Conspiracy beliefs and analytical thinking in COVID-19 information web search
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The phenomenon of conspiracy theories has seen a considerable increase in popularity on the internet, especially in the health domain. Surprisingly, despite a substantial body of research, none has directly examined the information-search process of conspiracists as they navigate on the Internet. This study examines how conspiracy theorists search for online information (through the Exploration/Exploitation trade-off), using a simulated COVID-19 fact-finding task on vaccine side effects presenting official and conspiracy webpages. The study investigates how conspiracy levels and analytical thinking predict navigational strategies and the acquisition of new knowledge. Results show that analytical thinking predicts the use of exploratory navigation strategies. Analytic thinkers gather more useful information from official webpages and have more confidence in this information. Conversely, conspiracists gather more novel information from conspiracy webpages and have more confidence in these sources. This study offers a novel approach by combining the psychology of belief, reasoning, and Internet information search. • Conspiracy beliefs relate to how people search health info on the Internet. • Analytical thinkers tend to be more critical regarding their evaluation of online information. • Conspiracy theorist tend to visit fewer “official” webpages during information search. • Reasoning style is related to navigation search strategies. • Exploratory findings reveal distinct information processing patterns across conspiracy theorist and analytic thinkers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it