Trends in Political Misinformation Over a Twelve Year Period
An analysis of twelve years of PolitiFact data reveals an increase in political misinformation, particularly on social media, highlighting the need for robust algorithms to combat its spread across different modalities and recurring topics.
ソーシャルメディアにおける欺瞞行為検出のための機械学習アプローチの系統的レビュー：手法、課題、バイアス - データ処理、ハイパーパラメータ調整、評価における落とし穴と将来の方向性
本論文は、ソーシャルメディアにおける欺瞞行為検出のための機械学習（ML）と深層学習（DL）の有効性と課題を体系的にレビューし、データの偏り、不十分な前処理、一貫性のないハイパーパラメータ調整、不適切な評価指標の使用など、MLライフサイクル全体にわたるバイアスを明らかにしています。
저자원 언어에 대한 단일 언어 및 다국어 허위 정보 탐지: 데이터 세트, 방법론, 과제 및 미래 방향에 대한 포괄적인 설문 조사
저자원 언어로 된 허위 정보 탐지는 심각한 과제이며, 데이터 세트의 부족, 모델 개발의 어려움, 문화적 및 언어적 맥락의 중요성, 실제 적용의 부족, 연구 노력의 부족 등 여러 과제에 직면해 있습니다.
A Survey of Misinformation Detection in Low-Resource Languages: Challenges and Future Directions
Low-resource languages face significant challenges in misinformation detection due to limited data, technical constraints, and contextual complexities, necessitating increased research efforts, language-agnostic models, and multi-modal approaches for effective mitigation.
CrediRAG: Detecting Misinformation on Reddit Using Source Credibility and Network Analysis
CrediRAG is a novel approach to detecting fake news on Reddit that leverages the credibility of news sources and the network structure of user interactions to achieve higher accuracy than existing methods.
Web Retrieval Agents Enhance Large Language Model Performance in Misinformation Detection
Combining large language models (LLMs) with web retrieval agents significantly improves the accuracy of misinformation detection, outperforming LLMs used in isolation.
A Comparative Study of Machine Learning and Deep Learning Models for Detecting COVID-19 Misinformation in Text
Deep learning models, particularly hybrid CNN+LSTM architectures, outperform conventional machine learning classifiers in detecting COVID-19 misinformation on social media.
Detecting Misinformation with Legal Consequences (MisLC): A Novel Task Using Large Language Models
This research paper introduces Misinformation with Legal Consequences (MisLC), a new task leveraging large language models to detect misinformation that could potentially violate existing laws.
SNIFFER: Multimodal Large Language Model for Out-of-Context Misinformation Detection
SNIFFER is a novel multimodal large language model specifically engineered for detecting and explaining out-of-context misinformation.
SNIFFER: Multimodal Large Language Model for Out-of-Context Misinformation Detection
Multimodal large language model SNIFFER detects and explains out-of-context misinformation effectively.
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