Stud.IP Uni Oldenburg
University of Oldenburg
08.05.2021 22:01:15
Seminar: 1.07.251 Frei wählbares Modul: Introduction to digital trace data in social science - Details
You are not logged into Stud.IP.

General information

Course name Seminar: 1.07.251 Frei wählbares Modul: Introduction to digital trace data in social science
Subtitle (Lehrsprache Englisch)
Course number 1.07.251
Semester Sommersemester 2019
Current number of participants 10
expected number of participants 25
Home institute Department of Social Sciences
Courses type Seminar in category Teaching
Preliminary discussion Thu., 11.04.2019 12:00 - 14:00, Room: A06 3-313 (OLExS-Labor)
First date Thu., 11.04.2019 12:00 - 14:00, Room: A06 3-313 (OLExS-Labor)
Type/Form S 2SWS
Lehrsprache englisch
ECTS points 6

Course location / Course dates

A06 3-313 (OLExS-Labor) Thursday. 11.04.19 12:00 - 14:00
Friday. 10.05.19 14:00 - 18:00
Saturday. 11.05.19 09:00 - 15:00
Friday. 07.06.19 14:00 - 18:00
Saturday. 08.06.19 09:00 - 15:00
Friday. 05.07.19 14:00 - 18:00
Saturday. 06.07.19 09:00 - 15:00

Comment/Description

Nowadays, diverse kinds of data with a large volume have become available to researchers. Online digital trace data in particular has a great potential for new approaches to social science questions.
This course focuses on digital trace data extraction and introduces network analysis which are typical analytical tools for digital trace data. In the first block, students will learn how to collect and manage digital trace data by using Python. In the second block, students learn basic network theories and do exercise to analyze exemplary digital trace data using the network-theoretic concepts such as centralities and clustering. In the third block, the course introduces co-occurrence networks and the exponential random graph model (ERGM). At the end of the course, each student submits a short paper which demonstrates network analyses using digital trace data collected for themselves.
Please bring your own notebook. Alternatively, you can use a computer from the laboratory.

Admission settings

The course is part of admission "Anmeldung gesperrt (global)".
Erzeugt durch den Stud.IP-Support
Settings for unsubscribe:
  • Admission locked.