Economic Analysis of Text and other Non-Standard Data

About

Much of human knowledge is stored in unstructured formats, in particular in written text. This course teaches methods to process and analyze text data. The learning goals are to understand the structure and concept text-as-data methods, and to evaluate the use of text-analysis tools in economics research. The course will conclude with an overview of non-standard data beyond text, in particular audio data and image data. The course covers 10 topics, see below. For most topics, a theoretical lecture will be provided first, followed by a discussion of a recent research paper in economics/NLP

Course leader

Prof. M. Benjamin Arold, University of Cambridge, England

Target group

Master's students, doctoral candidates, researchers, and university professors, as well as other executives in the public and private sectors

Course aim

The 10 topics are ordered as follows:
Overview
Dictionaries
Tokenization & Distance
Unsupervised and Supervised ML with Text
Word Embeddings and Linguistic Parsing
Embedding Sequences with Attention
Generative AI; and Using Transformers for YOUR Research
Image Data in Business & Economics
Audio Data in Business & Economics
Ethical Considerations

Fee info

Tuition fees include all materials needed for the course and the provision of information about accommodation and restaurants near ISEG