MG486 Half Unit
Social Computing, Data and Information Service
This information is for the 2018/19 session.
Prof Jannis Kallinikos NAB 3.24
This course is available on the CEMS Exchange, Global MSc in Management, Global MSc in Management (CEMS MiM), Global MSc in Management (MBA Exchange), MBA Exchange, MRes/PhD in Management (Information Systems and Innovation), MSc in Management (1 Year Programme), MSc in Management of Information Systems and Digital Innovation and MSc in Media and Communications (Data and Society). This course is available with permission as an outside option to students on other programmes where regulations permit.
The course is about the growing importance ordinary users assume in spinning the fabric of the Web and supporting the operations of social media platforms and networks. This social transformation of the Web that is often referred to as social computing is closely associated with the diffusion of potent lightweight technologies such as smart phones, tablet computers and wearables and the continuing development of advanced interactive software applications. It is also linked to architectural and other software-based innovations that help construct interoperable information systems and infrastructures. Taken together, these trends set the stage for the transition from a transaction-based Web (e.g. buying items) to a Web in which online interaction, talk and communication become the backbone activities for the production of data and the generation of economic value.
In this context, social media platforms emerge as key entities that mark the social transformation of the Web and the production of services that accommodate a great deal of stakeholders, such as platform owners, platform users and third parties such as advertisers and digital analytics companies. The course deals with the ways by which social media platforms operate as data platforms by analysing the ways by which they engineer user participation to produce a computable data footprint that is subsequently used to develop a range of data-based resources and services. The course also shows how social media deploy personalization strategies and how personalization is inherently connected to big data and, more particularly, social data. The course takes a unique approach to social media by examining the data-work they perform and the innovative economic practices they promote. Social media powered networks, platforms, and infrastructures are at the heart of today’s digital economy.
The course blends theories, ongoing research insights and real-life examples to analyse the social and economic implications of these significant developments.
• Explain the drives behind social computing
• Describe the technological developments and the architectural principles that govern social computing and the growing involvement of lay publics in the Web
• Link data-based practices with social systems and the digital economy
• Explain how social media platforms operate as business organisations
• Understand information infrastructures and the role they play in sustaining social media platforms and the digital economy
• Describe social media as important actors in the digital economy
• Understand personalization strategies and their implications
• Acquire critical awareness of social data and big data
20 hours of lectures and 9 hours of seminars in the LT.
There is a Reading Week in Week 6. There will be no teaching during this week.
Classes are based around reading and discussing selected journal articles and case studies from the course reading list.
Written formative feedback is provided on the 500 words proposal for the summative essay.
1. Alaimo, C. and Kallinikos, J. (2016). “Encoding the everyday: Social data and its media apparatus”, in Big data is not a monolith: Policies, practices, and problems, Sugimoto, C, Ekbia, H. and Mattioli M. (eds.) Cambridge, MA: The MIT Press, pp. 77-90.
2. Alaimo C. and Kallinikos J., (2017). Computing the everyday, The Information Society 33/4: 175-191.
3. Brynjolfsson, E. and McAffee, A. (2014). The second machine age. New York: Norton.
4. Constantiou, I. and Kallinikos, J. (2015). New games, new rules: Big data and the changing context of strategy. Journal of Information Technology, 30 (1): 44-57.
5. Kitchin, R (2014). The data revolution: Big data, open data, data infrastructures and their consequences. London: Sage.
6. Konstan, J and Riedl, J. (2012) Recommended for you. Spectrum, IEEE, 49(10), 54-61.
7. Parker, G, G, Van Alstyne, M. and Choudary, S. P. (2016). Platform revolution. London: Norton.
8. van Dijck, J. (2013). The culture of connectivity: A critical history of social media. Oxford: Oxford University Press.
9. Weinberger, D. (2007). Everything is miscellaneous: The power of the new digital disorder. New York: Times Books.
10. Zittrain, J. (2008) The future of the internet. New Haven: Yale University Press.
Essay (100%, 3000 words) in the LT.
Total students 2017/18: 74
Average class size 2017/18: 15
Controlled access 2017/18: Yes
Lecture capture used 2017/18: Yes (LT)
Value: Half Unit
Personal development skills
- Problem solving
- Application of information skills
- Commercial awareness
Course survey results
(2014/15 - 2016/17 combined)1 = "best" score, 5 = "worst" score
The scores below are average responses.
Response rate: 82%
Reading list (Q2.1)
Course satisfied (Q2.4)