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| Semester | fall semester 2021 |
| Course frequency | Irregular |
| Lecturers | Helge Liebert (helge.liebert@unibas.ch, Assessor) |
| Content | Much of human knowledge is stored in unstructured formats. This course teaches methods to process and analyze unstructured data, focusing on text data. In the first part, we review tools required for processing text data. One lecture will be dedicated to web scraping fundamentals. We then focus on the concepts underlying the transformation of unstructured data into structured formats. Finally, we study supervised models suited for the analysis of text data, as well as unsupervised models which make it possible to discover structure in unlabeled text data. Throughout the course, I will emphasize real-world applications of the techniques in research and industry. Course outline 1. PC fundamentals 2. Regular expressions and pattern recognition. 3. Web scraping 4. Representing text as data 5. Analysis of text data: Supervised models 6. Analysis of text data: Unsupervised models |
| Learning objectives | The course aims to provide a thorough understanding of the workflow, tools and models related to the analysis of text data, and their implementation in R. |
| Bibliography | The course does not adhere strictly to a single reference. References are pointed out in the course material. The two books below serve as a general reference. Jurafsky, D. and Martin, J. H. (2019). Speech and Language Processing (3rd ed. draft). https://web.stanford.edu/~jurafsky/slp3/. Hastie, T., Tibshirani, R. and Friedman, J. (2001). The elements of statistical learning: Data mining, inference, and prediction (2nd ed.). Springer, New York. https://web.stanford.edu/~hastie/ElemStatLearn/. |
| Weblink | Course website |
| Course application | Please enrol by email to Graduate School of Business and Economics <gsbe-wwz@unibas.ch> until September 15, 2021. |
| Language of instruction | English |
| Use of digital media | No specific media used |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| unregelmässig | See individual dates | ||
| Comments | The course is planned as an in-class course, if necessary it will be offered in hybrid form, i.e. with a simultaneous livestream or as an online presence course. |
| Date | Time | Room |
|---|---|---|
| Monday 20.09.2021 | 09.15-12.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Wednesday 22.09.2021 | 14.15-18.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Thursday 23.09.2021 | 14.15-18.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Monday 27.09.2021 | 09.15-12.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Wednesday 29.09.2021 | 14.15-18.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Thursday 30.09.2021 | 14.15-18.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Monday 04.10.2021 | 09.15-12.00 | Wirtschaftswissenschaftliche Fakultät, Grosses PC-Labor S18 HG.37 |
| Modules |
Modul: Fachlich-methodische Weiterbildung (Doctoral Studies - Faculty of Business and Economics) |
| Assessment format | record of achievement |
| Assessment details | Take-home assignment. |
| Assessment registration/deregistration | Registration/deregistration: teaching staff |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,1 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Business and Economics , studiendekanat-wwz@unibas.ch |
| Offered by | Faculty of Business and Economics |