Timetable information in the Course Catalogue may be subject to change.

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Social and Political Science : Postgrad (School of Social and Political Studies)

Postgraduate Course: The Use and Evolution of Digital Data Analysis and Collection Tools (PGSP11443)

Course Outline
SchoolSchool of Social and Political Science CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate)
Course typeOnline Distance Learning AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryPlease note that this course is only available to students of the Data Science, Technology and Innovation (DSTI) online distance learning programme

Research techniques and methods have been developed and deployed to explore 'digital life' since the earliest days of computing and online communication. In this course we will address the opportunities and challenges of a range of traditional and emerging digital research approaches and techniques focusing on the relevance of their applications from a user perspective. It will cover ethical, practical, legal, methodological and economic issues in practice. The students will explore practice and knowledge in the field of research on email use, forums, SMS; internet use derived data sets; use of web analytics in engaging with consumers and citizens; opportunities and challenges of clickstream data & scraping data from internet services ; use of crowdsourcing for data collection, analysis and stakeholder engagement; use of behavioural data from IT systems, such as smart meters, GPS etc; using digital games and simulations to engage decision makers, customers and citizens, and in research on behaviour; deriving indicators from and the use of open administrative data in Policy Making 2.0.
By reviewing a number of existing projects at the forefront of digital research, the student will develop skills to assess the relevance of digital research. By learning from how advanced digital research tools have been applied to inform practice in a number of different domains, the student will be able to anticipate further developments in the field. This course has three main aims: (i) to review case studies from experimental digital research projects; (ii) to provide students with knowledge about the existence of a number of data collection and analytics services developed in research environments and (iii) to provide students with tools to assess digital research approaches and findings, including issues of ethics and risk.
Course description Week 1 - Digital Research for the Digital Age
This week introduces the field 'Digital Research', and will help students gain a broad vision of digital research methods, and questions. In recent years digitally-derived data, and in particular 'big data' and 'social media' have has come to dominate the conception of digital research, but digital research can be considered more broadly to include not only 'data', but the study of new digital social practices, institutions, relationships. Digital research can also be considered in terms of the types of methods deployed, questions asked, and the
What can be considered digital research? Is it the source of the data, the analysis methods, the management of research, the review process, the presentation and dissemination process?

Study Session 1 - Research methods in the digital age

This session will focus understanding the types of approaches that are being developed for 'digital research', and the different professional groups that are developing them. Marres (2012) discusses the way that digital research has been conceptualised by research professionals as something 'new' demanding 'new' methods, or as merely the extension of the existing world, therefore requiring new fundamental change in practice.
While the development computational data methods and availability of more and richer and larger data sets has raised the profile and confidence of 'data scientists', some social scientists, especially sociologists, are losing faith in the primacy and power of their tools, especially theory driven research (Savage & Burrows, 2007). What are the claims of the new data scientists, and what is the response of professionals in social science (Levallois, et al 2013; Elliot et al 2013 ; Lazer et al 2009) to the claim that 'With enough data, the numbers speak for themselves.' (Chris Anderson (2008).

Study Session 2 - Group assignment on Research methods in the digital age

In this session students will work together to identify the key elements of 'new digital research' .In discussion, they will draw on previous readings and experience to suggest different types of digital research, and identify the key dimensions. The aim will be drawing up a taxonomy of types of digital research, identifying important dimension such as:
New Contexts
New Data
New Capabilities
New Methods
New Practices
New Uses

Students will then work together in small groups to prepare a debate on 'Is digital social research really new?'

Week 2 - Internet research
Research on computer mediated communications has a long history, drawing on studies of telephony in the 1970s, through bulletin boards, email, online communities, and online games (MMOPRGs) through the subsequent decades. The Association of Internet Researchers was founded in 2000 as this research became mainstream, and many research disciplines have incorporated digital research into their activities. This week will make students aware of some of the history of research in these digital domains.

Study Session 1 - Simple Social Digital environments
This session looks at research on behaviour and community through traces left in common digital communication systems, For example:
1. Research on and using email
2. Research on bulletin boards and online groups
3. Research on social media sites

Three example cases of research using these resources will be discussed, demonstrating the breath of research questions, and types of challenges (e.g. (e.g. Howison, 2011).

Study Session 2 Ethics and Legality of Internet Research
Research online brings similar ethical challenges as offline research, but certain issues can be magnified. For example, when is Twitter data really 'public' Zimmer, M. (2010)., what should be the ethic research standards of academics compared to commercial firms? This session will use the ethics documents of the British Psychological Society and the Association of Internet researchers as the starting point to understand how different types of research present ethical challenges, and the types of care research thus need to take in commissioning or design research.

Week 3 - Digital Ethnography

This week explores qualitative research practice in complex immersive digital environments most clearly represented by online gaming, and in the digital world where all human interactions now include a digital component. In contrast to 'data'driven approaches, ethnography immerses the researcher in the everyday world it is studying to build a rich picture of relationships and meanings that can never be captured by other quantitative or simpler qualitative methods. The internet has opened new challenges, but also new opportunities to ethnographers and anthropologists (Gacia et al 2009; Miller and Horst (eds) 2012; Miller and Slater 2000)

Study Session 1
This session will allow students to explore 2 examples of online ethnography, one within an online game environment, and other in a mix online-offline situation.

Study Session 2 - Adding Data to ethnography
While ethnographers can build up detailed pictures of communities and practices, there is much that cannot be seen or recorded using conventional techniques. This session explores how digital data capture can be used to develop richer ethnographies, using both remote monitoring, and active media production by participants, such as video diaries.

Includes a video lecture by an invited speaker.

Week 4 - Online surveys and clickstream data
This week introduces students to two uses of the internet for research. First, it looks at the conventional survey work, and to the internet as a tool for conducting representative surveys. Secondly it introduces a number of uses of 'Web Analytics' including clickstream analysis, in particular how these standard tools in commerce can be applied in policy research.

Session 1 Online surveys and internet Panels
Face to face and telephone surveys are being increasingly replaced by online surveys. This session will feature two short video presentations, by Francisco Lupiañez, describing his research on 'Citizens and ICT for Health in 14 EU countries', and Rosa Dalet, the Managing Director of Block de Ideas, a research firm that offers a wide range of research services, including European panels. Discussed will be: What are the benefits and limitations of Internet panel surveys? How reliable are they. What populations cannot be studied using this technique?

Session 2 Web Analytics, Clickstream and web logs
The traces of online behaviour of internet users has proved a gold mine for e-commerce, as complex Web Analytic tools are deployed to track the online behaviours of customers, not only on an ecommerce website, but as they leave a data trail in their online activities that is tracked and sold to business to help improve their marketing, sales and service design. This session will provide a basic introduction to this tools as they are used in operations. However, this is not the only example of use. The 'clickstream data' of thousands of members of Internet Panels is also monitored by firms such as Neilsen. This data can also be used in policy research. This session will include a short video from Bertin Martens (JRC) on the use of Nielsen clickstream data to explore the online music download practices of European citizens to help inform policy on copyright protection.

Week 5 - Crowdsourcing
This session will introduce the topic of crowdsourcing as a means for collecting data, engaging a community and doing analysis. First it will address the development of the crowdsourcing generally, and then address how it is used in various sorts of commercial and academic research.

Session 1 - What is Crowdsourcing?
Crowdsourcing of data, ideas, and action has become a staple concept and practice in the digital society, and is slowly making its way in to various types of research. Crowdsourcing (Howe 2008). ) brings together ideas from biology (Bollen and Heylighen 1996), and information science (Levy P, 2010; (Brin and Page, 1998) of collective intelligence from, and of human computing (Van Ahn, 2004) and has been popularized with the concept of the 'Wisdom of the crowds'(Surowiecki 2004. The concept of crowdsourcing has been retrospectively applied to 'peer' production processes that have created Wikipedia and other social computing projects.
Researchers and those wishing to exploit data sources have turned to crowdsourcing to collect data, and to analyse data. Ipeirotis (2010) and Ipeirotis & Paritosh (2011) are among those who have addressed the challenges of turning tools such as Amazon Mechanical Turk into resources for researchers. Business such as Clickworker provide platforms for business to collect data from the real world, and do data cleaning and classification.

Session 2
This session will concentrate on a number of different cases of research through crowdsourcing. Citizen Science ( e.g. Silvertown, 2009) and citizen social science (Purdam, 2014) represent some of the ways that academic researchers are using crowdsourcing methods to collect and process data. Public sector economists are also using the crowdsourcing tools of business to collect data such as market prices in developing economies in order to better understand and model these economies (Hamadeh, 2012). However, more action research oriented are being taken ¿ such as the Harassmap, used to collect data on sexual harassment from women in Cairo, as the basis for public and political campaigning. While much crowdsourcing is designed centrally, there are other movements that emerge from the ¿bottom up¿. A case is the ¿Quantified self¿ Movement (Swan 2013; Neff 2014)
Students will chose a case to focus on, and present the case, its methodological challenges, and the results in a Virtual classroom.

Reflective Discussion Topic - design a crowdsourcing research project for your industry
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements Please note that this course is only available to students of the Data Science, Technology and Innovation (DSTI) online distance learning programme
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. - identify ethical issues facing research on the 'digital society' and in the deployment of digital research methods, with reference to academic and professional guidelines.
  2. - understand the conceptual ideas and approaches behind open data and big data- and critically engage with the claims of those promoting and developing these approaches.
  3. - be prepared to initiate or participate in open data projects, understanding the barriers to open data, and pathways to innovation via open data.
  4. -compare and assess potential of a range of emerging digital research techniques such as crowdsourcing, citizen science, mobile research, and games, including their value in public engagement, and critically assess their potential in commissioning or deploying these to meet organisational needs.
Reading List
Bowker Geoffrey C. and Star Susan (2001) Sorting Things Out. Publication Info: Ann Arbor, MI: MPublishing, University of Michigan Library April 2001

Buchanan E (ed) (2004) Readings in Virtual Research Ethics: Issues and Controversies. IGI (

Elliot, M, K Purdam, E Mackey (2013) Data Horizons. New Forms of Data For Social Research, University of Manchester, CCSR Report 2013-3 12/6/2013

Neff, G. (2013). Why Big Data Won¿t Cure Us. Big Data, 1(3), 117¿123. doi:10.1089/big.2013.0029

Hamadeh, N, Marko Rissanen, and Mizuki Yamanaka (World Bank) (2012), Crowd-sourced price data collection through mobile phones, NTTS 2013,

Howison, J. (2011). Validity Issues in the Use of Social Network Analysis with Digital Trace Data. Journal of the Association for Information Systems, 12(12), 767¿-797.

Ipeirotis, P. G. (2010a). Demographics of Mechanical Turk. working paper CeDER-10-01, New York University, Stern School of Business.

Ipeirotis, P. G., & Paritosh, P. K. (2011). Managing crowdsourced human computation. In Proceedings of the 20th international conference companion on World wide web - WWW 11 (p. 287). New York, New York, USA: ACM Press. doi:10.1145/1963192.1963314

Lazer, D., Brewer, D., Christakis, N., Fowler, J., & King, G. (2009). Life in the network: the coming age of computational social science. Science, 323(5915), 721-723. doi:10.1126/science.1167742.Life

Levallois, Clement ,Stephanie Steinmetz, Paul Wouters (2013) Sloppy Data Floods or Precise Social Science Methodologies?. In Paul Wouters, Anne Beaulieu, Andrea Scharnhorst and Sally Wyatt (2013) Virtual Knowledge. Experimenting in the Humanities and the Social Sciences, MIT Press

Lupton D (2013) Digital Sociology, Routledge

Marres, N. (2012). The redistribution of methods: on intervention in digital social research, broadly conceived. Live Methods: Sociological Review Monographs. Wiley-Blackwell. Retrieved from

Miller, D . Slater D (2000) The Internet: An Ethnographic Approach. Oxford:Berg.

Miller, D . (2011) Tales from Facebook. Cambridge: Polity.

Miller, D and Horst H (eds) (2012) Digital Anthropology. Oxford: Berg.

Purdam, K. (2014). Citizen social science and citizen data? Methodological and ethical challenges for social research. Current Sociology, 62(3), 374-392. doi:10.1177/0011392114527997

Rogers, R. (2013). Digital methods. Cambridge, Massachusetts; London: The MIT Press.

Savage, M., & Burrows, R. (2007). The Coming Crisis of Empirical Sociology. Sociology, 41(5), 885-899. doi:10.1177/0038038507080443

Silvertown, J. (2009). A new dawn for citizen science. Trends in Ecology & Evolution, 24(9), 467-71. doi:10.1016/j.tree.2009.03.017

Stewart, J (2014) From Crowd to Cloud: Online work exchanges for freelancing and 'crowdsourced' labour JRC Scientific and Policy Report (Forthcoming)

Swan, M. (2013). The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery. Big Data, 1(2), 85-99. doi:10.1089/big.2012.0002

Von Ahn, L., & Dabbish, L. (2004). Labeling images with a computer game. In Proceedings of the 2004 conference on Human factors in computing systems - CHI '04 (pp. 319¿326). New York, New York, USA: ACM Press. doi:10.1145/985692.985733

Zimmer, M. (2010). But the data is already public: On the ethics of research in Facebook. Ethics & Information Technology, 12(4), 313-325.

Report of the Working Party on Conducting Research on the Internet: Guidelines for ethical practice in psychological research online, British Psychological Society , 2007

Ethical Decision-Making and Internet Research Recommendations from the AoIR Ethics Working Committee (Version 2.0)


Avinash Kaushik Blog on Web analytics

Crowd-Sourced Price Collection, World Bank

Digital Social Research Programme (UK)

Commercial panel organisations:

Appleton: Can Online Qualitative Research Be Potentially Misleading?

Steve August: Going Deeper with Online Qual

Harass Map, Egypt.
Rebecca Chiao - HarassMap: Social Mapping Sexual Harament
Additional Information
Graduate Attributes and Skills Not entered
Special Arrangements Enrolment is restricted to students on the Online Distance Learning Data Science Programme only.
KeywordsNot entered
Course organiserDr James Stewart
Tel: (0131 6)50 6392
Course secretaryMr Jason Andreas
Tel: (0131 6)51 3969
Help & Information
Search DPTs and Courses
Degree Programmes
Browse DPTs
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Important Information