Oslo Summer School for Social Sciences 2021

Controversy mapping and computational anthropology: digital methods between the qualitative-quantitative divide

Associate Professor Anders Kristian Munk, Aalborg University Copenhagen

Course dates: 28 June - 2 July 2021

Main disciplines: Technology, Innovation and Culture, Science and Technology Studies, Techno-Anthropology, Research Methodology

Course Credits: 8 ECTS

Limitation: 25 participants

Teaching: Online

Course content

The past twenty-five years have seen a host of new digitally mediated fields becoming available to researchers in the social sciences and humanities. The shift is not only in the volume of digital traces, which is admittedly dramatic, but very much also in the kind of digital empirical material, we can now work with. Rather than having more of the same, and having it digitized, we are faced with a staggering and ever-evolving array of natively digital empirical material, born from social media platforms, search engines, mobile devices, sensors, etc., and thus shaped by the socio-technical infrastructures of these media environments.

While these new types of data hold great research potential, especially for fields and approaches interested in mundane traces of everyday life (e.g. anthropology), they also entail a set of methodological challenges. Indeed, both challenges and potentials are significantly compounded by the fact computational techniques like machine learning, natural language processing, network analysis, or computer vision have made it possible to work with conventionally qualitative data types (e.g. text, images or social interactions) in quantitative ways. Or, seen from a different angle, that these techniques have made the qualitative exploration of very large corpora feasible.

One strand of research that has taken a particular interest in the application of computational techniques to the analysis of digitally born material is the study of public knowledge controversies. This is partly due to the fact that such controversies are everywhere on the internet, but also because controversies typically involve a very heterogeneous and distributed cast of actors forming coalitions and alliances around an equally heterogeneous distributed set of issues. They are, in short, both complex and dynamic situations. The liveliness, richness, and granularity of online debates, combined with the power of computation to find patterns in these messy data streams, therefore hold great potential for controversy mapping.

The course introduces you to digital controversy mapping and its broader societal relevance discusses the role of computation in a traditionally qualitatively inclined field and gives you hands-on experience with the newest tools and techniques.

Learning objectives

Students who have followed the course should be able to:

  • Explain key concepts in digital methods
  • Explain key concepts in controversy mapping
  • Harvest traces of online controversy with scrapers and APIs
  • Conduct semantic analysis and find patterns in discourse using natural language processing
  • Conduct network analysis to find interactional patterns, identify actor groups and estimate their centrality
  • Discuss the role of such computational techniques in relation to other methods as well as their consequences for conventional divisions of labour between quantitative and qualitative traditions
  • Implement such computational techniques to do exploratory work in a research design and open up new questions for exploration
  • Critically reflect on the relationship between online knowledge controversy controversies and democratic publics
  • Critically reflect on the importance of involving stakeholders in successful controversy mapping projects

Teaching 

The course is organized as a series of lectures incorporating a substantial amount of teacher led exercises where students will have the opportunity to get hands-on experience with a series of digital methods techniques, ranging from ready made tools like Gephi, Cortext or Hyphe, to custom built scripts in Python.
 

Lecture 1: Introduction to digital methods and online grounding

What can traces of online interaction tell us about wider socio-cultural phenomena? What are the main methodological questions and challenges? And what are the promises this research agenda brings to the social sciences and humanities?

Readings:
Marres, N. (2015). Why map issues? On controversy analysis as a digital method. Science, Technology, & Human Values, 40(5), 655–686. 31 pages.

Rogers, R. (2018). Digital Traces in Context| Otherwise Engaged: Social Media from Vanity Metrics to Critical Analytics. International Journal of Communication, 12, 23. 22 pages.

Munk, A. K., Abildgaard, M. S., Birkbak, A., & Petersen, M. K. (2016, July). (Re-) Appropriating Instagram for Social Research: Three methods for studying obesogenic environments. In Proceedings of the 7th 2016 International Conference on Social Media & Society (pp. 1-10). 10 pages.

 

Lecture 2: Curating natively digital material

How can data be harvested from digital platforms? What kind of questions should we ask about these platforms in order to make sense of the harvested material? What does it mean that our methods are distributed? Introduction to techniques like scraping, crawing, and API interaction.

Readings:
Jacomy, M., Girard, P., Ooghe-Tabanou, B., & Venturini, T. (2016, March). Hyphe, a curation-oriented approach to web crawling for the social sciences. In Tenth International AAAI Conference on Web and Social Media. 4 pages.

Lomborg, S., & Bechmann, A. (2014). Using APIs for data collection on social media. The Information Society, 30(4), 256-265. 9 pages.

Rogers, Richard. (2017). Foundations of Digital Methods: Query Design. In: The Datafied Society: Studying Culture through Data, Publisher: Amsterdam University Press, Editors: Mirko Schaefer and Karin van Es, pp.75–94 19 pages.

Munk, A. (2013). Techno-anthropology and the digital natives. What is techno-anthropology, 287-310. 13 pages.
 

Lecture 3: Introduction to controversy mapping

What characterizes public knowledge controversies as objects of study? What is the difference between knowledge controversies and mere political disagreements? What hapens when expertise is contested and questions become ambiguous? We take an actor-network theoretical approach to controversies and how they can be mapped.

Readings:
Venturini, T. (2010). Diving in magma: how to explore controversies with actor-network theory. Public understanding of science, 19(3), 258-273. 25 pages.

Pinch, T., & Leuenberger, C. (2006). Studying scientific controversy from the STS perspective. Department of Science & Technology Studies. 11 pages

Epstein, S. (1995). The construction of lay expertise: AIDS activism and the forging of credibility in the reform of clinical trials. Science, Technology, & Human Values, 20(4), 408–437. 29 pages.

Thompson, C. (2002). When elephants stand for competing philosophies of nature: Amboseli National Parc, Kenya. J. Law et A. Mol (Eds.), Complexities, 166–190. 24 pages.
 

Lecture 4: Mapping controversies with digital methods

How can digital methods help controversy mappers chart the changing landscapes of actors and issues online?

Readings:
Burgess, J., & Matamoros-Fernández, A. (2016). Mapping sociocultural controversies across digital media platforms: One week of# gamergate on Twitter, YouTube, and Tumblr. Communication Research and Practice, 2(1), 79-96. 27 pages.

Moats, D. (2019). Following the Fukushima Disaster on (and against) Wikipedia: A Methodological Note about STS Research and Online Platforms. Science, Technology, & Human Values, 44(6), 938-964. 25 pages.

Marres, N., & Moats, D. (2015). Mapping controversies with Social Media: The case for symmetry. Social Media+ Society, 1(2). 17 pages.

Venturini, T. (2012). Building on faults: how to represent controversies with digital methods. Public understanding of science, 21(7), 796–812. 16 pages.

Weltevrede, E., & Borra, E. (2016). Platform affordances and data practices: The value of dispute on Wikipedia. Big Data & Society, 3(1), 2053951716653418. 16 pages.

Koed Madsen, A. (2012). Web-visions as controversy-lenses. Interdisciplinary Science Reviews, 37(1), 51-68. 16 pages.

Munk, A. K. (2014). Mapping Wind Energy Controversies Online: Introduction to Methods and Datasets. 24 pages.

 

Lecture 5: Visual network analysis and explorative data visualization

How can force directed graph layouts and other network metrics help us discover patterns in the way actors and informants interact? Introduction to Gephi.

Readings:
Venturini, T., Jacomy, M., Jensen, P. (2019). What Do We See When We Look at Networks. An Introduction to Visual Network Analysis and Force-Directed Layouts. 30 pages

Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. ICWSM, 8, 361-362. 2 pages.

Venturini, T., Munk, A., & Jacomy, M. (2019). Actor-network vs network analysis vs digital networks are we talking about the same networks? digitalSTS: A Field Guide for Science & Technology Studies. 13 pages.
 

Lecture 6: Exploration of large text corpora

How can natural language processing help us discover discourse from actors and informants? Introduction to Cortext.

Readings:
Venturini, T., Baya Laffite, N., Cointet, J. P., Gray, I., Zabban, V., & De Pryck, K. (2014). Three maps and three misunderstandings: A digital mapping of climate diplomacy. Big Data & Society, 1(2). 19 pages.

Elgaard Jensen, T., Kleberg Hansen, A. K., Ulijaszek, S., Munk, A. K., Madsen, A. K., Hillersdal, L., & Jespersen, A. P. (2019). Identifying notions of environment in obesity research using a mixed‐methods approach. Obesity Reviews, 20(4), 621-630. 18 pages
 

Lecture 7: Quali-quantitative analysis as methodological complementarity

We will discuss how computational analysis of large volumes of digital traces can help us pose questions and generate hypotheses that can subsequently be qualitatively explored and thus guide fieldwork.

Readings:
Blok, A., & Pedersen, M. A. (2014). Complementary social science? Quali-quantitative experiments in a Big Data world. Big Data & Society, 1(2), 2053951714543908. 6 pages.

Munk, A. K., & Ellern, A. B. (2015). Mapping the New Nordic issuescape: How to navigate a diffuse controversy with digital methods. Tourism encounters and controversies: Ontological politics of tourism development.

Borch, K., Munk, A. K., & Dahlgaard, V. (2020). Mapping wind-power controversies on social media: Facebook as a powerful mobilizer of local resistance. Energy Policy, 138, 111223. 10 pages.
 

Lecture 8: Quali-quantitative analysis beyond micro and macro levels

What are the anthropological and sociological foundations for the current debate about qualitative and quantitative methods and their potential interfaces? We revisit the Tarde-Durkheim debate and the historical-geographical paradigm in material folk culture and ask how current computational techniques could return the social sciences to a state where micro and macro levels of analysis are no longer necessary.

Readings:
Latour, B., Jensen, P., Venturini, T., Grauwin, S., and Boullier, D. (2012). The whole is always smaller than its parts’ – a digital test of Gabriel Tardes’ monads. The British Journal of Sociology 2012 Volume 63 Issue 4, 590-615. 25 pages.

Munk, A. K. (2019). Four styles of quali-quantitative analysis: Making sense of the new Nordic food movement on the web. Nordicom Review, 40(s1), 159-176. 17 pages.

Munk, A. K., & Jensen, T. E. (2014). Revisiting the histories of mapping. Ethnologia Europaea, 44(2), 31. 17 pages.

 

Lecture 9: Knowledge controversies and their analysis in a democratic context

What is the role of controversies and controversy mapping in relation to democratic publics? We will draw on ideas from American pragmatism and the public engagement with science paradigm to critically revisit notions like post-truth, echo-chambers and fake news in online contexts.

Readings:
Stengers, I. (2005). The cosmopolitical proposal. Making things public: Atmospheres of democracy, 994–1003. 9 pages.

Law, J., & Singleton, V. (2014). ANT, multiplicity and policy. Critical policy studies, 8(4), 379–396. 18 pages.

Callon, M. (1999). The role of lay people in the production and dissemination of scientific knowledge. Science, Technology and Society, 4(1), 81–94. 13 pages.

Whatmore, S. J. (2009). Mapping knowledge controversies: science, democracy and the redistribution of expertise. Progress in Human Geography, 33(5), 587-598. 11 pages.

Marres, N. (2005). Issues spark a public into being: A key but often forgotten point of the Lippmann-Dewey debate. Making things public: Atmospheres of democracy, 208–217. 9 pages.

Barry, A. (2002). The anti-political economy. Economy and society, 31(2), 268–284. 16 pages.
 

Lecture 10: Data curation and computation in the presence of its ‘victims’

What are the rationales for involving stakeholders upstream in digital methods projects? And what are the different strategies for facilitating this involvement (such as the organization of data sprints). We work with the concept of participatory data design and the difference between what Latour calls ‘critical proximity’ and ‘critical distance’ in digital methods.

Readings:
Madsen, A. K., & Munk, A. K. (2019). Experiments with a data-public: Moving digital methods into critical proximity with political practice. Big Data & Society, 6(1). 14 pages.

Munk, A. K., Madsen, A. K., & Jacomy, M. (2019). Thinking through the databody: Sprints as experimental situations. In Designs for Experimentation and Inquiry (pp. 110-129). Routledge. 19 pages.

Munk, A. K., Meunier, A., & Venturini, T. (2019). Data sprints: A collaborative format in digital controversy mapping. digitalSTS: A Field Guide for Science & Technology Studies, 472.

Whatmore, S. J., & Landström, C. (2011). Flood apprentices: an exercise in making things public. Economy and society, 40(4), 582-610. 28 pages

Latour, B. (2004). Why has critique run out of steam? From matters of fact to matters of concern. Critical inquiry, 30(2), 225–248. 23 pages.

 

Reading list

Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. ICWSM, 8, 361-362. 2 pages.

Barry, A. (2002). The anti-political economy. Economy and society, 31(2), 268–284. 16 pages.

Blok, A., & Pedersen, M. A. (2014). Complementary social science? Quali-quantitative experiments in a Big Data world. Big Data & Society, 1(2), 2053951714543908. 6 pages.

Borch, K., Munk, A. K., & Dahlgaard, V. (2020). Mapping wind-power controversies on social media: Facebook as a powerful mobilizer of local resistance. Energy Policy, 138, 111223. 10 pages.

Burgess, J., & Matamoros-Fernández, A. (2016). Mapping sociocultural controversies across digital media platforms: One week of# gamergate on Twitter, YouTube, and Tumblr. Communication Research and Practice, 2(1), 79-96. 27 pages.

Callon, M. (1999). The role of lay people in the production and dissemination of scientific knowledge. Science, Technology and Society, 4(1), 81–94. 13 pages.

Elgaard Jensen, T., Kleberg Hansen, A. K., Ulijaszek, S., Munk, A. K., Madsen, A. K., Hillersdal, L., & Jespersen, A. P. (2019). Identifying notions of environment in obesity research using a mixed‐methods approach. Obesity Reviews, 20(4), 621-630. 18 pages

Epstein, S. (1995). The construction of lay expertise: AIDS activism and the forging of credibility in the reform of clinical trials. Science, Technology, & Human Values, 20(4), 408–437. 29 pages.

Jacomy, M., Girard, P., Ooghe-Tabanou, B., & Venturini, T. (2016, March). Hyphe, a curation-oriented approach to web crawling for the social sciences. In Tenth International AAAI Conference on Web and Social Media. 4 pages.

Koed Madsen, A. (2012). Web-visions as controversy-lenses. Interdisciplinary Science Reviews, 37(1), 51-68. 16 pages.

Latour, B., Jensen, P., Venturini, T., Grauwin, S., and Boullier, D. (2012). The whole is always smaller than its parts’ – a digital test of Gabriel Tardes’ monads. The British Journal of Sociology 2012 Volume 63 Issue 4, 590-615. 25 pages.

Latour, B. (2004). Why has critique run out of steam? From matters of fact to matters of concern. Critical inquiry, 30(2), 225–248. 23 pages.

Law, J., & Singleton, V. (2014). ANT, multiplicity and policy. Critical policy studies, 8(4), 379–396. 18 pages.

Lomborg, S., & Bechmann, A. (2014). Using APIs for data collection on social media. The Information Society, 30(4), 256-265. 9 pages.
Pinch, T., & Leuenberger, C. (2006). Studying scientific controversy from the STS perspective. Department of Science & Technology Studies. 11 pages

Madsen, A. K., & Munk, A. K. (2019). Experiments with a data-public: Moving digital methods into critical proximity with political practice. Big Data & Society, 6(1). 14 pages.

Marres, N. (2015). Why map issues? On controversy analysis as a digital method. Science, Technology, & Human Values, 40(5), 655–686. 31 pages.

Marres, N. (2005). Issues spark a public into being: A key but often forgotten point of the Lippmann-Dewey debate. Making things public: Atmospheres of democracy, 208–217. 9 pages.

Moats, D. (2019). Following the Fukushima Disaster on (and against) Wikipedia: A Methodological Note about STS Research and Online Platforms. Science, Technology, & Human Values, 44(6), 938-964. 25 pages.

Marres, N., & Moats, D. (2015). Mapping controversies with Social Media: The case for symmetry. Social Media+ Society, 1(2). 17 pages.

Munk, A. (2013). Techno-anthropology and the digital natives. What is techno-anthropology, 287-310. 13 pages.

Munk, A. K. (2019). Four styles of quali-quantitative analysis: Making sense of the new Nordic food movement on the web. Nordicom Review, 40(s1), 159-176. 17 pages.

Munk, A. K., & Ellern, A. B. (2015). Mapping the New Nordic issuescape: How to navigate a diffuse controversy with digital methods. Tourism encounters and controversies: Ontological politics of tourism development.

Munk, A. K., Abildgaard, M. S., Birkbak, A., & Petersen, M. K. (2016, July). (Re-) Appropriating Instagram for Social Research: Three methods for studying obesogenic environments. In Proceedings of the 7th 2016 International Conference on Social Media & Society (pp. 1-10). 10 pages.

Munk, A. K., Madsen, A. K., & Jacomy, M. (2019). Thinking through the databody: Sprints as experimental situations. In Designs for Experimentation and Inquiry (pp. 110-129). Routledge. 19 pages.

Munk, A. K., Meunier, A., & Venturini, T. (2019). Data sprints: A collaborative format in digital controversy mapping. digitalSTS: A Field Guide for Science & Technology Studies, 472. 24 pages.

Munk, A. K., & Jensen, T. E. (2014). Revisiting the histories of mapping. Ethnologia Europaea, 44(2), 31. 17 pages.

Munk, A. K. (2014). Mapping Wind Energy Controversies Online: Introduction to Methods and Datasets. 24 pages.

Venturini, T., Jacomy, M., Jensen, P. (2019). What Do We See When We Look at Networks. An Introduction to Visual Network Analysis and Force-Directed Layouts. 30 pages

Venturini, T., Baya Laffite, N., Cointet, J. P., Gray, I., Zabban, V., & De Pryck, K. (2014). Three maps and three misunderstandings: A digital mapping of climate diplomacy. Big Data & Society, 1(2). 19 pages.

Venturini, T., Munk, A., & Jacomy, M. (2019). Actor-network vs network analysis vs digital networks are we talking about the same networks? digitalSTS: A Field Guide for Science & Technology Studies. 13 pages.

Venturini, T. (2010). Diving in magma: how to explore controversies with actor-network theory. Public understanding of science, 19(3), 258-273. 25 pages.

Venturini, T. (2012). Building on faults: how to represent controversies with digital methods. Public understanding of science, 21(7), 796–812. 16 pages.

Rogers, R. (2018). Digital Traces in Context| Otherwise Engaged: Social Media from Vanity Metrics to Critical Analytics. International Journal of Communication, 12, 23. 22 pages.

Rogers, Richard. (2017). Foundations of Digital Methods: Query Design. In: The Datafied Society: Studying Culture through Data, Publisher: Amsterdam University Press, Editors: Mirko Schaefer and Karin van Es, pp.75–94 19 pages.

Stengers, I. (2005). The cosmopolitical proposal. Making things public: Atmospheres of democracy, 994–1003. 9 pages.

Thompson, C. (2002). When elephants stand for competing philosophies of nature: Amboseli National Parc, Kenya. J. Law et A. Mol (Eds.), Complexities, 166–190. 24 pages.

Whatmore, S. J. (2009). Mapping knowledge controversies: science, democracy and the redistribution of expertise. Progress in Human Geography, 33(5), 587-598. 11 pages.

Whatmore, S. J., & Landström, C. (2011). Flood apprentices: an exercise in making things public. Economy and society, 40(4), 582-610. 28 pages

Weltevrede, E., & Borra, E. (2016). Platform affordances and data practices: The value of dispute on Wikipedia. Big Data & Society, 3(1), 2053951716653418. 16 pages.

 

Key books for course preparations

Rogers, R. (2019). Doing digital methods. SAGE Publications Limited.

Marres, N. (2017). Digital sociology: The reinvention of social research. John Wiley & Sons.

Schäfer, M. T., & Van Es, K. (2017). The datafied society: Studying culture through data. Amsterdam University Press.

For Scandinavian readers:
Birkbak, A., & Munk, A. K. (2017). Digitale metoder. Hans Reitzels Forlag.

 

The lecturer

Anders Kristian Munk is associate professor in techno-anthropology and director of the Techno-Anthropology Lab at the University of Aalborg in Copenhagen. He holds a D.Phil. in geography from the university of Oxford and an M.A. in European ethnology from the University of Copenhagen. Over the past decade Anders’ research has been focused on the development of new digital methods and computational techniques for SSH research, particularly in the context of controversy analysis in STS. He has worked as a visiting research fellow at Bruno Latour’s médialab in Paris and has co-authored the first Danish language textbook on digital methods together as well as a forthcoming book on digital controversy mapping.

 

 

Tags: PhD, Summer School, Anthropology, Research Methods, Anders Munk
Published Feb. 27, 2020 8:42 AM - Last modified Jan. 12, 2021 3:36 PM