230149 SE Computer supported content analysis (2015S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from We 04.02.2015 08:00 to Tu 24.02.2015 23:59
- Deregistration possible until Su 15.03.2015 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 10.03. 09:00 - 10:30 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
- Monday 01.06. 09:00 - 14:00 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
- Monday 08.06. 09:00 - 14:00 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
- Monday 15.06. 09:00 - 14:00 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
- Monday 22.06. 09:00 - 14:00 Seminarraum STS, NIG Universitätsstraße 7/Stg. II/6. Stock, 1010 Wien
Information
Aims, contents and method of the course
This course offers a hands-on introduction to systematic methods for content analysis with a special focus on computer supported text analysis. Based on a broad range of analytic traditions, such as grounded theory, critical discourse analysis, controversy studies, issue mapping, and socio-semantic network analysis students will develop skills in data collection, preparation and analysis practices, exploring a range of techniques and approaches. The objective is to equip students with the necessary experience to be able to select appropriate methods for their own research questions.
Assessment and permitted materials
Minimum requirements and assessment criteria
Examination topics
The class is set up like a collaborative research project dealing with the issues revolving around shale gas and fracking. Therefore, students will choose thematic groups and assignments at the beginning of the semester, collect relevant text data until the start of the course in June. We will only use freely available software, to be installed and used on students personal computers.Students are expected to complete all reading and other assignments prior to class. Time in class will be split between lectures, discussions, and group-exercises. Lectures will review conceptual points and challenges of each approach and data type (e.g. social media vs news media). Exercises contain practising methods of data collection and text analysis. The last meeting will be spent presenting and discussing results.
Reading list
Association in the course directory
Last modified: Mo 07.09.2020 15:39