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Course / Optional Course: Audience data analysis: from segmentation to big data

Subject
Communication Studies
Activitytype
master course
Teaching language
English
Registration

Tilmelding sker via stads selvbetjening indenfor annonceret tilmeldingsperiode, som du kan se på Studieadministrationens hjemmeside

Når du tilmelder dig kurset, skal du være opmærksom på, om der er sammenfald i tidspunktet for kursusafholdelse og eksamen med andre kurser, du har valgt. Uddannelsesplanlægningen tager udgangspunkt i, at det er muligt at gennemføre et anbefalet studieforløb uden overlap. Men omkring valgfrie elementer og studieplaner som går ud over de anbefalede studieforløb, kan der forekomme overlap, alt efter hvilke kurser du vælger.

Registration is happing through stads selvbetjeningwithin the announced registration period, as you can see on the Studyadministration homepage.

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

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, and the demands have become increasingly complex. The goal of the course is to help students navigate the diverse methods, tools and techniques available for collecting, analyzing and evaluating audience data (offline and online, qualitative and quantitative) while maintaining a critical understanding of these analytical practices.

The course introduces students to the methods, tools and techniques used in the industry and academia to perform audience measurement and analysis. There is therefore a practical dimension to the course which will see students working with audience data, especially with regards to the digital footprints left by audiences in their use of digital media and the harvesting of data on web platforms. One of the main objectives of the course is to help students experiment and work creatively with data as a way to produce insights about audiences.

Throughout the course is maintained a critical understanding of audience measurement. The goal is to be able to relate critically to the science, practice and politics of audience measurement and place these in a larger context of academic, societal and ethical debates. These will include discussions of the validity of audience measurement and analysis, both qualitative and quantitative, being aware of the different interests at stake in audience measurement, as well as ethical considerations such as privacy invasion, surveillance and consent.

The course covers topics such as ratings, segmentation, target group analysis, interpretative and qualitative approaches, social media analytics and big data. It will involve a mix of lectures and workshop exercises that will allow students to relate and try their hands at different aspects of audience measurements.

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.

Evaluation- and feedback forms

The study board will evaluate the course this semester.

Administration of exams
IKH Studyadministration (ikh-studyadministration@ruc.dk)
The responsible course lecturer
David Mathieu (mathieu@ruc.dk)
Type of examination

Individual portfolio consisting of written products and other types of products.

The portfolio consists of up to 10 (number determined by the lecturer based on a professional assessment of the individual student's topic) products that are prepared in whole or in part during the course. For example, products can be exercise responses, speech manuscripts for a presentation, feedback, reflection, written assignments, wiki contributions, sound productions and visual productions.

The preparation of the products may be subject to time limits. The portfolio's written products must be 4,800 - 36,000 characters in length, including spaces.

The size specifications include the cover, table of contents, bibliography, figures and other illustrations, but exclude any appendices. The specific content and form of the portfolio, as well as any potential indicative size specifications for the various written products will be determined before the beginning of the course and published on study.ruc.dk.

The portfolio is delivered collectively (uploaded at eksamen.ruc.dk). Any potential partial deliveries to the lecturer in order to get feedback are not a substitute for the collective delivery. The deadline for handing in the assignments will be published on study.ruc.dk.

The assignment must document that the student possesses a confident mastery of the written English language, including grammar and linguistic correctness.

Assessment: 7-point grading scale.

Re-examination:

Same as ordinary

ECTS
10
Learning outcomes and assessment criteria

Knowledge and understanding of a specific subject area in the field of communication, information and media, including having knowledge and understanding of the common practices in relation to th subject area

Knowledge and understanding of current theories relevant to the subject area, including knowledge of essential communications concepts and terms

  • Knowledge and understanding of current methods used to study the subject area

  • Skills in being able to apply relevant theory to a specific communications-related research questio

  • Skills in being able to use appropriate methods to study communications-related research questions

  • Skills in being able to translate analyses and knowledge and understanding to a practical communications-related context

  • Competences in independently being able to take responsibility for one’s own professional development and specialisation within the subject area

Overall content

The course includes presentations and critical discussions as well as the testing the of knowledge about and understanding of a defined subject area within the field of communications, including presentations and discussions of concepts, theories and investigative methods

Prerequisites for participation
Currently no data from curriculum.
Prerequisites for participation in the exam
Currently no data from curriculum.
Teaching and working methods

The course consists of a mix of lectures and discussions, and it can include group work, homework and peer feedback. It is structured around a number of themes that will be presented at the start of the course

Type of course

Optional course

Exam code(s)
Exam code(s) : U41384
Last changed 14/02/2020

lecture list:

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

Thursday 13-02-2020 12:15 - 13-02-2020 16:00 in week 07
Comm: Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Thursday 20-02-2020 12:15 - 20-02-2020 16:00 in week 08
Comm: Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Thursday 05-03-2020 12:15 - 05-03-2020 16:00 in week 10
Comm: Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Thursday 19-03-2020 12:15 - 19-03-2020 16:00 in week 12
Comm: Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Monday 30-03-2020 08:15 - 30-03-2020 12:00 in week 14
Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Thursday 02-04-2020 12:15 - 02-04-2020 16:00 in week 14
Comm: Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Wednesday 15-04-2020 08:15 - 15-04-2020 12:00 in week 16
Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Monday 20-04-2020 08:15 - 20-04-2020 12:00 in week 17
Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Monday 27-04-2020 08:15 - 27-04-2020 12:00 in week 18
Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Thursday 30-04-2020 13:00 - 30-04-2020 17:00 in week 18
Comm: Advanced theory, method and practice: Audience data analysis: from segmentation to big data - excursion

Monday 11-05-2020 08:15 - 11-05-2020 12:00 in week 20
Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Monday 18-05-2020 08:15 - 18-05-2020 12:00 in week 21
Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Thursday 04-06-2020 10:00 - 04-06-2020 10:00 in week 23
Exam in Advanced theory, method and practice: Audience data analysis: from segmentation to big data

Monday 10-08-2020 10:00 - 10-08-2020 10:00 in week 33
Reexam in Advanced theory, method and practice: Audience data analysis: from segmentation to big data