Module code: SOCM082

Module Overview

We live in an increasingly digital world, with many of the issues of interest to a social researcher reflected in ¿born digital¿ data. Students taking this module will explore an array of established and emerging approaches within social science that are making use of this digital data. The digital landscape is fast-evolving and requires responsible and resilient researchers, able to adapt to new circumstances and new tools and to think critically about what data represent. Students will be encouraged to take an exploratory approach, developing both skills in the use of currently available tools and the ability to adapt to emerging situations. These skills will be underpinned by a commitment to responsible use of digital data in the interests of robust social science, and students will be encouraged to develop sophisticated and imaginative understanding of potential ethical issues raised by digital data.

Module provider


Module Leader

HINE Christine (Sociology)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Overall student workload

Workshop Hours: 11

Independent Learning Hours: 106

Lecture Hours: 11

Guided Learning: 11

Captured Content: 11

Module Availability

Semester 2

Prerequisites / Co-requisites


Module content

Indicative content will include:

  • Forms and sources of “born digital” data

  • Ethical approaches to digital social science

  • Small and large-scale social media analysis

  • Online fieldwork (including virtual and augmented reality)

  • Social network analysis

  • Writing and reporting on digital social science

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework Digital Social Science Project 100

Alternative Assessment


Assessment Strategy

  The assessment strategy is designed to provide students with the opportunity to demonstrate that they have successfully met the learning outcomes of the module, specifically that they are able to make use of appropriate methods to explore social science research questions using “born digital” data.


  Thus, the summative assessment for this module consists of:

An individual project (4,000 words) making use of methods of digital social science to explore a topic of the student’s choosing.


  Formative assessment

Students will be given the opportunity to submit an outline of their proposed digital social science for formative feedback. Written feedback will be provided via SurreyLearn, focusing on the feasibility and appropriateness of the project and taking account of any ethical issues that may be raised. The aim of the formative feedback phase is to ensure that students have a viable study to develop for the final submission.



 Verbal feedback on class exercises and discussions will be offered. Students will receive written feedback on their formative and summative submissions via SurreyLearn. Feedback on the formative exercise will focus on developing a viable final submission. The focus of feedback on the summative assignment will be on identifying elements of good practice and areas for future development.

Module aims

  • Introduce students to diverse forms of ¿born digital¿ data
  • Foster students¿ understanding of the potential and challenges of digital data, including ethical dimensions of data scraping
  • Enable students to develop skills in a range of techniques applied to digital data, including big data analysis, online fieldwork and social network analysis
  • Enable students to develop skills in a range of techniques applied to digital data, including big data analysis, online fieldwork and social network analysis
  • Equip students to design, conduct and report on their own small-scale digital social science projects

Learning outcomes

Attributes Developed
001 Understand the diversity of forms of ¿born digital¿ data and their potential for social science research CK
002 Show appreciation of the ethical principles that underpin responsible use of digital data CK
003 Understand how to design a robust social research study that makes use of digital social science techniques CP
004 Make effective use of digital social science techniques in a small-scale social research project PT
005 Be able to report effectively on a study using digital social research techniques CT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

•           Encourage students to take an active approach to their learning, including contributing their own perspectives and experience in interactive classes and reflecting on their personal engagement in a digital world.

•           Allow students to acquire knowledge on key principles and methods that underpin digital social science and to work individually and collectively to apply them in their own research

•           Offer students access to an array of useful resources to underpin their research, including introduction to a range of data sources and software tools


The learning and teaching methods include lectures and workshops, which includes demonstrations; class discussion and hands-on practical experience with software that provides the underpinning for individual learning. Group discussion will explore the challenges and opportunities of digital social science and the interpretation of ethical principles. Students will be encouraged to develop their individual skills in extended learning tasks to be conducted in their independent study hours.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list
Upon accessing the reading list, please search for the module using the module code: SOCM082

Other information

The Department of Sociology is committed to developing graduates with strengths in digital capabilities, employability, global and cultural capabilities, resourcefulness and resilience and sustainability. The MSc programme in Social Research specifically develops these strengths with a view to preparing graduates for careers in social research. The social world is increasingly mediated through digital technologies, and the contemporary social researcher is faced with an array of “born digital” data. This module aims to develop students’ ability to engage with this digital landscape with the skills and understandings to carry out robust social research using digital data. In particular, it supports students to develop in the following key areas.


Digital capabilities. This module supports students to identify and confidently use the appropriate software for research into digital data and to assess the benefits and challenges that different approaches bring.


Employability. The module aims to develop skills that are highly significant in the workplace for a social researcher, with a view to developing research that engages with an increasingly digital social world.


Global and cultural capabilities. The digital landscape is cross-cut by global and cultural diversity and multiple forms of inequality. Students will be encouraged to reflect on the social and cultural complexity of the digital landscape and to reflect on their own positioning within it, enabling them to act responsibly in relation to inequalities.


Resourcefulness and resilience. The digital landscape is ever-changing, and social researchers have to be responsive to the challenges and opportunities of new forms of data and new tools. Students are encouraged to see themselves as engaged in a process of continual development of their skills and as needing to keep abreast of emerging developments.


Sustainability. Multiple sustainability issues arise in virtue of digital technologies and are reflected in the digital landscape as are various forms of social action taken in the interests of sustainabilty. This module will equip students to explore sustainability issues as they are reflected in the digital landscape.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Social Research MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.