This document discusses Danish approaches to sentiment analysis, which is the computational study of opinions, sentiments and emotions expressed in text. It covers machine learning methods like bag-of-words modeling and algorithms like naive Bayes, maximum entropy, and support vector machines. It also discusses deep learning approaches using the Stanford Sentiment Treebank to model semantic compositionality. The document is a presentation by Daniel Hardt from Copenhagen Business School on sentiment analysis research.