SAFE: Similarity-Aware Multi-modal Fake News Detection

Xinyi Zhou, Jindi Wu, Reza Zafarani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Effective detection of fake news has recently attracted significant attention. Current studies have made significant contributions to predicting fake news with less focus on exploiting the relationship (similarity) between the textual and visual information in news articles. Attaching importance to such similarity helps identify fake news stories that, for example, attempt to use irrelevant images to attract readers’ attention. In this work, we propose a Similarity-Aware FakE news detection method (SAFE) which investigates multi-modal (textual and visual) information of news articles. First, neural networks are adopted to separately extract textual and visual features for news representation. We further investigate the relationship between the extracted features across modalities. Such representations of news textual and visual information along with their relationship are jointly learned and used to predict fake news. The proposed method facilitates recognizing the falsity of news articles based on their text, images, or their “mismatches.” We conduct extensive experiments on large-scale real-world data, which demonstrate the effectiveness of the proposed method.

Original languageEnglish (US)
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 24th Pacific-Asia Conference, PAKDD 2020, Proceedings
EditorsHady W. Lauw, Ee-Peng Lim, Raymond Chi-Wing Wong, Alexandros Ntoulas, See-Kiong Ng, Sinno Jialin Pan
PublisherSpringer
Pages354-367
Number of pages14
ISBN (Print)9783030474355
DOIs
StatePublished - 2020
Event24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020 - Singapore, Singapore
Duration: May 11 2020May 14 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12085 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020
CountrySingapore
CitySingapore
Period5/11/205/14/20

Keywords

  • Fake news
  • Multi-modal analysis
  • Neural networks
  • Representation learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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