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Optical Memory and Neural Networks

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01-03-2024

Multi-Modal Co-Attention Capsule Network for Fake News Detection

Authors: Chunyan Yin, Yongheng Chen

Published in: Optical Memory and Neural Networks | Issue 1/2024

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Abstract

Most of the existing fake news identification models mainly focused on exploiting multi-modal features to enhanced performance recently. This paper proposes Multi-modal Co-Attention Capsules Network (MCCN) for fake news detection, which consists mainly of feature extraction layer, feature fusion layer and classification layer. Feature extraction layer achieves the features building of users’ profiles, multi-modal source news and comments. Feature fusion layer adopts a dual parallel Cross-Modal Co-Attentional to fuse multi-modal interactions between source news text and its attached image, Hierarchical Co-Attention to fuse the interactions among user information, source news content and comments. Classification layer adopts capsules network to realize false information identification. Experimental results on three widely used large-scale datasets show that MCCN can achieve the excellent performance by comparing with other baselines.

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Title: Multi-Modal Co-Attention Capsule Network for Fake News Detection
Authors: Chunyan Yin
Yongheng Chen
Publication date: 01-03-2024
Publisher: Pleiades Publishing
Published in: Optical Memory and Neural Networks / Issue 1/2024
Print ISSN: 1060-992X
Electronic ISSN: 1934-7898
DOI: https://doi.org/10.3103/S1060992X24010041

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