Old strategies, new environments: Reinforcement Learning on social media DOI Creative Commons
Georgia Turner, Amanda M Ferguson,

Tanay Katiyar

и другие.

Biological Psychiatry, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Язык: Английский

Blatantly false news increases belief in news that is merely implausible DOI Open Access
David Levari, Cameron Martel, Reed Orchinik

и другие.

Опубликована: Фев. 1, 2024

What are the consequences of encountering blatant falsehoods and “fake news”? Here we show that exposure to a high prevalence very implausible claims can increase belief in other, more ambiguous false claims, as they seem believable comparison. Participants five preregistered experiments (N=5,476) were exposed lower or higher rates news headlines seemed blatantly false, well some plausible true headlines. Being extremely increased unrelated which (or even plausible), regardless whether false. The effect persisted for describing hypothetical events, actual It occurred people actively evaluated read them passively, among liberals conservatives, those low cognitive reflection. We observed this environments where plausibility claim was reliable useful cue it truth unrelated. argue lowers threshold other believable. Such relative comparisons hallmark brain’s tendency towards efficient computations perception judgment. Even when consumers reliably identify disregard content, such content may make subtler likely be believed.

Язык: Английский

Процитировано

3

Religion, Cognition, and Political Behavior DOI Creative Commons
Syahirul Alim

Peradaban Journal of Religion and Society, Год журнала: 2024, Номер 3(2), С. 113 - 129

Опубликована: Июль 29, 2024

Political polarization is a complex phenomenon with significant implications for democratic processes worldwide. This study investigates the cognitive mechanisms underlying political reinforcement learning and examines how environmental information influences decision-making, resulting in diverse behaviors beliefs. The methodology employed encompasses descriptive analysis, systematic literature review, content analysis. Data were sourced from various countries to ensure comprehensive perspective. Key findings indicate that both traditional social media significantly shape opinions, while biases motivations can lead divergent interpretations of identical facts, culminating polarized Interventions enhance flexibility metacognitive insight, as well those promoting civil discourse reducing intergroup anxiety, found be effective mitigating polarization. research provides valuable insights into dynamics proposes strategies reduce strengthen institutions. Future should prioritize empirical validation these models testing interventions across cultural contexts.

Язык: Английский

Процитировано

0

Reinforcement Learning in Social Sciences: A Survey DOI Creative Commons
Doaa El-Shahat, Nourhan Talal, Mohamed Abouhawwash

и другие.

Deleted Journal, Год журнала: 2024, Номер 4, С. 79 - 92

Опубликована: Авг. 5, 2024

Reinforcement Learning (RL) has become one of the most prominent topics in artificial intelligence research. It is widely used various fields, such as recommendation systems, psychology, economics, and natural language dialogue systems. Finding best path action to maximize cumulative reward long-term strategy RL. Undertaking research may yield suboptimal immediate results but optimal consequences. Economists can address difficult behavioral problems with knowledge, especially those generated by deep learning algorithms. We provide recent advancements RL methods this study, along their applications gaming, finance, economics. The survey's last section discusses RL's present potential future developments. Such open sample efficiency, safety, interpretability are currently being sought after researchers. Moreover, several ambitious prospective a wide variety domains discussed. This study gives comprehensive review many uses social science. study's will give researchers standard against which evaluate utility efficacy frequently Guide investigations across domains.

Язык: Английский

Процитировано

0

A cognitive approach to learning, monitoring, and shifting social norms DOI
Uri Hertz

Current Opinion in Psychology, Год журнала: 2024, Номер 60, С. 101917 - 101917

Опубликована: Сен. 25, 2024

Язык: Английский

Процитировано

0

Old strategies, new environments: Reinforcement Learning on social media DOI Creative Commons
Georgia Turner, Amanda M Ferguson,

Tanay Katiyar

и другие.

Biological Psychiatry, Год журнала: 2024, Номер unknown

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

0