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Veranstaltung

Semester: Sommersemester 2021

1.07.0691 Politikfeldanalyse: Digital Governance - Doing research using digital trace data -  


Veranstaltungstermin | Raum

  • Freitag, 16.4.2021 10:00 - 12:00 | online
  • Freitag, 23.4.2021 10:00 - 12:00 | online
  • Freitag, 30.4.2021 10:00 - 12:00 | online
  • Freitag, 7.5.2021 10:00 - 12:00 | online
  • Freitag, 14.5.2021 10:00 - 12:00 | online
  • Freitag, 21.5.2021 10:00 - 12:00 | online
  • Freitag, 28.5.2021 10:00 - 12:00 | online
  • Freitag, 4.6.2021 10:00 - 12:00 | online
  • Freitag, 11.6.2021 10:00 - 12:00 | online
  • Freitag, 18.6.2021 10:00 - 12:00 | online
  • Freitag, 25.6.2021 10:00 - 12:00 | online
  • Freitag, 2.7.2021 10:00 - 12:00 | online
  • Freitag, 9.7.2021 10:00 - 12:00 | online
  • Freitag, 16.7.2021 10:00 - 12:00 | online

Beschreibung

The wave of digitalization has changed the way of governance. Public authorities utilize their online channels in diverse way, e.g., announcing the policy, participating in public discourse, communicating with public etc. This course introduces technical skills to collect and analyze such digital footprints. More concretely, this course introduces Twitter API and provides multiple examples of collecting and analyzing Twitter data in R.
The course will start with general introduction of Twitter's API, available data and limitations. Subsequently, participants will learn how to collect diverse types of Twitter data (e.g., user timelines, tweets including certain keywords). To analyze collecting data, the course will discuss summary statistics of interested features, text analysis and simple network analysis (e.g. retweet network). Along with the data analysis, diverse possibilities for visualization will be demonstrated as well. During the course, students collect and analyze Twitter data based on their own research question (individually or in a small group). At the end of the course, students submit a report that summarize the process of data collection and analysis results.
The course is held in English. Previous experience in R is preferable but not required.

lecturer

SWS
2

Lehrsprache
englisch

(Stand: 19.01.2024)  | 
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