Postgraduate Course: Social Shaping of Digital Research (PGSP11445)
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 | Please note that this course is only available to students of the Data Science, Technology and Innovation (DSTI) online distance learning programme
Between data collection technologies and professional users of digital research data lies a massive assembly of computational and analytical resources that together constitute information infrastructure and promise to revolutionize analytical practice. This course provides an understanding of the possible outcomes of the adoption of digital research in business & policy-making, based on evidence gathered from other disciplines that have been early adopters of eScience as well as other fields whose practices have been modified by engagement with information infrastructure. In particular, the course will provide a theoretical framework for understanding the functioning of the 'human infrastructure' (e.g. technicians and scientific users) that is required to sustain digital research tools and methods. By analyzing the building of information infrastructure as a process that involves the alignment and realignment of people, processes, and tools, the course will provide an understanding of information infrastructure as it appears from the perspective of those who are creating and using it. |
| Course description |
Week 1 - The Social Shaping of technology
The social shaping of technology (MacKenzie & Wajckman, 1985) has become a broad umbrella term to cover a variety of theoretical and methodological perspectives in the social sciences. Scholars have sought to clarify and apply this concept to the study of any number of information and communication technologies (e.g., see Williams and Edge 1996). It has also defined a set of funded projects in the UK focused on a particular technical initiative around e-social science digital social research. Based on recent work on the social shaping of digital research (Dutton, 2012), this first week we will clarify how the social sciences, generally, and the social shaping of technology, more specifically, can be applied to the study of digital research.
Week 2 - The implications of digital research for social science
This week presents a critical account of social media data narrative (Boyd & Crawford, 2011) and in particular of the claim that big data displaces traditional social science methods and theories (Marres, 2012). We will highlights potential flaws in social media derived data compared to data derived from existing social science research techniques (e.g. surveys). We will focus in particular on recent interpretive understanding of digital methods, occurring under the name of 'Social Life of Methods' (Ruppert, Law & Savage, 2013) which focuses on how digital devices are shaped by social worlds and in turn shape them. We will also present an overview of critical works in digital sociology (Orton-Johnson & Prior, 2013; Lupton, 2015).
Week 3 - Social Learning and the adoption of e-research tools
Sharing research resources of different kinds, in new ways, and on an increasing scale, is a central element of the unfolding e-Research vision (Procter et a., 2010). Web 2.0 is seen as providing the technical platform to enable these new forms of scholarly communications. In this week we report findings from a study of the use of Web 2.0 services by UK researchers and their use in novel forms of scholarly communication. We document the contours of adoption, the barriers and enablers, and the dynamics of innovation in Web services and scholarly practices.
Reflective discussion topic: Comment the steps suggested by the authors that different stakeholders might take to encourage greater experimentation and uptake of e-research tools.
Week 4 - Politics of Platforms: why social media data is not neutral
In this week we will propose a view of social media data through the lens of 'platform politics' (Gillespie, 2010), focusing in particular on controversies around user data access, ownership, and control. Originally developed by the author to understand how online content providers such as YouTube are positioning themselves to various stakeholders as 'neutral' curators of the public discourse, the approach has been extended to Twitter data (Puschmann & Burgess, 2013) to highlight social media platforms¿ often conflicting interests.
Week 5 - PageRank, EdgeRank: a sociology of the algorithm
The final week addresses the functioning of the algorithms used by major online platform owners and how they condition our everyday access to information. We will develop a further argument contrasting the assumption of digital social media neutrality inculcated and shaped by the ongoing engagement with online search practices. We will do so by discussing the partial conception encoded algorithmically by engineers that relevance is the defining feature of knowledge. We will also discuss evidence that contrasts the search industry view that everything that matters is now on the web.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Only available to students of Data Science, Technology and Innovation online distance learning programme |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- assess evidence deriving from monitoring digitally derived internet data, recognizing its strengths and limitations in comparison to other ways of apprehending user needs;
- understand the work-practices of information professionals in digital research;
- critically discuss the current context and the future evolution of digital research;
- appreciate the practical benefits and limitations of digital data for organizational decision-making;
- assess the relevance and value of projects at the forefront of digital research
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Reading List
boyd danah and Crawford K (2011) Six Provocations for Big Data. SSRN eLibrary, Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1926431
Gillespie, T. (2008) The politics of 'platforms'. New Media & Society May 2010 vol. 12 no. 3 347-364.
Hillis, Ken, Michael Petit, and Kyle Jarrett. 2013. Google and the Culture of Search. New York, Routledge. (Chapter 2: Google Rules)
Lupton, D. (2015) Digital Sociology, Routlegde.
MacKenzie, D. (2014) A Sociology of Algoritms: High-Frequency Trading and the Shaping of Markets. First Draft February 2014, Available from: http://www.sciencespo.fr/master-public-affairs/content/sociology-algorithms
Noortje Marres (2012), 'The redistribution of methods: on intervention in digital social research, broadly conceived', The Sociological Review, pp. 139- 165.
Orton-Johnson, K. and Prior, N. (eds) (2013) Digital Sociology: Critical Perspectives. Houndmills: Palgrave Macmillan.
Procter, R., Williams, R., Stewart, J., Poschen, M., Snee, H., Voss, A. & Asgari-Targhi, M. (2010), 'Adoption and use of Web 2.0 in scholarly Communications' Philosophical Transactions of the Royal Society Series A vol. 368 no. 1926 pp. 4039-4056.
Evelyn Ruppert, John Law and Mike Savage (2013) Reassembling Social Science Methods: The Challenge of Digital Devices, Theory Culture Society, DOI: 10.1177/0263276413484941
James Stewart, Rob Procter, Robin Williams and Meik Poschen (2012) 'The role of academic publishers in shaping the development of Web 2.0 services for scholarly communication', New Media and Society, DOI: 10.1177/1461444812465141.
Weblinks:
Workshop organised by the Oxford e-Social Science Project
Social Science and Digital Research: Interdisciplinary Insights:
http://www.oii.ox.ac.uk/events/?id=486
http://www.whatisedgerank.com/
http://culturedigitally.org/tag/sociology-of-algorithms/
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Special Arrangements |
Enrolment is restricted to students on the Online Distance Learning Data Science Programme. |
| Keywords | Not entered |
Contacts
| Course organiser | Prof Robin Williams
Tel: (0131 6)50 6387
Email: |
Course secretary | Mr Jason Andreas
Tel: (0131 6)50 3937
Email: |
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