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PhD course

Qualitative Digital Methods for Social Scientists

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Course description

Language of instruction

English

Course content

*What are qualitative digital methods (QDMs)?

*What kind of knowledge do QDMs generate?

*How can we use QDMs to help us to understand social, political and spatial processes?

*What ethical challenges do QDMs pose, and how can qualitative digital research be done ethically?

This course addresses how qualitative digital methods can inform research in the social sciences, including media and communications, anthropology, human geography, sociology, and political science. It will provide hands-on experience of using QDMs, guidance on designing research using these methods, and an introduction to the interdisciplinary literature on the digital transformation of society. The course will also include a guidance and reflection on ethics in digital methodologies and strategies for preparing an application for NSD* for ethical approval of digital data.

Examples of the kinds of issues studied during the course (illustrated by case studies):

  • How to research cultural identities, political discussion, online-offline dynamics of protests and processes of social inclusion and exclusion in digital and mixed environments.
  • Ethical issues involved in the gathering and presentation of digital data.
  • Digital mapping techniques, and the use of digital date to investigate urban processes.
  • The accessibility, quality and variety of digital data and the qualitative methods used to capture and analyze them.
  • The transferability of long-standing qualitative methods to digital contexts, and the development of `digitally native' methods.

Examples of skills students will learn through the course:

  • Design research questions and find ways to investigate them using QDMs
  • Use QDMs to visualize and map digital networks, e.g. become familiar with scripts for accessing APIs** and performing network analysis, to gain insights into the dynamics of debate and contention on Twitter.
  • Use QDMs to perform a visual analysis of digital content, e.g. of the aesthetics of protest on YouTube.
  • Use QDMs to investigate multi-platform media representations, e.g. use Media Cloud and Twitter to investigate the construction of neighborhood reputations.

*Norwegian Centre for Research Data

**Application Programming Interface.

Learning outcomes

Upon successful completion of this course the participants should be able to:

5 ECTS:

  • Formulate and express arguments about the value, ethical challenges and limitations of qualitative analysis of digital data clearly and cogently, both orally and in writing.
  • Demonstrate knowledge of critical and analytical approaches within both theory and methodology in the domain of digitally mediated social interaction, specifically drawing on the literature assigned to the course.
  • Prepare and present a paper that engages one or several of the issues of the course and which makes use of one or several case studies (Assignment 1)
  • Demonstrate in the context of guided workshops the ability to gather and analyze digital data in a manner appropriate to your field of enquiry.
  • Receive and give constructive criticism to other course participants

10 ECTS:

  • Formulate and express arguments about the value, ethical challenges, and limitations of qualitative analysis of digital data clearly and cogently, both orally and in writing.
  • Demonstrate knowledge of critical and analytical approaches within both theory and methodology in the domain of digitally mediated social interaction, specifically drawing on the literature assigned to the course.
  • Prepare and present a paper that engages one or several of the issues of the course and which makes use of one or several case studies (Assignment 1)
  • Demonstrate the ability to gather and analyze digital data in a manner appropriate to your field of enquiry in the context of a paper and presentation related to your research topic (Assignment 2)
  • Receive and provide constructive criticism on the assignments.
  • Undertake an investigation using QDMs on a topic of relevance to the participant's doctoral studies and communicate findings orally and in writing.

Study period

Autumn 2022.

Session 1: 12 to 15 September (5 and 10 ECTS)

Session 2: November one day tba by negotiation with participants (10 ECTS)

Credits (ECTS)

5 or 10 ECTS

Specific terms

Course registration and deadlines

Application deadline 17 August 2022, 4 weeks prior to first course day.

Participants apply for admission here

Course dates: 12 to 15 September and a session with presentation in November (only for 10 ECTS students).

The maximum number of participants is 16.

Recommended previous knowledge

Specified reading prior to the first course day

Reading list

Compulsory Requirements

  • Before the course starts, each PhD student will prepare a 2500-word essay (+/- 10 percent, excluding references) for pre-circulation, addressing her or his research project in relation to the course theme.
  • Each PhD student must also familiarize himself/herself with the course literature and overview of lectures before the course (see separate document)
  • Each PhD student must also act as a commentator of another PhD student's paper during the course.
  • Each PhD student must participate in the guided workshops introducing digital methods

Form of assessment

5 ECTS:

  • Presentation of the pre-circulated essay
  • Instructor assessment of satisfactory participation in digital workshops

10 ECTS:

  • Presentation of the pre-circulated essay
  • Paper (2500 Words +/- 10 percent, excluding references). Within two months after the course participants will submit a paper which reports on their use of QDMs to address the research topic.
  • Presentation of the paper at a follow up workshop, either digitally or in person.

Who may participate

PhD students in media and communications studies, anthropology, political science, human geography, sociology or related humanities fields e.g. history, religious studies, either before or after conducting qualitative fieldwork involving digital methods, or considering doing so. PhD candidates for the Faculty of Social Sciences will be given priority.

Student participation in the course will be in person.

Additional information

Programme

The program will blend lectures, workshops, and discussions, with PhD students presenting and discussing their papers. Check the detailed program for a list of titled lectures and slots for PhD students.

In the course seminars, each paper will be allotted ca. 45 minutes, beginning with the PhD student presenting a 15-minute summary of the paper's contents. This is followed by a 10-minute commentary from one of the other PhD students (selected in advance), after which she or he will chair an open discussion on the paper for approximately 20 minutes.

Workshop and paper discussion sessions will be physical, as will most lectures, with one digital lecture and a final hybrid plenary.

Contact

Anna Polster

Anna.Polster@uib.no

Academic responsibility

Professor David Herbert, Sociology, University of Bergen

Lecturers

Internal:

Dag Elgesem (Media and Communications, UiB); Gidske Andersen (Human Geography, UiB); Knut Helland (Media and Communications, UiB); Knut Mikjel Rio (Anthropology, UiB); Ragnhild Overå (Human Geography, UiB)

External:

Alberta Giorgi, (Media and Communications, University of Bergamo, Italy)

John Boy, (Cultural Anthropology, University of Leiden, Netherlands)

Hande Eslen Ziya, (Media and Communications, University of Stavanger)

Reading list

Each PhD student must familiarize himself/herself with the course literature and overview of lectures before the first course day.

Course location

UiB, Social Sciences Faculty Building (SV-bygget) meeting room 902, Norway

Contact

Exam information

  • Type of assessment: Presentations and Paper

    • Exam part: PAPER

    • Exam part: PRESENTATIONS

  • Type of assessment: Presentation and instructor assessment

Study period

Autumn 2022.

Session 1: 12 to 15 September (5 and 10 ECTS)

Session 2: November one day tba by negotiation with participants (10 ECTS)