EXMULF: An Explainable Multimodal Content-Based Fake News Detection System

Sabrine Amri; Dorsaf Sallami; Esma Aı̈meur

doi:10.1007/978-3-031-08147-7_12

ScienceGate Book Chapters

BOOK-CHAPTER

EXMULF: An Explainable Multimodal Content-Based Fake News Detection System

Sabrine Amri Dorsaf Sallami Esma Aı̈meur

Year: 2022 Lecture notes in computer science Pages: 177-187 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-08147-7_12

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Latent Dirichlet allocation Topic model Relevance (law) Artificial intelligence Content (measure theory) Information retrieval Modalities Multimodal learning Natural language processing

Metrics

Cited By

25.87

FWCI (Field Weighted Citation Impact)

Refs

0.99

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Misinformation and Its Impacts

Social Sciences → Social Sciences → Sociology and Political Science

Topic Modeling

Physical Sciences → Computer Science → Artificial Intelligence

Sentiment Analysis and Opinion Mining

Physical Sciences → Computer Science → Artificial Intelligence

EXMULF: An Explainable Multimodal Content-Based Fake News Detection System

Metrics

Citation History

Topics

Related Documents

Knowledge-Aware Multimodal Explainable Fake News Detection

Comment Filtering Based Explainable Fake News Detection

Exploiting Content Characteristics for Explainable Detection of Fake News

Multimodal Fake News Detection

MFIR: Multimodal fusion and inconsistency reasoning for explainable fake news detection