Universität Wien
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230151 SE M6 Digital Methods and their Integration with Qualitative Approaches (2024W)

Sociological Specialisation of Choice

5.00 ECTS (2.00 SWS), SPL 23 - Soziologie
Continuous assessment of course work
Moodle
Tu 01.10. 16:45-18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre

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).
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Details

max. 25 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 08.10. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 15.10. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 29.10. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 05.11. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 12.11. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 19.11. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 26.11. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 03.12. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 10.12. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 17.12. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 07.01. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 14.01. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 21.01. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre
  • Tuesday 28.01. 16:45 - 18:15 Seminarraum H10, Rathausstraße 19, Stiege 2, Hochparterre

Information

Aims, contents and method of the course

The point of departure for this seminar is the observation that we increasingly deal with large amounts of data in everyday life and in the practice of social science. The development of new approaches, particularly in computational social science and digital methods, affects existing sociological methodologies, including qualitative research approaches. The course aims to explore the possibilities and limitations of integrating such approaches with qualitative research methodologies.

Initially, the course focuses on a theoretical and methodological approach to the phenomenon of “big data.” Approaches from American cultural sociology, which suggest opportunities for hermeneutic and context-sensitive methods, will be presented and critically discussed together. The seminar pays particular attention to relational approaches (relations between text elements and between actors) both methodologically and practically (in the form of network analyses). Students will learn about practical examples and examine their methodological procedures as well as their potential integration into the principles and applications of qualitative research.

In the second part of the course, students will learn some fundamental technical aspects (data collection, data cleaning, pre-processing) as well as possibilities and techniques of visualization. Students will work in groups on their own small research projects. These projects will consider the possibilities of integrating computational social science methods with existing qualitative methods (various forms of discourse analysis and qualitative content analysis, interviews).

Key competencies to be acquired by students include:

-Theoretical Foundation: The linkage of computational methods (especially text-as-data methods) to cultural sociology and the sociology of knowledge, as well as various currents of relational sociological theory.
-Meaningful and justifiable connections with other methods: Especially discourse analysis and interviews.
-Getting to know other fields of application: Data collection, visualization, as well as data journalism and science communication.

Prerequisites:
-Basic knowledge of R software or comparable text statistical software.

A detailed course program will be presented at the beginning of the semester and will be accessible via the Moodle learning platform.

Assessment and permitted materials

• Active participation and regular attendance
• Reading the texts
• Students must formulate a question about the text each week and post it on Moodle by Monday evening, 10 PM
• Development and presentation of a research project in small groups

The research project should be submitted in the form of a written paper of 5 to 7 pages (12,500 to 17,500 characters including spaces), including an appendix with code and a detailed description of the practical research steps (no page limit for the appendix). The paper should address a methodological approach discussed in the seminar and apply it. At least one text from the literature discussed in the seminar should be considered. Additional relevant literature should be independently researched. Further details on the content and formal requirements will be announced in the first class session.

For a note by the SPL Sociology, please see the German version

Minimum requirements and assessment criteria

This is an immanent course with mandatory attendance. For a positive evaluation, the following partial achievements must be completed in addition to regular and active participation in the sessions:

• Preparation, discussion, and presentation of academic literature (10%)
• Students should read the basic literature announced in the course and actively participate in the discussion of the literature during the seminar.
• Posting a weekly question about the text on Moodle (30%)
• Presentation of the research project proposal in the group (20%)
• Finalization of the research project proposal in the group in the form of a written paper (40%)

The exact content and formal requirements will be announced during the course.

Examination topics

For a positive completion, all partial achievements must be passed, and the minimum attendance requirement must be met.

Reading list

Salganik, M. J. (2017) Bit by Bit: Social Research in the Digital Age. Princeton, NJ: Princeton University Press. Open review edition, https://www.bitbybitbook.com/en/1st-ed/preface/
Jünger, J, & Gärtner, C. (2023). Computational Methods für die Sozial-und Geisteswissenschaften. Springer Nature.
Bonikowski, B., & Nelson, L. K. (2022). From ends to means: The promise of computational text analysis for theoretically driven sociological research. Sociological Methods & Research, *51*(4), 1469-1483.
Lena, J. C., et al. 2019. Measuring culture. Columbia University Press.

Association in the course directory

Last modified: Mo 16.09.2024 14:06