Level of Study
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.
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.
Due to the measures taken to avoid the spread of Covid-19, UiB is closed for on-campus assessment. As a consequence, the following changes is made to assessment autumn semester 2020:
- Written home examination instead of written examination
Examination Support Material
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
Examination both spring semester and autumn semester. In semesters without teaching the examination will be arranged at the beginning of the semester.
The reading list will be available within June 1st for the autumn semester and December 1st for the spring semester
The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department.
The Programme Committee is responsible for the content, structure and quality of the study programme and courses.
Course coordinator and administrative contact person can be found on Mitt UiB, or contact Student adviser
The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.
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
- 18.02.2021, 09:00
- 3 hours
- Withdrawal deadline
- Examination result announcement
- Examination system
- Digital exam