Mr Ignacio Ojea Quintana

College of Arts and Social Sciences

Areas of expertise

  • Decision Theory 220302
  • Logic 220308
  • Social Philosophy 220319
  • History And Philosophy Of Science (Incl. Non Historical Philosophy Of Science) 220206
  • History Of Ideas 220209
  • History Of Philosophy 220210
  • Communications Technologies 1005
  • Simulation And Modelling 080110

Research interests

My interests are in social and formal epistemology. I use formal tools to understand and tackle some of the impact that digital technologies have and will have in the way we organize knowledge in scientific and non-scientific communities. My dissertation focused on how to best represent the consensus and (network) dynamic of a social group given the attitude of its individuals, be them opinions or judgments of sympathy. I am now working on network segregation and (mis)information diffusion, as well as how reinforcement learning techniques used in recommender algorithms shape opinions and preferences. I am also interested in data science and machine learning (my GitHub).


I am a Research Fellow at the Philosophy Department of the Australian National University working on issues about trust in social networks and the impact of artificial intelligence in online communities.

I just finished my PhD at Columbia University where I spent the past two years teaching Columbia's core class Contemporary Civilization.

Curriculum Vitae

Researcher's projects

Segregation Dynamics in Social Networks

This project provides an explanation for online segregation and integration by extending some ideas originally developed by Schelling  [1969, 1971]. Agents in a social network aim to satisfy homophily and heterophily thresholds but, unlike other Schelling-like models, they do not change location within at topology but they cut and form new ties with neighbors. Hence the model is designed to represent the dynamics of friending/unfriending and following/unfollowing in social media. Although it is different from Schelling's, the model reveals that high degrees of macro segregation (integration) can emerge even with moderate homophily (heterophily) preferences at the micro level. We also show that heterophily has more effect than homophily in unequal populations. These results are demonstrated analytically and using simulations in Netlogo. The upshot, much like in Schelling's original models, is that large scale online segregation can emerge from otherwise innocuous individual behavior.

Return to top

Updated:  16 May 2021 / Responsible Officer:  Director (Research Services Division) / Page Contact:  Researchers