Postgraduate Course: The use and evolution of digital data analysis and collection tools (PGSP11388)
Course Outline
| School | School of Social and Political Science |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | 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 theory and 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.
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 five main aims: (i) to review case studies and theoretical papers on the development and use of digital research; (ii) to provide students with knowledge about the existence of a number of data collection and analytics services and approaches developed in research environments and (iii) to provide students with tools to assess digital research approaches and findings, including issues of ethics and risk. (iv) understand emerging use of digital resources to engage stakeholders in research, and move beyond conventional expert analysis to interactive use of data by stakeholders. (v) organize the procurement of services to match the need of their organization.
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| 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 will also be considered in terms of the types of methods deployed, questions asked, and the way it is used.
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.
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)
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.
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.
Readings:
Ipeirotis, P. G. (2010a). Demographics of Mechanical Turk. working paper CeDER-10-01, New York University, Stern School of Business. http://hdl.handle.net/2451/29585
Harass Map, Egypt. http://harassmap.org/en/what-we-do/the-map/
Rebecca Chiao - HarassMap: Social Mapping Sexual Harament https://www.youtube.com/watch?v=hLq7fCUQANM
Swan, M. (2013). The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery. Big Data, 1(2), 8599. doi:10.1089/big.2012.0002
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2021/22, Available to all students (SV1)
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Quota: None |
| Course Start |
Block 5 (Sem 2) and beyond |
| Course Start Date |
06/06/2022 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
98 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Assessment: 2500-word Essay (100%)
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| Feedback |
The Essay is usually built on feedback from an ungraded presentation. Students will receive feedback on the Presentation in an online voice/video session, as to how to develop the essay. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Gain a critical and broad knowledge of how the digital age has created opportunities and challenges for research on topics with social value, and be able to critically evaluate existing and emerging techniques and data sources.
- Understand the methodological opportunities and limits of different resources when commissioning and using both qualitative and quantitative digital research.
- Gain critical and practical knowledge of 'open data' as a source of evidence, and be able to apply these to their own field of work.
- Understand and be able to commission or conduct research that is sensitive to ethical issues involved in digital social research across different research professions and institutions.
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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 (http://www.igi-global.com/book/readings-virtual-research-ethics/858)
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
http://www.ccsr.ac.uk/publications/Data_Horizons_Report.pdf
Hamadeh, N, Marko Rissanen, and Mizuki Yamanaka (World Bank) (2012), Crowd-sourced price data collection through mobile phones, NTTS 2013, http://www.cros-portal.eu/sites/default/files//NTTS2013fullPaper_82-v2.pdf
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), 767797.
Hsu Digital Ethnography Toward Augmented Empiricism: A New Methodological Framework Journal of Digital Humanities
Ipeirotis, P. G. (2010a). Demographics of Mechanical Turk. working paper CeDER-10-01, New York University, Stern School of Business. http://hdl.handle.net/2451/29585
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), 721723. 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 http://www.clementlevallois.net/download/datafloods_2013.pdf
Lupton D (2013) Digital Sociology, Routledge
Marres, N. (2012, April 6). The redistribution of methods: on intervention in digital social research, broadly conceived. Live Methods: Sociological Review Monographs. Wiley-Blackwell. Retrieved from http://eprints.gold.ac.uk/7773/1/Marres_redistribution_of_methods.pdf
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.
Neff, G. (2013). Why Big Data Wont Cure Us. Big Data, 1(3), 117 123. doi:10.1089/big.2013.0029
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 http://www.bps.org.uk/sites/default/files/documents/conducting_research_on_the_internet-guidelines_for_ethical_practice_in_psychological_research_online.pdf
Ethical Decision-Making and Internet Research Recommendations from the AoIR Ethics Working Committee (Version 2.0)
http://aoir.org/reports/ethics2.pdf
Gray, M. L. (2011). Anthropology as BIG DATA: Making the case for ethnography as a critical dimension in media and technology studies.http://research.microsoft.com/apps/video/default.aspx?id=155639
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr James Stewart
Tel: (0131 6)50 6392
Email: J.K.Stewart@ed.ac.uk |
Course secretary | Ms Maria Brichs
Tel: (0131 6)51 3205
Email: mbrichs@ed.ac.uk |
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