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Misinformation on social media thrives on surprise, emotion, and identity-driven reasoning, often amplified through human cognitive biases. To investigate these mechanisms, we model large language model (LLM) personas as synthetic agents…

社会与信息网络 · 计算机科学 2025-12-10 Raj Gaurav Maurya , Vaibhav Shukla , Raj Abhijit Dandekar , Rajat Dandekar , Sreedath Panat

Large language models (LLMs) make it possible to generate synthetic behavioural data at scale, offering an ethical and low-cost alternative to human experiments. Whether such data can faithfully capture psychological differences driven by…

计算与语言 · 计算机科学 2025-11-27 Manuel Pratelli , Marinella Petrocchi

The spread of misinformation on social media platforms threatens democratic processes, contributes to massive economic losses, and endangers public health. Many efforts to address misinformation focus on a knowledge deficit model and…

计算与语言 · 计算机科学 2024-10-16 Saadia Gabriel , Liang Lyu , James Siderius , Marzyeh Ghassemi , Jacob Andreas , Asu Ozdaglar

Fake news and misinformation poses a significant threat to society, making efficient mitigation essential. However, manual fact-checking is costly and lacks scalability. Large Language Models (LLMs) offer promise in automating…

计算与语言 · 计算机科学 2025-06-09 Xiaofei Xu , Xiuzhen Zhang , Ke Deng

Misinformation is a growing societal threat, and susceptibility to misinformative claims varies across demographic groups due to differences in underlying beliefs. As Large Language Models (LLMs) are increasingly used to simulate human…

计算与语言 · 计算机科学 2026-05-27 Angana Borah , Zohaib Khan , Rada Mihalcea , Verónica Pérez-Rosas

Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reproduce patterns of susceptibility to misinformation remains unclear. We test whether LLM-simulated…

社会与信息网络 · 计算机科学 2026-04-13 Eun Cheol Choi , Lindsay E. Young , Emilio Ferrara

Existing challenges in misinformation exposure and susceptibility vary across demographic groups, as some populations are more vulnerable to misinformation than others. Large language models (LLMs) introduce new dimensions to these…

计算与语言 · 计算机科学 2025-10-15 Angana Borah , Rada Mihalcea , Verónica Pérez-Rosas

Large Language Models (LLMs) have demonstrated impressive capabilities in reasoning, positioning them as promising tools for supporting human problem-solving. However, what happens when their performance is affected by misinformation, i.e.,…

计算与语言 · 计算机科学 2025-09-24 Yiyang Feng , Yichen Wang , Shaobo Cui , Boi Faltings , Mina Lee , Jiawei Zhou

Disinformation campaigns can distort public perception and destabilize institutions. Understanding how different populations respond to information is crucial for designing effective interventions, yet real-world experimentation is…

社会与信息网络 · 计算机科学 2025-11-10 David Farr , Lynnette Hui Xian Ng , Stephen Prochaska , Iain J. Cruickshank , Jevin West

The rapid spread of misinformation, further amplified by recent advances in generative AI, poses significant threats to society, impacting public opinion, democratic stability, and national security. Understanding and proactively assessing…

人工智能 · 计算机科学 2025-06-02 Sania Nayab , Marco Simoni , Giulio Rossolini

Large language models (LLMs) can generate persuasive narratives at scale, raising concerns about their potential use in disinformation campaigns. Assessing this risk ultimately requires understanding how readers receive such content. In…

人工智能 · 计算机科学 2026-04-09 Zonghuan Xu , Xiang Zheng , Yutao Wu , Xingjun Ma

Misinformation about climate change causes numerous negative impacts, necessitating corrective responses. Psychological research has offered various strategies for reducing the influence of climate misinformation, such as the…

计算与语言 · 计算机科学 2024-07-09 Francisco Zanartu , Yulia Otmakhova , John Cook , Lea Frermann

Misinformation is on the rise, and the strong writing capabilities of LLMs lower the barrier for malicious actors to produce and disseminate false information. We study how LLMs behave when prompted to spread misinformation across languages…

Automated disinformation generation is often listed as an important risk associated with large language models (LLMs). The theoretical ability to flood the information space with disinformation content might have dramatic consequences for…

计算与语言 · 计算机科学 2025-06-13 Ivan Vykopal , Matúš Pikuliak , Ivan Srba , Robert Moro , Dominik Macko , Maria Bielikova

In today's digital era, the rapid spread of misinformation poses threats to public well-being and societal trust. As online misinformation proliferates, manual verification by fact checkers becomes increasingly challenging. We introduce…

计算与语言 · 计算机科学 2023-10-16 Eun Cheol Choi , Emilio Ferrara

Generative AI and misinformation research has evolved since our 2024 survey. This paper presents an updated perspective, transitioning from literature review to practical countermeasures. We report on changes in the threat landscape,…

计算机与社会 · 计算机科学 2026-02-12 Alexander Loth , Martin Kappes , Marc-Oliver Pahl

The capabilities of recent large language models (LLMs) to generate high-quality content indistinguishable by humans from human-written texts raises many concerns regarding their misuse. Previous research has shown that LLMs can be…

计算与语言 · 计算机科学 2025-07-28 Aneta Zugecova , Dominik Macko , Ivan Srba , Robert Moro , Jakub Kopal , Katarina Marcincinova , Matus Mesarcik

The advent of generative Large Language Models (LLMs) such as ChatGPT has catalyzed transformative advancements across multiple domains. However, alongside these advancements, they have also introduced potential threats. One critical…

计算与语言 · 计算机科学 2023-09-28 Bohan Jiang , Zhen Tan , Ayushi Nirmal , Huan Liu

Advances in large language models have raised concerns about their potential use in generating compelling election disinformation at scale. This study presents a two-part investigation into the capabilities of LLMs to automate stages of an…

Increased sophistication of large language models (LLMs) and the consequent quality of generated multilingual text raises concerns about potential disinformation misuse. While humans struggle to distinguish LLM-generated content from…

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