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
Rhythmus | Tag | Uhrzeit | Format / Ort | Zeitraum |
---|
Modul | Veranstaltung | Leistungen | |
---|---|---|---|
23-CL-BaCL5 Vertiefungsmodul | Lehrveranstaltung 1 | Studienleistung
|
Studieninformation |
Lehrveranstaltung 2 | Studienleistung
|
Studieninformation | |
- | benotete Prüfungsleistung | Studieninformation | |
23-TXT-BaCL5 Vertiefungsmodul | Veranstaltung aus dem Vertiefungsbereich | Studienleistung
|
Studieninformation |
Die verbindlichen Modulbeschreibungen enthalten weitere Informationen, auch zu den "Leistungen" und ihren Anforderungen. Sind mehrere "Leistungsformen" möglich, entscheiden die jeweiligen Lehrenden darüber.