Profiling Bolsobot Networks

How to capture the operation of political bots networks? Which types of accounts compose bot ecologies? How do bots promote content? To what extent do platform moderation policies impact bots’ activities over time? How does inauthentic activity change as content moderation measures refine their capture of bots and other “platform manipulations”? This project gathers and profiles accounts operating in Brazilian online political debates through the use of quali-quantitative methods. It investigates the activities of pro- and anti- president Jair Bolsonaro bots across platforms (i.e. Instagram, Twitter and TikTok) to make “inauthentic” behaviour visible, as well as addressing challenges of studying networked disinformation environments.

The project explores methodological approaches for studying inauthentic behaviour online that moves beyond bot detection towards an analysis of their vernacular, collective strategies and particularities. The project aims to produce a series of research reports on “bolsobots”, their networks and digital methods recipes to understand their social lives.

For more details see: Omena, J. J., Lobo, T., Tucci, G., Bitencourt, E., de Keulenaar, E., Kerche, F., Chao, J., Liedtke, M., Li, M., Paschoal, M. L., & Lavrov, I. (2024). Quali-quanti visual methods and political bots: A cross-platform study of pro- & anti-bolsobots. Journal of Digital Social Research6(1), 50-73.



East and Southeast Asians: Documenting a Category in the Making

In collaboration with organisations involved in its development and promotion, the aim of this project is to critically document and analyse the making of a new collective ethnic identifier in the United Kingdom: “East and Southeast Asian” (ESEA).

The term ESEA has emerged relatively recently in the UK, coming to prominence since 2018. This term is typically used as a bottom-up collective ethnic identifier for communities who originate from, or have ties to, East and Southeast Asia. Increasingly, it also functions as means of categorising communities to secure political recognition and representation.

Ethnic and racial categories are crucial yet contested components of modern societies. These categories are often essential for tracking the presence of minority groups within a polity and ensuring their representation and inclusion in formal politics and institutional settings. But such categories can also be instruments of exclusion – particularly if they mis-represent the groups they’re supposed to encompass. Indeed, communities often also form in resistance to the very mechanisms of categorisation.

In the past few years, a number of different activist groups and civil society campaigns have begun to use ESEA for at least three key reasons: 

  1. In solidaristic response to the intensification of anti-Asian racism and violence spurred by the COVID-19 pandemic, and racism against BIPOC highlighted by BLM; 
  2. To campaign for the institutional inclusion of ESEA communities (In the UK, the word “Asian” typically refers to people of South Asian origin); and
  3. As a form of political community-building.

The emergence of this term provides us with a rare opportunity to study a collective ethnic identifier in the making. Using digital methods and approaches derived from critical code race studies, we hope to produce research outcomes that our collaborating organisations can use in their advocacy work, while also producing a better understanding of how and why such collective community identifiers emerge and how they come to be institutionalised as categories. 

For more on this project see:

A Field Guide to Algorithms

What are algorithms? Who and what do they involve? What do they do? What is at stake with them? How can we account for them? How can we respond to them?

Following on from the Field Guide to “Fake News”, A Field Guide To Algorithms aims to gather and curate different starting points, recipes, approaches, experiments in participation and activities for collective inquiry into algorithms and the collectives, cultures, infrastructures, imaginaries and practices associated with them.

See also:

Assembling a Global Database on Corporate Taxation

This project explores the assembly of a global, open-source database on the economic activities and tax contributions of multinational corporations. In particular it examines how prototyping may serve as a speculative method to not only gather information from diverse sources, but also to engage with organisations, groups and communities who are concerned or affected by this issue, to materialise the problem of corporate tax avoidance and to suggest other ways of organising economic life.

The project is undertaken together with the Open Data for Tax Justice (#OD4TJ) network and builds on the What Do They Pay? report. If you’re interested in contributing or finding out more, you can get in touch on this address.

Field Guide to Public Data Projects

The United Nations has suggested the need for a “data revolution” to address urgent transnational issues such as climate change and inequality. It has endorsed not only improving national statistical data collection, but also opening public sector data up for broader societal re-use, as well as exploring the capacities of emerging forms of digital data, infrastructures and devices in understanding and responding to public problems.

Over the past decade, open data and civic tech initiatives around the world have been set up to promote the re-use of public data for participation and involvement; citizens are gathering their own data on air, soil and biodiversity; and journalists and activists are increasingly using and creating data to support their investigations and campaigns around economic, racial and ecological justice.

What do public data projects do? How do they invite and enable participation and action, and to what end? How can they be studied? How can we critically engage with their histories, social lives and politics? How might studies of these kinds of projects lead to modifications in data practice?

The Field Guide to Public Data Projects explores methods and approaches for finding, following, gathering and comparing different kinds of projects involving public data – from data portals to data communities, sensing practices to mobile apps.

Exploratory research for this project is being developed with support from the King’s Undergraduate Research Fellowship (KURF) scheme at King’s College London.

Out of the Flames: Mapping the Politics of #AmazonFires

A collaboration with the European Forest Institute to explore forest governance and the changing role of forests in society according to web and social media data.

The project explores how the 2019 Amazon forest fires were addressed and accounted for through a series of analyses using online data from digital platforms including Twitter, Facebook, Google, Instagram, and Youtube. For further details see:

  • Out of the Flames – project website and report with the European Forest Institute
  • Colombo, G., Bounegru, L., & Gray, J. (2023). Visual Models for Social Media Image Analysis: Groupings, Engagement, Trends, and Rankings. International Journal Of Communication, 17, 28. Retrieved from
  • Gray, J. W. Y., Bounegru, L., & Colombo, G. (forthcoming). #AmazonFires and the online composition of forest politics. In J. Turnbull, A. Searle, H. Anderson-Elliot, & E. H. Giraud (Eds.), Digital Ecologies: Mediating More-Than-Human Worlds. Manchester, UK: Manchester University Press.