MSc Social Network Analysis

Year of entry: 2023

Overview

Degree awarded
Master of Science
Duration
1 year (full-time); 2 years (part-time)
Entry requirements

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.

Full entry requirements

How to apply
Apply online

Course options

Full-time Part-time Full-time distance learning Part-time distance learning
MSc Y N N N

Course overview

The programme 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.

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Study MSc Social Network Analysis at The University of Manchester

Open days

The University holds regular open days, where you will have the opportunity to find out more about our facilities and courses.

See  open days  for more information.

Social Network Analysis Virtual Masterclass

  • Wednesday 10 May 2023
  • 3pm - 4pm 

On 110 May 2023 we will be hosting a virtual masterclass to introduce prospective students to social network analysis. The session will give you a taste of what you can learn on the programme, together with an overview of the prospective career opportunities after graduation.  

To register for this session please complete our short registration form .

Fees

For entry in the academic year beginning September 2023, the tuition fees are as follows:

  • MSc (full-time)
    UK students (per annum): £11,000
    International, including EU, students (per annum): £23,500

Further information for EU students can be found on our dedicated EU page.

Policy on additional costs

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

Contact details

School/Faculty
School of Social Sciences
Telephone
School/Faculty

Courses in related subject areas

Use the links below to view lists of courses in related subject areas.

Entry requirements

Academic entry qualification overview

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.

English language

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

You are not required to submit an English language certificate at the time of application, however if you are eligible for an offer it will be subject to meeting our English language requirements.

Pre-Sessional English Courses

We will consider applicants who do not meet these scores but you may be required to complete a pre-sessional English language course at the University of Manchester prior to the start of the course.

To be considered for a pre-sessional English language course for this programme we require the following minimum IELTS (Academic) scores:

6 Week Pre-Sessional Course  : IELTS 6.5 overall with 6.5 in writing and no more than one sub-skill of 6.0.

10 Week Pre-sessional Course  : IELTS 6.0 overall with 6.0 or above in each sub-skill 

If you have not yet completed your current academic study and are interested in studying a pre-sessional course, you must hold an IELTS for UKVI (Academic) test certificate to ensure that you are eligible for a separate visa for the English language course.

English language test validity

Some English Language test results are only valid for two years. Your English Language test report must be valid on the start date of the course.

Applicants from Majority English-speaking countries

If you are a national of a majority English-speaking country    (or have studied for a full bachelor's degree or higher from one of these countries) you may be exempt from submitting further evidence of English language proficiency.

Application and selection

How to apply

Advice to applicants

Application deadline:  31st July 2023

Please note, due to the high volume of applications we receive the course may close before the advertised deadline and as such, early application is advised.

If you meet our entry requirements but we are unable to make you an offer you may be placed on a waiting list. Candidates on a waiting list will receive an offer only if places become available.

Students who fail to fulfil the requirements to pass the 180 credits necessary to attain the final degree of MSc can leave the course with the award of PGDip by passing 120 credits at the pass mark of 40%, or can qualify for the PGCert by passing 60 credits at the pass mark of 40%.

Students who do not fulfil the criteria for passing the taught element of the course at the master's level of 50% will not be permitted to progress to the dissertation element of the course, and will leave the course with the highest award that the credits that have been passed will allow.

University Regulations regarding re-sit, referral and compensation will apply within this course.

Course details

Course description

The programme aims to offer a unique comprehensive training in social network analysis (SNA) covering theoretical foundations, research design, data collection techniques, methods for the analysis and visualization of network data, and statistical modelling of networks. At the end of the programme the students will be able to:

  • Design research projects using SNA in a variety of applicative areas.
  • Critically engage with the theoretical foundations of SNA and use them to formulate robust and coherent SNA empirical questions.
  • Collect social network data in online and offline contexts, selecting the right data collection tools and assessing the validity and reliability of the data collection.
  • Apply a wide range of analytical techniques to social network data.
  • Statistically model the mechanisms for social network formation and evolution.
  • Develop network studies and intervention that can be used in private and public sectors.
  • Write social network analysis academic reports

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

Coursework and assessment

A student's year is divided into two study periods: October - December and February - April.

During each of these periods, students sit 60 credits.  

Assessments are due after the teaching period, and the Dissertation component is due in September of the following year. 

Assessment is normally by a 3,000-word assessed essay or a computer-based coursework for each unit, and a dissertation of between 12,000 and 15,000 words.

Course unit details

You will take five compulsory units: 

  • SOCY60361 Social network analysis: concepts and measures 
  • SOCY60631 Theories of social relations, networks, and social structure 
  • SOCY60292 Doing research with social network data and visualizations 
  • SOST71032 Network modelling. 
  • CRIM70821 Data Analysis with R & RStudio. 

You will also take 3 optional modules. Optional modules will give students the possibility of continuing the specialization in SNA (Mitchell centre seminar series, independent study), or extending the interdisciplinary training to other social sciences substantive areas. You will be able to choose from the wider list of modules offered in the MA sociology, Msc social research, and Msc social research methods and statistics. Choices from other SoSS master modules will be available upon discussion with the Programme director.

Examples of optional modules are: 

  • SOCY60360 Mitchell Centre seminar series 
  • SOST70151 Statistical Foundations 
  • SOCY60142 Protest and Progress: Understanding Movements for Social and Political Change 
  • QRM, Qualitative research methods venue

You may also negotiate an independent studies course unit, linked to your particular research interests, subject to a suitable academic supervisor being available. If you have registered for the MA (or upgraded from the PG Diploma), you will need to complete a 12,000-word dissertation, on a social network research topic of your choice, in addition to the eight taught course units.

Course unit list

The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.

TitleCodeCredit ratingMandatory/optional
Data Analysis with R & RStudio CRIM70821 15 Mandatory
Doing research with social network data and visualizations SOCY60292 15 Mandatory
Social network analysis: concepts and measures SOCY60361 15 Mandatory
Theories of social relations, networks, and social structure SOCY60631 15 Mandatory
Statistical Models for Social Networks SOST71032 15 Mandatory
Protest and Progress: Understanding Movements for Social and Political Change SOCY60142 15 Optional
Mitchell Centre seminar series SOCY60360 15 Optional
Independent Studies I SOCY60531 15 Optional
Independent Studies II SOCY60592 15 Optional
Statistical Foundations SOST70151 15 Optional

What our students say

Our students share their experiences of studying Sociology at The University of Manchester in Student Spotlights .

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: dass@manchester.ac.uk

Careers

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 organisational 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. 

The University also has its own dedicated Careers Service that you would have full access to as a student and for two years after you graduate. At Manchester you will have access to a number of opportunities to help boost your employability.