BWL XI: New Master's Course: Text Mining
Course: Text Mining (M. Sc.)
- Module codes: TBA
- Lecturer: Prof. Dr. Nicolas Pröllochs (BWL XI)
- Course format: Lecture (6 CP)
- Term: Winter semester 19 / 20
- Language: English
- Grading: Presentation & Term Paper
The digital age has ignited a burst in the volume of textual materials available to businesses and the public. Common examples include blog entries, posts on social media platforms, user-generated reviews, descriptions in recommender systems and product advertisements in electronic commerce. Text mining provides computational techniques to derive actionable (managerial) insights from such unstructured data sources.
The course “Text Mining” provides students with an overview of a wide range of text mining methods: from regular expressions, to lexicon-based sentiment analysis, to more complex machine learning approaches and supervised text classification. At the end of the course, participants will be familiar with the most important concepts, principles, and algorithms in text mining. The course includes practical sessions focusing on text mining in R. Basic experience in R programming is desirable but not mandatory.
The main objectives of this course are:
1) Understand the basic concepts of text mining and its relevance for business applications
2) Gain an overview of different methods, algorithms and software tools for extracting knowledge from unstructured text data
3) Practice the implementation of text mining applications in R