ArticlePloS one2020
An automated pipeline for the discovery of conspiracy and conspiracy theory narrative frameworks: Bridgegate, Pizzagate and storytelling on the web.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Network structure shapes consensus dynamics through individual decisions.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Leave the world(view) behind, but keep the words: The effect of conspiracism on writing.PloS one · 2026Article
- Dynamics and triggers of misinformation on vaccines.PloS one · 2025Article
- On modeling the correlates of conspiracy thinking.Scientific reports · 2023Article
- Article
- Individual, intergroup and nation-level influences on belief in conspiracy theories.Nature reviews psychology · 2023Review
- Should I trust or should I go? How people perceive and assess the quality of science communication to avoid fake news.Quality & quantity · 2022Article
- Interconnectedness and (in)coherence as a signature of conspiracy worldviews.Science advances · 2022Article
- Americans' Perspectives on Online Media Warning Labels.Behavioral sciences (Basel, Switzerland) · 2022Article
- Impact of correcting misinformation on social disruption.PloS one · 2022Article
- Modeling Discontinuous Cultural Evolution: The Impact of Cross-Domain Transfer.Frontiers in psychology · 2022Article
- Modelling social readers: novel tools for addressing reception from online book reviews.Royal Society open science · 2021Article
- Validation of the COVID-19 Transmission Misinformation Scale and Conditional Indirect Negative Effects on Wearing a Mask in Public.International journal of environmental research and public health · 2021Article
- Deceptive Online Content Detection Using Only Message Characteristics and a Machine Learning Trained Expert System.Sensors (Basel, Switzerland) · 2021Article
- COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication.Journal of medical Internet research · 2021Article
- Characterizing partisan political narrative frameworks about COVID-19 on Twitter.EPJ data science · 2021Article
- Article
- Article
- Conspiracy in the time of corona: automatic detection of emerging COVID-19 conspiracy theories in social media and the news.Journal of computational social science · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although a great deal of attention has been paid to how conspiracy theories circulate on social media, and the deleterious effect that they, and their factual counterpart conspiracies, have on political institutions, there has been little computational work done on describing their narrative structures. Predicating our work on narrative theory, we present an automated pipeline for the discovery and description of the generative narrative frameworks of conspiracy theories that circulate on social media, and actual conspiracies reported in the news media. We base this work on two separate comprehensive repositories of blog posts and news articles describing the well-known conspiracy theory Pizzagate from 2016, and the New Jersey political conspiracy Bridgegate from 2013. Inspired by the qualitative narrative theory of Greimas, we formulate a graphical generative machine learning model where nodes represent actors/actants, and multi-edges and self-loops among nodes capture context-specific relationships. Posts and news items are viewed as samples of subgraphs of the hidden narrative framework network. The problem of reconstructing the underlying narrative structure is then posed as a latent model estimation problem. To derive the narrative frameworks in our target corpora, we automatically extract and aggregate the actants (people, places, objects) and their relationships from the posts and articles. We capture context specific actants and interactant relationships by developing a system of supernodes and subnodes. We use these to construct an actant-relationship network, which constitutes the underlying generative narrative framework for each of the corpora. We show how the Pizzagate framework relies on the conspiracy theorists' interpretation of "hidden knowledge" to link otherwise unlinked domains of human interaction, and hypothesize that this multi-domain focus is an important feature of conspiracy theories. We contrast this to the single domain focus of an actual conspiracy. While Pizzagate relies on the alignment of multiple domains, Bridgegate remains firmly rooted in the single domain of New Jersey politics. We hypothesize that the narrative framework of a conspiracy theory might stabilize quickly in contrast to the narrative framework of an actual conspiracy, which might develop more slowly as revelations come to light. By highlighting the structural differences between the two narrative frameworks, our approach could be used by private and public analysts to help distinguish between conspiracy theories and conspiracies.
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