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Seminar: 09-406-D.1-4 Practical Seminar 4: Computational methods - Network Analysis and Visualisation for Computational Social Science with Python and Gephi - Details

Seminar: 09-406-D.1-4 Practical Seminar 4: Computational methods - Network Analysis and Visualisation for Computational Social Science with Python and Gephi - Details

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General information

Course name Seminar: 09-406-D.1-4 Practical Seminar 4: Computational methods - Network Analysis and Visualisation for Computational Social Science with Python and Gephi
Subtitle
Course number 09-406-D.1-4
Semester SoSe 2025
Current number of participants 5
maximum number of participants 30
Home institute Kommunikations- und Medienwissenschaften
Courses type Seminar in category Teaching
First date Friday, 11.04.2025 11:00 - 12:00, Room: (Vorbesprechung am 11.04. online via Zoom)
Type/Form
Englischsprachige Veranstaltung Ja

Rooms and times

(Vorbesprechung am 11.04. online via Zoom)
Friday, 11.04.2025 11:00 - 12:00
LINZ4 60070
Friday, 13.06.2025, Friday, 27.06.2025, Friday, 04.07.2025, Friday, 11.07.2025 11:00 - 17:00

Module assignments

Comment/Description

Media and communication scholars and social scientists have always, at least implicitly, developed
theories about the structures and dynamics of networks. Today, the internet, online news, and social
media not only make these networks appear more visible, measurable, and complex, but their ubiquity
also creates a need to deal explicitly with the network paradigm – in theory, empirical research, and in
practice. In turn, networks, as models of interactions or relations, allow a researcher to tame phenomena
of organized complexity and therefore to analyse social phenomena from singular qualitative details,
through repeating patterns, up to global trends and comparisons in and between whole societies.
This class focuses on how questions that are relevant to the social sciences in general and communication
science in particular may be approached, using digital media data in combination with the visualization
and analysis of networks. The course will follow a hands-on approach, with short theoretical sessions
followed by coding and analysis challenges for which the participants will need to acquire new skills, using
a combination of Python and a network visualization tool (Gephi or Gephi Lite). They will be introduced to
behavioural trace data collection, network sampling, network modelling, (social) network measures,
community detection methods, network visualization as well as some basic (partly automated) content
analysis techniques to interpret the results. As part of a group project, participants will apply a set of
techniques that we have studied to a dataset or data collection of their choice.

Admission settings

The course is part of admission "Beschränkte Teilnehmendenanzahl: Practical Seminar 4: Computational methods".
The following rules apply for the admission:
  • At least one of these conditions must be fulfilled for enrolment:
    • Subject is ea9d0a6e64eb5d0ae99eeca825160a88
    • Subject is 57454d2eff7c96d8631ba5c87a2f5bf9
    • Subject is Media and Public Engagement
  • A defined number of seats will be assigned to these courses.
    The seats will be assigned in order of enrolment.
  • The enrolment is possible from 24.03.2025, 10:00.

Registration mode

After enrolment, participants will manually be selected.

Potential participants are given additional information before enroling to the course.