Full time
1 year
23-SEP-24
MSc - Master of Science
Network Analysis Using The World Wide Web
Taught
Course description
The course offers a comprehensive training in social network analysis, covering theories, methods and applications of social networks in social sciences.
Students will learn the theoretical foundations of social network analysis, the constitutive elements of research design, techniques for data collection, advance methods for social network data analysis and visualization, statistical modelling of social networks and mixed methods.
The learning environment will include face to face lectures, computer assisted workshops, and applications of social network theories and methods to a variety of substantive fields in social sciences.
With an interdisciplinary combination of lecturers from the Mitchell Centre for Social Network Analysis , who specialise in mathematics, social statistics, sociology and criminology, the teaching team will guide and supervise students in all the aspects related to social network research.
Areas of applications include (but are not limited to) online networks, criminal networks, health network, cultural networks, scientific networks, migration networks and academic networks.
Aims
Teaching and learning
Career opportunities
This degree is designed to ensure highly numerate, research-oriented and employable graduates, and will provide you with the skills necessary for roles within:
academia;
government departments;
research institutes;
commercial research.
Our graduates can find career opportunities as consultants or analysts in organizational development to help companies optimise their work structure; as data scientists with specialised skills in network analysis in areas like social media analytics; and as data scientists/data analysts in governmental agencies like the Home Office and Trading Standards.
For this course (per year)
£13,000
For this course (per year)
£24,500
A bachelor degree with honours (minimum 2:1 or international equivalent) in social sciences, mathematics, physics, computer sciences, or the overseas equivalent. The entry requirements are intentionally kept open as SNA is an interdisciplinary approach that attracts scholars from both humanities and natural sciences.