Director of Online Learning Strategy & Development
I am Lecturer in Science & Technology Studies and Turing Inaugural Fellow at the University of Edinburgh, where I research and teach in the sociology of data science. In my research I empirically focused on ICT market intermediaries (salespeople, global IT vendors, industry analysts & management consultants) and their interaction with clients and user organisations (click the publications tab above for my latest papers). When business turned heavily to analytics, I became interested in 'data science' applications with a view on how 'big data' is made visible and turned into pictures. I recently completed a ten year-long research programme on the sociology of business knowledge applying a mixed methods approach (including micro-empirical, computational and sequence analysis) to identify the dynamics of expertise in Information Technology markets. The picture below is the cover of my latest book that summarises this programme.
New book website: https://www.palgrave.com/gp/book/9783030603571
My current research empirically focuses on 'big data' and its role in high velocity environments, including sport. Methodologically, my continued focus is to demonstrate the role of micro-empirical social research in the development of the new discipline of social data science. Facilitated by domain expertise (I have UEFA B coaching licence from the Italian Football Association (FIGC) and a Match Analyst Certificate from SICS) I take football analytics as a field to develop a sociology of data science. I am currently studying the use of random forest algorithms to analyse football data. As part of a work that looks at the distribution of data science expertise in professional football, I am writing with Giolo Fele (University of Trento) on how sport data is used in TV broadcasting.
Follow my blog for more: https://blogs.ed.ac.uk/footballanalytics/
Marketing Technical Products (MAEE09003)
I have been pioneering online teaching delivery in the School of Social and Political Science and contributed to develop a Science, Technology and Innovation pathway in the Data Science, Technology and Innovation Msc, an cross-college with 220 on course students.
Within that programme I teach the popular online 20 credit course Understanding Data Visualisation (PGSP11484) in Semester 2 and the 10 credit Managing Digital Influence (PGSP11441) in Semester 1.
Campagnolo, G.M (2020) Social Data Science Xennials: Between Analogue and Digital Social Research, Palgrave.
Campagnolo, G.M. (2019) Participative epistemology in social data science: combining ethnography with computational and statistical approaches ().
Campagnolo, G.M., The Nguyen, H., Williams, R. (2019), “The temporal dynamics of technology promises in government and industry partnerships for digital innovation: the case of the Copyright Hub”, Technology Analysis & Strategic Management.
Campagnolo, G.M., Franklin, M., Giannatou, E., Stewart, J., Williams, R., (2018) “Revolution Remixed? The emergence of Open Content Filmmaking as a viable component within the mainstream film industry ”, Information, Communication & Society.
Giannatou, E., Campagnolo, G.M., Stewart, J., Williams, R., (2018) "Revolution Postponed? Tracing the Development and Limitations of Open Content Filmmaking", Information, Communication & Society.
Campagnolo, G.M., Pollock, N. & Williams, R. (2015) “Technology as we do not know it: the extended practice of global software development”, Information & Organization. Volume 25, Issue 3, July 2015, Pages 150–159.
Johnson, M., Mozaffar, H., Williams, R., Campagnolo, G.M., Hyysalo, S., Pollock, N. (2014) “The managed prosumer: Evolving knowledge strategies in the design of information infrastructures”. Information, Communication & Society, Published Online. 17:7, 795-813.
Campagnolo, G.M. (2013) “The Evolution of Client-Consultant Relationships: A Situational Analysis of IT Consultancy in the Public Sector”. Financial and Accountability Management, 29(2), 161-185.
Campagnolo, G.M., Fele, G., (2010) "From Specifications to Specific Vagueness: How Enterprise Software Mediates Engineering Relations". Engineering Studies, 2(3), 221-243.
Viscusi, G., Campagnolo, G.M., Curzi, Y., (2012) Phenomenology, Organizational Politics and IT Design: The Social Study of Information Systems, IGI Global, Hershey, PA.
Pollock, N., Campagnolo, G.M. (2015) “Subitizing Practices and Market Decisions. The Role of Simple Graphs In Business Settings” in Making Things Valuable, Martin Kornberger, Lise Jusesen, Jan Moursitsen & Anders Koed Madsen (Eds), Oxford University Press. (In Press).
Campagnolo, G.M., Ducati, S. (2010) “Changing Spaces for Social Learning in ERP Implementation: a Situational Analysis”, in: A. D’Atri, M. De Marco, A. M. Braccini, F. Cabiddu (eds), Management of the Interconnected World, Springer Physica-Verlag, pp. 97-104.
Campagnolo, G.M. (2010) “La prospettiva actor-network”, in: T.M. Fabbri (ed.), L’organizzazione: concetti e metodi, Carocci, Rome, pp. 243-255.
Campagnolo G.M. (2008) “Multi-sited ethnography and comparative case studies on technological implementation in the manufacturing industry” in A. Comacchio, A. Pontiggia, (eds.), L’organizzazione fa la differenza?, Carocci, Rome, pp. 95-111.
Campagnolo G.M., Jacucci G. (2006), “Designing the Accountability of Enterprise Architectures”, in J. Berleur, M.I. Nurminen & J. Impagliazzo (eds.), Social Informatics: An Information Society for All? In Remembrance of Rob Kling, Springer, New York, pp. 355-366.
Erbizzoni E., Teli M., Campagnolo G.M., De Paoli S., D’Andrea V. (2006), “Free/Open Source ERPs and translation processes: four empirical cases”, in A. Min Tjoa, L. Xu, S. Chaudhry (eds.) Research and Practical Issues of Enterprise Information Systems, Springer, New York, pp. 695- 704.
Liberman, K., Fele, G., D’Andrea, V., Campagnolo, G.M., Curzi, Y. & Viscusi, G. (2009) “Phenomenology and the Social Study of Information Systems: Conversations with Kenneth Liberman”, Quaderni di Sociologia, n.46, 5-60.
Campagnolo, G.M. (2007) “A Sociology of the Translation of ERP Systems to Financial Reporting”, Quaderni di Sociologia, n. 37, 5-91.
Valuation Studies, Social Data Science, Sociology of Images, Big data, Football
My current research programme progresses from qualitative to more data intensive approaches to map out expertise in the area of performance measurement, empirically addressing the field of professional football (see project micro-site). This programme already promoted interdisciplinary collaborations with applied mathematics (Andrew Duncan, Imperial College and Jacopo Diquigiovanni, University of Padua). I have been PI of the Alan Turing Institute Data Study Group "Player pathways: Understanding career paths that deliver success for professional football players and clubs" run in partnership with transfer market intelligence company PlayerLens. With a team of data scientists I took part to the first data hackathon a Football Association ever organised (Oct 18) and the publication of the report was seen on Twitter by more than 5,000 people within the first three weeks and got nearly 300 downloads on Edinburgh Research Explorer. Ours was the only team of academics invited to present to the prestigious Opta Pro Analytics Forum 2018, in front of an audience of Premier League club analysts and sport directors. This is a web application based on our study developed by a group of Edinburgh University students: https://dfd-fifa18.herokuapp.com/fifa18/home.
In team with Beatrice Alex, Gil Viry and Duncan Chapple I developed research that builds links between interpretive/qualitative and data intensive/quantitative research for the study of careers and expertise (see micro-website). By applying a combination of techniques including text mining, sequence analysis and ethnography, the project explores new ways to respond to the question: how do workers build careers across organisations? This large-scale study of career patterns provides insights into how professional background contributes to acquiring the skills and relationships necessary to build successful careers.
Other research activities
I also coordinate the social science input to the Edinburgh Data Science virtual campus. Previously, I have been visiting research fellow at Ecole des Mines in Paris and post-doc fellow at University of Trento (Italy), where I have also been consultant for the government’s digital agenda. I am interested in supervising PhD research addressing data science applications in policy-making and sport science.
I am currently interested in supervising postgraduate students wanting to undertake ethnographic studies of 'data science' applications, qualitatively analysing the full data life-cycle from production, to analysis, consumption, data presentation and related controversies. I am open to consider PhDs wanting to address this topic with empirical cases from different fields, from marketing to policy making to performance measurement including sport. Potential PhD topics are: - the impact of digital objectivity on coach ‘trained judgement’; - the implications of information overload on player performance; - data, gender and sport; - the promises of new analytics techniques applied to sport data; - the public perception of decision-aid technologies in sport; - the relationship between gaming and sport; - digital world and the future of sport; the embedded nature of player knowledge; - the interaction between different forms of data in sport (including social media data); - the use of data in injury prevention, transfer market analytics and player valuation.
Find out more about the programmes that I am involved with: