PDF for print Find calendar

Elective course: Audience Data Analysis: From Segmentation to Big Data

Title
Elective course: Audience Data Analysis: From Segmentation to Big Data
Semester
E2025
Master programme in
Communication Studies / Media and Communication
Type of activity

Course

Mandatory or elective

Elective

Teaching language
English
Study regulation

Read about the Master Programme and find the Study Regulations at ruc.dk

REGISTRATION AND STUDY ADMINISTRATIVE
Registration

You register for activities through stads selvbetjening during the announced registration period, which you can see on the Study administration homepage.

When registering for courses, please be aware of the potential conflicts and overlaps between course and exam time and dates. The planning of course activities at Roskilde University is based on the recommended study programmes, which should not overlap. However, if you choose optional courses and/or study plans that goes beyond the recommended study programmes, an overlap of lectures or exam dates may occur depending on which courses you choose.

Number of participants
ECTS
10
Responsible for the activity
David Mathieu (mathieu@ruc.dk)
Head of study
David Mathieu (mathieu@ruc.dk)
Teachers
Study administration
IKH Registration & Exams (ikh-exams@ruc.dk)
Exam code(s)
U60599
ACADEMIC CONTENT
Overall objective

The course contains presentation and critical discussion as well as testing knowledge of a defined media and communication subject area/field of activity, including presentation and discussion of current practice concepts, theories, and research methods, possibly in collaboration with practitioners within the field.

Detailed description of content

This course is about the science, practice and politics of audience measurement and analysis. Audience data analysis is increasingly a needed skill for communication professionals. The goal of the course is to help students navigate the diverse methods, tools and techniques used in the industry and academia for collecting, analyzing and evaluating audience data while maintaining a critical understanding of these analytical practices. There is therefore a practical dimension to the course which will see students working with a diversity of audience data (measurements, metrics, interview, etc).

The course relates to the communicative and media-related aspects of audience measurement, and not the technical aspects such as programming or statistical analysis. No pre-requisite knowledge of these is required to participate and benefit from the course. We will work with relatively simple tools and will get help to assist with technical aspects of using softwares. We will have our focus on how these tools help us understand communication and provide insights about audiences.

Course material and Reading list

Readings for the course will be made available on Moodle. Reading guidelines are provided for each reading.

Overall plan and expected work effort

The total study effort for the student (ECTS points converted into hours) = 270 hours. The hours are divided as follows:

  • Course teaching: 40 hours
  • Reading the course literature: 150 hours
  • Preparation and research: 60 hours. These could include: researching and preparing an oral presentation; designing, conducting and analysing interviews; collecting, preparing and analysing data; preparing competency statements, etc.
  • Other activities: 20 hours (semester start, literature search, etc.)
Format

In principle, teaching activities take place on campus. The teaching can be arranged so that one or more activities take place elsewhere than at Roskilde University. This can also be online.

Evaluation and feedback

Evaluation is based on the evaluation practice of the study board.

Programme

The course is organised in 3 modules that cover topics such as 1) audience ratings, segmentation, target group analysis, 2) social media analytics and metrics, big data and data research ethics, as well as 3) interpretative and socio-cultural analysis. Each session involves a mix of lectures and workshop exercises that will allow students to relate and try their hands at different aspects of audience measurement. If possible, the course will include a visit to DR-byen to meet with the head of audience research at DR (the Danish public broadcaster), followed by a guided tour of the premises.

ASSESSMENT
Overall learning outcomes

At the end of the course, the student is able to:

  • Demonstrate in-depth knowledge of a defined subject area/field of activity within media and communication, including nuanced knowledge of common practice in relation to the subject area.

  • Identify and account for current theories of relevance to the subject area/field of activity, including understanding of significant communication professional issues.

  • Develop, organize and present a specific communication production or practice relevant to the subject area/field of activity.

  • Independently and reflectively translate theoretical perspectives and methodological approaches into a concrete communication professional practice.

  • Independently take responsibility for one's own professional development.

Prerequisites
Form of examination
Active, regular attendance, and satisfactory participation

Active participation is defined as:
The student must participate in course-related activities (e.g., workshops, seminars, field excursions, process study groups, working conferences, supervision groups, and feedback sessions).

Regular attendance is defined as:
- The student must be present for a minimum of 80 percentof the lessons.

Satisfactory participation is defined as:
- e.g., oral presentations (individually or in a group), peer reviews, mini projects, tests, and planning of a course session.

Assessment: Pass/Fail
Form of Re-examination
Individual written take-home assignment

The character limit of the assignment is: 28,800-36,000 characters, including spaces.
The character limit includes the cover, table of contents, bibliography, figures and other illustrations, but exclude appendices.

The duration of the take-home assignment is 7 days and may include weekends and public holidays.



Assessment: Pass/Fail
Type of examination in special cases
Examination and assessment criteria (implemented)

The course is assessed on the basis of active participation. An overall assessment is made of the student performance based on the 3 criteria involved in the exam form (active, regular and satisfactory participation). Students will be notified at the end of the course via eksamen.ruc.dk whether they passed or failed the course.

In the context of this course: Active participation means that the students have to participate in the workshops that are planned for nearly all lectures and in related activities, such as the field excursion to DR. Regular attendance means that students must be present for at least 8 course sessions out of 10. Satisfactory active participation means that students have done the readings in preparation for each lecture and are able to discuss and reflect on these in class as well as implement these readings in their group work during the workshops. Additionally, students have to engage in group work constructively and competently, present their work in plenum and provide feedback to each others' work.

In special cases (e.g. documented sickness), a student may be asked to produce individual additional assignments in order to palliate a lack in active, regular and satisfactory participation.

Students are referred to the following guidelines regarding exam cheating and its consequences: https://intra.ruc.dk/en/students/study-administration/everything-about-exam/avoid-cheating-at-exams/

Exam code(s)
Exam code(s) : U60599
Last changed 02/05/2025

lecture list:

Show lessons for Subclass: 1 Find calendar (1) PDF for print (1)

Monday 01-09-2025 12:15 - 01-09-2025 16:00 in week 36
Audience Data Analysis: From Segmentation to Big Data
-

Friday 05-09-2025 12:15 - 05-09-2025 16:00 in week 36
Audience Data Analysis: From Segmentation to Big Data
-

Monday 08-09-2025 12:15 - 08-09-2025 16:00 in week 37
Audience Data Analysis: From Segmentation to Big Data
-

Friday 12-09-2025 12:15 - 12-09-2025 16:00 in week 37
Audience Data Analysis: From Segmentation to Big Data
-

Monday 15-09-2025 12:15 - 15-09-2025 16:00 in week 38
Audience Data Analysis: From Segmentation to Big Data
-

Thursday 18-09-2025 12:15 - 18-09-2025 16:00 in week 38
Audience Data Analysis: From Segmentation to Big Data
-

Monday 22-09-2025 12:15 - 22-09-2025 16:00 in week 39
Audience Data Analysis: From Segmentation to Big Data
-

Thursday 25-09-2025 12:15 - 25-09-2025 16:00 in week 39
Audience Data Analysis: From Segmentation to Big Data
-

Monday 29-09-2025 12:15 - 29-09-2025 16:00 in week 40
Audience Data Analysis: From Segmentation to Big Data
-

Thursday 02-10-2025 12:15 - 02-10-2025 16:00 in week 40
Audience Data Analysis: From Segmentation to Big Data
-

Monday 12-01-2026 10:00 - Monday 19-01-2026 10:00 in week 03 and week 04
Audience Data Analysis: From Segmentation to Big Data
-