science research. The course also provides a hands-on introduction to statistical methods to generate insights from text data using open source libraries in R.
At the end of this course students will have a sound understanding of the key concepts of statistical analysis of textual data, the ability to analyse such data using some of its main methods, and a solid foundation for more advanced or more specialised study in natural language processing.