Agency in sustained human-AI chatbot talks emerges as co-constructed turn-by-turn through boundary-setting and intention-steering, organized in a new 3-by-4 framework of actors and actions.
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Large-scale experiments on two million agents reveal that collective intelligence does not emerge from scale alone due to sparse and shallow interactions.
Crepe introduces a graph-query technique in a no-code Android app for flexible collection of targeted mobile screen data with privacy and consent controls.
Survival analysis of three years of X posts shows conspiracy claims with greater semantic mutations have substantially longer lifespans, linked to changes in pronouns, social words, cognitive terms, and actor-action-target structures.
A counterspeech bot influences bystanders subtly through credible and normative presence, with cognitive strategies paired with positive tone proving relatively effective while poor performance can discourage participation.
An epidemiological model with Stackelberg interaction between a profit-maximizing platform and welfare-maximizing government shows that an optimal tax on amplification reduces hate speech prevalence, eliminates bistability, and lowers victim harm.
Multiverse analysis of three published CSS studies reveals substantial variation in findings across methodological decision combinations and identifies cases of computational failure not reported in originals.
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Platform-Driven Hate Speech: An Epidemiological Model with Optimal Taxation
An epidemiological model with Stackelberg interaction between a profit-maximizing platform and welfare-maximizing government shows that an optimal tax on amplification reduces hate speech prevalence, eliminates bistability, and lowers victim harm.