Student Pages
Undergraduate course

Social Networks Theory

  • ECTS credits10
  • Teaching semesterAutumn
  • Course codeINF207
  • Number of semesters1
  • LanguageEnglish
  • Resources

Main content

Level of Study




Teaching semester

Autumn. In odd numbered years, the course code INFO207 is used for registering.

Objectives and Content


The course provides an overview of how theoretical frameworks from different fields can be used to model and analyze complex social networks. Social network theory helps us understand the structure of the various social networks, how they evolve, how communication in social networks occurs, and how networks form the basis for interaction. The network terminology is central to many subjects, like economics, sociology, computer science, information science and mathematics. An interdisciplinary approach to social networking gives the possibility of analyzing common characteristics of seemingly disparate phenomena, from how information and behavior spreads in electronic social networks to how epidemics and financial crises develop, to how search engines utilize the html links between websites for ranking pages in a Web search. The huge amounts of data in applications today mean that efficient algorithms must be used.

The course will be taught jointly by the Departments of Informatics and Information Sciences.

Learning Outcomes

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

After completing the course the student should be able to:

  • demonstrate knowledge of theoretical models, concepts and results related to modeling and analysis of social networks.
  • Reproduce, explain and demonstrate the most important mathematical models of social networks and social interaction.
  • reproduce and explain the most important scientific results related to modeling of social networks.
  • utilize different theoretical tools to analyze social networks.
  • select between mathematical models apt to create an abstraction for a given type of phenomenon in a given social network.

Required Previous Knowledge


Recommended Previous Knowledge

INFO102 or MNF130 or equivalent.

Credit Reduction due to Course Overlap

INFO207 10 SP

Access to the Course

Access to the course requires admission to a programme of study at The Faculty of Mathematics and Natural Sciences

Teaching and learning methods

4 hours of lecture per week, and 2 hours of work in groups. 15 weeks.

Compulsory Assignments and Attendance

The course will have compulsory assignments. The assignments are valid two semesters: the semester when they are approved and the succeeding semester.

Forms of Assessment

3 hour written exam. Compulsory exercises may count towards the final grade.

Examination Support Material


Grading Scale

The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.

Assessment Semester

Examination both spring semester and autumn semester. In semesters without teaching the examination will be arranged at the beginning of the semester.

Reading List

The reading list will be available within June 1st for the autumn semester and December 1st for the spring semester

Course Evaluation

The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department.

Programme Committee

The Programme Committee is responsible for the content, structure and quality of the study programme and courses.

Course Coordinator

Course coordinator and administrative contact person can be found on Mitt UiB, or contact studieveileder@ii.uib.no

Course Administrator

The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.

Contact Information

This course is administered by the Department of Informatics.

Contact studieveileder@ii.uib.no

Exam information

  • For written exams, please note that the start time may change from 09:00 to 15:00 or vice versa until 14 days prior to the exam.

  • Type of assessment: Written examination

    23.02.2023, 09:00
    3 hours
    Withdrawal deadline
    Examination result announcement
    Examination system
    Digital exam