Çerez Bildirimi

Kişiselleştirilmiş içerik, ilgili reklamlar ve gelişmiş işlevlerle size daha iyi bir tarama deneyimi sunmak için çerezleri kullanıyoruz. Tümüne izin vererek, Çerez Bildirimi'ne göre çerez kullanımını kabul etmiş olursunuz. Tercihlerinizi dilediğiniz zaman Çerezleri Yönet ekranı üzerinden değiştirebilirsiniz.

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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

  • Meet the increasing national and international demand of social network analysis (SNA) in academic social research as well as commercial environment including market research, crime analysis and public health.
  • Contribute to the national and international need for theoretically informed and methodologically skilled researchers in SNA.
  • Train in the necessary skills to understand and contribute to future developments in social network research.
  • Provide advanced, systematic and critical knowledge of theoretical and methodological aspects of SNA in a vibrant and internationally leading research environment.
  • Offer a unique set of skills in data visualization and modelling techniques that are highly valuable in commercial and public sectors, with understanding of the implications for markets and policy.
  • Prepare students for PhD level research careers in academic life or as professionals in government, public and private sectors.

Teaching and learning

  • Face-to-face lectures
  • Workshops
  • Computer-assisted tutorials
  • Student-led presentations and debate
  • Independent study
  • Seminars

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.

Hangi bölümdeyim?

School of Social Sciences

Öğrenim seçenekleri

Full Time (1 yıl)

Okul ücreti
£22,000.00 (TRY 417,695) Yıllık
Bu ücret sabittir
Başlangıç tarihi

19 Eylül 2022

Yer

The University of Manchester

Oxford Road,

Manchester,

M13 9PL, England

Giriş koşulları

Uluslararası öğrenciler için

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. Applicants whose first language is not English should meet the following language requirements: IELTS Academic test score of 7 overall, including 7 in writing with no further component score below 6.5; TOEFL IBT 100 with 25 in writing and no further score below 22 in each section. TOEFL code for Manchester is 0757; Pearson Test of English (PTE) score of 76 overall, with 76 in writing and no further score below 70.

Seçtiğiniz bölüme bağlı olarak farklı IELTS koşulları olabilir.

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