Master's Thesis

Course content

The Master’s thesis is the conclusion of the degree programme. The purpose of the Master’s thesis is for students to acquire research-based competencies by conducting a social data science in-depth study of a problem of their choosing. This includes identifying a problem by gathering and analysing relevant social data and applying methodological, theoretical, ethical and legal perspectives while at the same time incorporating social science and data science. Relevant data may include, but is not limited to, big social data from e.g. social media platforms or other sources.

Education

Master’s thesis format


Students can choose the following formats:

  • Social Data Science Monograph
  • Scientific article(s)
  • Annotated dataset
  • Report for external partner

 

Social Data Science Monograph
The Master’s Thesis must meet the learning outcomes described below in one comprehensive piece of writing and fulfil the requirements in the Curricula’s Common Part. The thesis should be written at a level comprehensible to any graduate of the MSc in Social Data Science and should reflect all learning content of the program relevant to the project. This means for example:

  • Empirical theses should include sections related to data collection, analytical methodology, and the ethical and legal context for both.
  • Theoretical or methodological theses should include sections comprehensively placing the problem the thesis addresses in the relevant literature, and might include sections applying a comprehensive set of relevant angles to the problem (e.g., different stakeholders, different 38 ethical principles, different theoretical or conceptual perspectives) or evaluating the proposed methodology against existing baselines.


Scientific working paper
The Master’s thesis must fulfil the standard criteria and contain the following main components:

  • A companion framing text containing a more comprehensive introduction and background giving a comprehensive account of the theory and methods employed, outlining the social scientific/academic background for the study. Any ethical or legal concerns, e.g. about data collection, data processing, fieldwork, application of algorithms, should be analysed and critically reflected upon.
  • One scientific working paper. The working paper should be written with the style, format, and length of a “letter” or “short article” in a top social science journal of the student’s choosing, emphasizing how the Master’s thesis contributes to existing literature.

 

Annotated dataset
The Master’s thesis must fulfil the standard criteria and contain the following main components:

  • A companion framing text containing a more comprehensive introduction and background giving a comprehensive account of the theory and methods employed, outlining the social scientific/academic background for the study. Any ethical or legal concerns, e.g. about data collection, data processing, fieldwork, application of algorithms, should be analysed and critically reflected upon. The companion framing document should also state how the dataset is useful for new research and/or for commercial as well as social purposes.
  • A detailed annotated dataset, including a thorough account of how data was produced, cleaned, categorized, and/or analysed, as relevant for the intended purpose of the dataset.

 

Report for external partner
The Master’s thesis must fulfil the standard criteria and contain the following main components:

  • A report, primarily addressed to an external party, in which a problem from an academic internship/​project-oriented work or data collection is analysed.
  • A companion paper containing a more comprehensive introduction and background giving a comprehensive account of the theory and methods employed, outlining the social scientific/academic background for the study, the social context and relation to the external partner. The paper should challenge and discuss the project-oriented work for the external partner, targeted at an academic audience. Any ethical or legal concerns, e.g. about data collection, data processing, fieldwork, application of algorithms, should be analysed and critically reflected upon.
Learning outcome

At the end of the Master’s thesis, students are able to:


Knowledge

  • Account for the scientific and social potentials of the investigation or development.
  • Relate critically to existing knowledge within this area.
  • In connection with the oral defence, the student must demonstrate a command of the methodologies applied in connection with the preparation of the Master’s thesis.

 

Skills

  • In connection with the oral defence, the student must be able to account for the issue of the thesis and its clarification in a clear and comprehensible manner.
  • Structure and argue convincingly while processing the problem.
  • Critically assess the quality and use of empirical data or algorithms employed in the Master’s thesis, including any legal, ethical, political or other relevant considerations.
  • Justify the design and discuss the choice of methodology.
  • Justify in what sense new knowledge has been generated or new light shed on existing knowledge and qualify this in terms of usefulness, topicality, theory or methodological progress.
  • Account for the distinct social science contribution to knowledge made by the analysis and how it is part of a social data science approach.

 

Competencies

  • Formulate a precise problem statement/research question.
  • Independently take responsibility for own academic progress.
  • Plan, structure and implement a social data science study in accordance with scientific standards.
  • Independently manage and coordinate the collaboration with fellow student, supervisor, and potential external partner; including handling interdisciplinary differences, political or commercial interests, time schedules etc.
  • Apply relevant social science theory in the analysis and present independent observations on it.
  • Discuss the knowledge produced critically and put it into perspective.

Students are assigned to a cluster consisting of 4-6 students with two supervisors per cluster. The supervisors are drawn from a supervisor pool made up of the full-time teachers at the Master’s program and PhD students and post docs affiliated with the Copenhagen Center for Social Data Science (SODAS). The cluster will meet during the semester by appointment.

The assignment of students to supervision clusters is done by the Head of Studies or a full-time lecturer appointed by the Head of Studies. The assignment is based on supervisor availability, fit between supervisor profiles and proposed thesis topic and format, students’ requests as well as overlap among all students signed up for the Master’s Thesis. In exceptional circumstances, students may apply to the Board of Studies for an external supervisor.

Please note that supervision is only offered in connection with the first thesis contract

Oral
Continuous feedback during the course of the semester
ECTS
30 ECTS
Type of assessment
Oral defence, 1 hour
Type of assessment details
The Master’s thesis may be written individually or together in a group by a maximum of three students. For the classic Master’s thesis, the total number of pages must amount to no more than 40 standard pages for a single student, 60 pages for groups of two students, and 80 pages for groups of three students. For the non-classic formats, the same page limits apply to the combination of all thesis components.

The Master’s thesis is defended in an oral defence based on the student’s written presentation. Students co-writing their Master’s thesis defend it together. The duration of the oral defence is one hour for one student, with 15 minutes added for each additional student in a group. This time frame includes dedicated time for an initial discussion among external censor and supervisors (up to 1/6 of the total duration) and time for students’ presentation (approximately one third of the total duration).

The Master’s thesis must include a summary that summarizes the main points of the Master’s thesis and how the student arrived at these points. The summary must be written in English, German or French, even if the Master’s thesis is not written in Danish.
Exam registration requirements

It is a requirement that 60 ECTS credits have been passed before the thesis writing period begins. Students are strongly encouraged to place the Master’s thesis in their final semester, and as a minimum complete all compulsory courses before writing their thesis.

Aid
All aids allowed

ChatGPT and other large language model tools are permitted as a dedicated source, meaning text copied verbatim needs to be quoted, the tool cited, and generally the specific use made of them needs to be described in the submitted exam.

Marking scale
7-point grading scale
Censorship form
External censorship
Re-exam

Re-examination: Students who fail to submit their Master’s thesis within the stipulated deadline must register for a second examination attempt (and, if needed, a third attempt) in accordance with the rules laid down by section 4.2.5 of the Curricula’s Common Part.
The student cannot make use of second and third attempts if the maximum completion time is exceeded. In that case, the student is disenrolled from the University regardless of whether all attempts have been used.

Criteria for exam assessment

The Master’s thesis and the oral defence are graded according to the Danish 7-point grading scale. The exam is graded by an external examiner.


The summary is included in the assessment of the Master’s thesis. The assessment of the Master’s thesis is weighted in such a way that the written part weighs approx. 2/3 and the oral part approx. 1/3.


Writing and spelling skills form part of the overall assessment of the Master’s thesis. However, the academic content is assigned the highest weight. The Board of Studies might grant an exemption from this rule in case of impairment, cf. the Danish Examination Order.


Criteria for exam assessment: The exam will be assessed on the basis of the learning outcome (knowledge, skills and competencies) for the Master’s thesis.

  • Category
  • Hours
  • Guidance
  • 40
  • Exam Preparation
  • 802
  • Exam
  • 1
  • English
  • 843

Kursusinformation

Language
English
Course number
ASDK20100E
ECTS
30 ECTS
Programme level
Full Degree Master
Duration

1 semester

Placement
Autumn And Spring
Studyboard
Social Data Science
Contracting department
  • Social Data Science
Contracting faculty
  • Faculty of Social Sciences
Course Coordinator
  • Friedolin Merhout   (8-6b726a776d747a794578746833707a336970)
Saved on the 16-01-2024

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