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 Humanities and Social Science |
| 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), 85¿99. 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 2016/17, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
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 1 (20%) Group assessment
Assessment 2 (30%) Group assessment
Assessment 3 (50%) Individual Project
The first Group assessment is at the end of week one. The second Group assessment is in the middle of Week 3,. Students are expected to work in small teams of two or three. Maximum flexibility is allowed when it comes to the format of the submission. It can take the form of a presentation, a wiki page or an exercise done using data analysis tools introduced during the tutorial. The second assignment will involve a synchronous online debate. The final assessment consists in a 1.500 words essay to be submitted two weeks after the end of the course. The student should confirm the essay topic in consultation with the course convener.
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| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Knowledge and Understanding:
The students will gain a critical and broad knowledge of how the digital age has created opportunities and challenges for social research that has been conducted in the past and is being developed today.
Learn basic understanding of the conceptual ideas and approach behind ¿open data¿, ¿big data¿.
Understand the methodological opportunities and limits of different resources approaches when commissioning and using both qualitative and quantitative digital research.
- Students will understand how to choose relevant research approaches to tackle different research questions, and understand different challenges.
Students will gain knowledge of the state of the art and practice in the digital research, and the limitations and challenges that face those conducting and commissioning digital research.
The students will learn to plan a research project using digital research techniques
Students will understand how to engage with data science professionals, and key aspects of setting up open data projects.
Learn how to
- Students will extend their critical skills and thinking through engagement with research texts
Students will develop ability to communicate with their peers through the group assignments and discussions
Students will gain skills in critical evaluation of research methods used to generate digital research.
Students will gain practical Skills to access Digital Research services.
- Autonomy and Working with Others
Students will develop skills in autonomously finding information, and critically engaging with both academic research and with sources from practice.
Students will develop skills of online group work, and, especially how to bring together evidence and examples to develop common frameworks and understanding.
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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), 767¿797.
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), 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 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 Won¿t 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 Nicole Develing-Bogdan
Tel: (0131 6)51 5067
Email: v1ndeve2@exseed.ed.ac.uk |
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