Social Media (such as Twitter, Facebook, Reddit, YouTube, and so on) is a big part of our daily lives. It provides big unstructured data for researchers to understand individual and societal tendencies. The field of computational linguistics can provide many tools to use this unstructured data and transform it into manageable and scientific or application-oriented research topics.
After a general introduction and a hands-on primer on programming in Python (e.g., with NumPy, sci-kit-learn), we will dive into several exciting topics, including scraping data from social media and text preprocessing, data exploration, and text classification.
The course will be taught in English.
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.
• crawl a linguistically valuable social media data
• experiment with data from popular social media platforms
• differentiate various types of social media data and methods to process/analyze them
• 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 present a paper or Python library/package
• to submit a 1-2 page research question/hypothesis summary
Rhythmus | Tag | Uhrzeit | Format / Ort | Zeitraum |
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Modul | Veranstaltung | Leistungen | |
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23-CL-BaCL6 Projektmodul | Projektseminar | Studienleistung
benotete Prüfungsleistung |
Studieninformation |
23-CL-BaCL6-KF Projektmodul Kernfach | Projektseminar | Studienleistung
benotete Prüfungsleistung |
Studieninformation |
23-TXT-BaCL6 Projektmodul | Projektseminar | benotete Prüfungsleistung
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Studieninformation |
Die verbindlichen Modulbeschreibungen enthalten weitere Informationen, auch zu den "Leistungen" und ihren Anforderungen. Sind mehrere "Leistungsformen" möglich, entscheiden die jeweiligen Lehrenden darüber.
Zu dieser Veranstaltung existiert ein Lernraum im E-Learning System. Lehrende können dort Materialien zu dieser Lehrveranstaltung bereitstellen: