"Disinformation Spread" is a suite of computational models designed to encourage reflection on
the factors that affect belief in and the spread of disinformation.
Disinformation Spread is part of a project that I lead at the Transformative
Learning Technologies Lab
based at Columbia University. The models are developed using
the NetLogo language and extend two other models -- "Spread of
Disease" (Rand &, Wilensky, 2008) and "Virus on a Network" (Stonedahl & Wilensky, 2008). Each of
those models addresses a learning need identified in previous academic research on mis- and
in this project: I conceived, designed and
developed the models by remixing existing ones. In Fall 2022, I recruited a Master's student to
help me turning the prototype into a research project. Since then, we have collected data
through a study in which we interviewed learners testing the models and giving feedback on the
learning possibilities using the models, as well as their user interface and experience. We used
screen recording and task-based interviews to collect data, then analyzed data using thematic
analysis and UX research techniques.
The design process
involved user interviews
and learning about agent-based
, more specifically using Java-based NetLogo.
Below are some images of the models in their current stage of development.
image: model #1, containing components that are common to all
image: model #2, with "instant messaging" as form of spread
image: model #3, with "social media" as form of spread
image: model #4, which adds "fact-checking" as a factor reducing
the pace of disinformation spread
Click here to view the
prototype. Here and here are conference papers
associated with this project.