Utrecht Summer School
Applications of text mining are everywhere: social media, web search, advertising, emails, customer service, healthcare, marketing, etc. In this course, students will learn how to apply text mining methods on text data and analyse them in a pipeline with statistical learning algorithms. The course has a strongly practical hands-on focus, and students will gain experience in using and interpreting text mining on data examples from humanities, social sciences, and healthcare.
This course introduces the basic and advanced concepts and ideas in text mining and natural language processing. In this course, students will learn how to apply text mining methods on text data and analyse them in a pipeline with machine learning and deep learning algorithms. The course has a strongly practical hands-on focus, and students will gain experience in using text mining on real data from social sciences, humanities, and healthcare and interpreting the results.
The accelerating datafication of society constitutes challenges and opportunities for humanities research. This course will acquaint you with (methodological) fundamentals of data practices in the Digital humanities. These will include data collection, data preparation, data visualisation, critical data and algorithm studies, network analysis, and an introduction to programming in Python. Besides training these skills, you will work in small teams on a hands-on case. To top it off, guest speakers from several fields will share their experiences with data practices.