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.
Master’s thesis format
Students can choose the following formats:
- Classic Master’s thesis
- Scientific article(s)
- Annotated dataset
- Report for external partner
Classic Master’s thesis
The Master’s thesis must fulfil the standard requirements above as
well as those in the Curricula’s Common Part.
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.
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
and two supervisors among the group of full-time teachers at the
Faculty of Social Sciences. The cluster will meet weekly during the
semester to discuss how to structure data collection, analysis and
writing. The meetings are not compulsory.
The assignment of students to supervision clusters is done by a
full-time lecturer appointed by the Head of Studies. The assignment
is based on students’ requests as well as overlap between the
proposed thesis format, supervisors’ profiles and overlap with the
proposed format of other students under supervision. In unusual
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.
Students must register for the Master’s thesis in accordance with the rules laid down by section 4.2.4 of the Curricula’s Common Part.
It is not possible to cancel the thesis contract once it has been
approved by the University. For a detailed description of the
registration procedures, see the study pages on
KUnet.
- ECTS
- 30 ECTS
- Type of assessment
-
Oral defence, 1 hour
- Type of assessment details
- The Master’s thesis is defended in an oral defence based on the
student's written presentation. The oral defence lasts one hour
in total, and the student has approximately 20 minutes to make the
presentation.
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 another language than Danish, even if the Master’s thesis is not written in Danish. The summary may be in English, German or French. Swedish and Norwegian do not count as foreign languages, cf. the Danish Examination Order.
The Master’s thesis may be written individually or together in a group by a maximum of three students. If written by one student, the total number of pages in the Master’s thesis must amount to no more than 40 standard pages; with two students the limit is 60 pages; with three 80 pages.
Students co-writing their Master’s thesis defend it together. - Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
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 (8-697068756b72787743767266316e7831676e)
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