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The content and spread of conspiracy theories
La croyance aux théories du complot (TC) est associée à de nombreux préjudices sociétaux, notamment la violence, le refus des vaccins et l’extrémisme politique. Compte tenu de la vitesse et de l’intensité avec lesquelles les informations se propagent sur l’internet, il est urgent de comprendre ce que sont les TC et comment elles circulent. À travers quatre études, cette thèse de doctorat vise à atteindre cet objectif: comprendre le contenu et la diffusion des TC. Dans l’étude 1, nous avons développé le plus grand corpus de TC disponibleaujourd’hui, LOCO, qui permet d’explorer le contenu et la diffusion des TC. Une analyse du contenu linguistique a montré que les textes conspirationnistes sont axés sur la tromperie, le pouvoir et la domination. Les pages web conspirationnistes qui s’appuient sur un langage conspirationniste prototypique sont davantage partagées sur Facebook. Dans l’étude 2, nous avons constaté que les textes conspirationnistes sont plus interconnectés, plus hétérogènes sur le plan thématique et plus semblables les uns aux autres. Ces résultats ont apporté un soutien empirique solide à l’idée d’une vision globale du monde conspirationniste dans les récits conspirationnistes. Dans l’étude 3, nous avons développé des mesures pour évaluer les éléments de la pensée divergente et convergente dans les textes. Nous montrons que les textes conspirationnistes sont plus originaux, sémantiquement divergents et sophistiqués, mais moins adaptés à leur contexte et moins variables que les textes non conspirationnistes. Les résultats indiquent un déséquilibre entre la pensée divergente et la pensée convergente et peuvent expliquer l’accumulation de TC dans les systèmes de croyance des gens. Dans l’étude 4, nous avons conçu une étude de terrain pour comparer l’impact des médias sociaux et des biais cognitifs individuels sur le comportement de navigation en ligne vers des sites web classés en fonction de leur type et de leur force idéologique. Nous avons constaté qu’à mesure que l’idéologie conspirationniste des sites web augmente, la contribution des biais cognitifs individuels s’accroît au détriment du trafic provenant des médias sociaux. En résumé, les résultats obtenus dans le cadre de cette thèse ont des implications pratiques. En ce qui concerne le contenu des TC, la présence d’une mentalité conspirationniste qui émerge des textes représente une possibilité prévisible de développer des algorithmes pour la détection automatique des TC en ligne. En ce qui concerne la diffusion des TC, le fait de savoir que les biais cognitifs individuels favorisent l’accès aux sites web conspirationnistes suggère que les interventions au niveau individuel, telles que l’amélioration de la pensée critique, devraient être prioritaires dans la lutte contre la diffusion des TC. Belief in conspiracy theories (CTs) is associated with numerous societal harms, including violence, vaccine refusal, and political extremism. Given the speed and intensity with which information spread through the internet, there is a pressing need to understand what CTs are and how they circulate. Across four studies, This PhD thesis works towards this goal: understanding the content and spread of CTs. In Study 1, we developed the largest corpus of CTs available today, LOCO, that allows to explore the content and spread of CTs. An analysis of linguistic content showed that conspiracy texts are focused on deception, power, and dominance. Conspiracy webpages that rely on prototypical conspiratorial language are more shared on Facebook. In Study 2, we found that conspiracy texts are more interconnected, more topically heterogeneous, and more similar to one another. These results provided strong empirical support for an overarching conspiracy worldview in conspiracy narratives. In Study 3, we developed measures to assess elements of divergent and convergent thinking in texts. We show that conspiracy texts were more original, semantically divergent, and sophisticated, but less appropriate to their context and less variable compared to those in non-conspiracy texts. Results point to an imbalance between divergent and convergent thinking and may explain the accumulation of CTs within people’s belief systems. In Study 4, we devised a field study to compare the impact of social media and individual cognitive biases on online browsing behavior towards websites classified on ideological types and strength. We found that as the websites’ conspiratorial ideology increases, the contribution from individual cognitive biases increases at the expense of traffic from social media. In sum, results obtained from this thesis have practical implications. As for the content of CTs, the presence of conspiracy mentality that emerges from texts represents a foreseeable possibility to develop algorithms for the automatic detection of CTs online. In regard to the spread of CTs, knowing that individual cognitive biases drive access to conspiracy websites suggests that individual-level interventions, such as improving critical thinking, should be prioritized in the fight against the spread of CTs.
Interconnectedness and (in)coherence as a signature of conspiracy worldviews.
Conspiracy theories may arise out of an overarching conspiracy worldview that identifies common elements of subterfuge across unrelated or even contradictory explanations, leading to networks of self-reinforcing beliefs. We test this conjecture by analyzing a large natural language database of conspiracy and nonconspiracy texts for the same events, thus linking theory-driven psychological research with data-driven computational approaches. We find that, relative to nonconspiracy texts, conspiracy texts are more interconnected, more topically heterogeneous, and more similar to one another, revealing lower cohesion within texts but higher cohesion between texts and providing strong empirical support for an overarching conspiracy worldview. Our results provide inroads for classification algorithms and further exploration into individual differences in belief structures.
LOCO: The 88-million-word language of conspiracy corpus.
The spread of online conspiracy theories represents a serious threat to society. To understand the content of conspiracies, here we present the language of conspiracy (LOCO) corpus. LOCO is an 88-million-token corpus composed of topic-matched conspiracy (N = 23,937) and mainstream (N = 72,806) documents harvested from 150 websites. Mimicking internet user behavior, documents were identified using Google by crossing a set of seed phrases with a set of websites. LOCO is hierarchically structured, meaning that each document is cross-nested within websites (N = 150) and topics (N = 600, on three different resolutions). A rich set of linguistic features (N = 287) and metadata includes upload date, measures of social media engagement, measures of website popularity, size, and traffic, as well as political bias and factual reporting annotations. We explored LOCO's features from different perspectives showing that documents track important societal events through time (e.g., Princess Diana's death, Sandy Hook school shooting, coronavirus outbreaks), while patterns of lexical features (e.g., deception, power, dominance) overlap with those extracted from online social media communities dedicated to conspiracy theories. By computing within-subcorpus cosine similarity, we derived a subset of the most representative conspiracy documents (N = 4,227), which, compared to other conspiracy documents, display prototypical and exaggerated conspiratorial language and are more frequently shared on Facebook. We also show that conspiracy website users navigate to websites via more direct means than mainstream users, suggesting confirmation bias. LOCO and related datasets are freely available at https://osf.io/snpcg/ .