230017 Hate Speech Detection (S) (WiSe 2022/2023)
Contents, comment
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As the number of social media platforms grows, the spread of hate speech among online communities (such as Twitter, Facebook, Reddit, Youtube, and so on) becomes widespread. We broadly define hate speech as “inappropriate language” expressed via text, image, or video. This seminar will focus on the automatic detection of hate/offensive/toxic speech by using various NLP methods, such as dictionary-based or classification-based methods. The basics of these methods have been taught in the class "Maschinelle Sprachverarbeitung (SS 2021)".
The course will be taught in English. General knowledge of Python programming language would be nice, but it is not obligatory.
In this seminar, students learn to
• break down a research question/problem into manageable components
• develop an analytical approach to address a research problem in computational sociolinguistics.
• process raw text for Hate Speech Detection
• apply different classical machine learning or deep learning algorithms in Python Environment to get insights for specific research questions,
• interpret the result of data analysis,To successfully pass, we ask participants
• to hand in 2-3 small homework assignments
• to make 15-min presentation on a relevant research paper or relevant Python library/package
• to submit a 1-2 page research proposal based on the course content
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period |
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Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 23-CL-BaCL5 Vertiefungsmodul | Lehrveranstaltung 1 | Study requirement
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Student information |
| Lehrveranstaltung 2 | Study requirement
|
Student information | |
| - | Graded examination | Student information | |
| 23-TXT-BaCL5 Vertiefungsmodul | Veranstaltung aus dem Vertiefungsbereich | Study requirement
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Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
- Registered number: 14
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- Address:
- WS2022_230017@ekvv.uni-bielefeld.de
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- Coverage:
- 10 Students to be reached directly via email
- Notes:
- Additional notes on the electronic mailing lists
- Last update basic details/teaching staff:
- Thursday, May 5, 2022
- Last update times:
- Thursday, May 5, 2022
- Last update rooms:
- Thursday, May 5, 2022
- Type(s) / SWS (hours per week per semester)
- S / 2
- Language
- This lecture is taught in english
- Department
- Faculty of Linguistics and Literary Studies
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