Exploring the Potential of the Large Language Models (LLMs) in Identifying Misleading News Headlines

arXiv:2405.03153v1 Announce Type: cross
Abstract: In the digital age, the prevalence of misleading news headlines poses a significant challenge to information integrity, necessitating robust detection mechanisms. This study explores the efficacy of Large Language Models (LLMs) in identifying misleading versus non-misleading news headlines. Utilizing a dataset of 60 articles, sourced from both reputable and questionable outlets across health, science & tech, and business domains, we employ three LLMs- ChatGPT-3.5, ChatGPT-4, and Gemini-for classification. Our analysis reveals significant variance in model …

abstract age arxiv challenge cs.cl cs.cy cs.lg dataset detection digital digital age information information integrity integrity language language models large language large language models llms robust study type versus