A multimodal fake news detection model based on crossmodal attention residual and multichannel convolutional neural networks

Information Processing & Management - Tập 58 - Trang 102437 - 2021
Chenguang Song1, Nianwen Ning1, Yunlei Zhang2, Bin Wu1
1Beijing Key Laboratory of Intelligence Telecommunication Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, PR China
2North China Institute of Science and Technology, Hebei 065201, PR China

Tài liệu tham khảo

Ajao, 2018, Fake news identification on twitter with hybrid cnn and rnn models, 226 Antol, 2015, Vqa: visual question answering, 2425 Ba, J. L., Kiros, J. R., & Hinton, G. E. (2016). Layer normalization. Boididou, 2016, Verifying multimedia use at mediaeval 2016 Bondielli, 2019, A survey on fake news and rumour detection techniques, Information Sciences, 497, 38, 10.1016/j.ins.2019.05.035 Cao, J., Guo, J., Li, X., Jin, Z., Guo, H., & Li, J. (2018). Automatic rumor detection on microblogs: a survey. Cao, 2020, Exploring the role of visual content in fake news detection, 141 Castillo, 2011, Information credibility on twitter, 675 Chen, 2018, Call attention to rumors: deep attention based recurrent neural networks for early rumor detection, 40 Chen, 2019, Attention-residual network with cnn for rumor detection, 1121 Cui, 2019, Same: Sentiment-aware multi-modal embedding for detecting fake news, 4148 Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. Dungs, 2018, Can rumour stance alone predict veracity?, 3360 Guo, 2018, Rumor detection with hierarchical social attention network, 943 Gupta, 2013, Faking sandy: characterizing and identifying fake images on twitter during hurricane sandy, 729 Gupta, 2012, Evaluating event credibility on twitter, 153 Jin, 2017, Multimodal fusion with recurrent neural networks for rumor detection on microblogs, 795 Jin, 2016, News verification by exploiting conflicting social viewpoints in microblogs, 2972 Jin, 2017, Novel visual and statistical image features for microblogs news verification, IEEE Transactions on Multimedia, 19, 598, 10.1109/TMM.2016.2617078 Kakol, 2017, Understanding and predicting web content credibility using the content credibility corpus, Information Processing & Management, 53, 1043, 10.1016/j.ipm.2017.04.003 Karimi, 2018, Multi-source multi-class fake news detection, 1546 Ke, 2015, False rumors detection on sina weibo by propagation structures, 651 Khattar, 2019, Mvae: multimodal variational autoencoder for fake news detection, 2915 Kim, 2014, Convolutional neural networks for sentence classification, 1746 Kochkina, 2018, All-in-one: multi-task learning for rumour verification, 3402 Lazer, 2018, The science of fake news, Science, 359, 1094, 10.1126/science.aao2998 Ma, 2016, Detecting rumors from microblogs with recurrent neural networks, 3818 Ma, 2018, Detect rumor and stance jointly by neural multi-task learning, 585 Ma, 2018, Rumor detection on twitter with tree-structured recursive neural networks, 1980 Ma, 2019, Detect rumors on twitter by promoting information campaigns with generative adversarial learning, 3049 van der Maaten, 2008, Visualizing data using t-SNE, Journal of Machine Learning Research, 9, 2579 Mikolov, 2013, Distributed representations of words and phrases and their compositionality, 3111 Oshikawa, R., Qian, J., & Wang, W. Y. (2018). A survey on natural language processing for fake news detection. Qi, 2019, Exploiting multi-domain visual information for fake news detection Qian, 2018, Neural user response generator: Fake news detection with collective user intelligence, 3834 Rubin, 2015, Deception detection for news: three types of fakes, 83:1 Ruchansky, 2017, Csi: A hybrid deep model for fake news detection, 797 Sejeong, 2013, Prominent features of rumor propagation in online social media, 1103 Sharma, 2019, Combating fake news: a survey on identification and mitigation techniques, ACM Transactions on Intelligent Systems and Technology, 10, 21:1, 10.1145/3305260 Shu, 2019, defend: explainable fake news detection, 395 Shu, 2017, Fake news detection on social media: a data mining perspective, ACM SIGKDD Explorations Newsletter, 19, 2236, 10.1145/3137597.3137600 Shu, 2018, Understanding user profiles on social media for fake news detection, 430 Simonyan, 2015, Very deep convolutional networks for large-scale image recognition Singhal, 2020, Spotfake+: A multimodal framework for fake news detection via transfer learning (student abstract), 13915 Singhal, 2019, Spotfake: A multi-modal framework for fake news detection, 39 Slaney, 2008, Locality-sensitive hashing for finding nearest neighbors, IEEE Signal processing magazine, 25, 128, 10.1109/MSP.2007.914237 Su, 2019, Ensembles of recurrent networks for classifying the relationship of fake news titles, 893896 Tsai, 2019, Multimodal transformer for unaligned multimodal language sequences, 6558 Vaswani, 2017, Attention is all you need, 5998 Vinyals, 2015, Show and tell: a neural image caption generator, 3156 Vo, 2018, The rise of guardians: Fact-checking url recommendation to combat fake news, 275 Vo, 2019, Learning from fact-checkers: analysis and generation of fact-checking language, 335 Vosoughi, 2018, The spread of true and false news online, Science, 359, 1146, 10.1126/science.aap9559 Wang, 2018, Dkn: Deep knowledge-aware network for news recommendation, 1835 Wang, 2018, Eann: event adversarial neural networks for multi-modal fake news detection, 849 Yang, 2012, Automatic detection of rumor on sina weibo, 13:1 Yang, 1998, A study of retrospective and on-line event detection, 28 Yang, 2019, Xlnet: Generalized autoregressive pretraining for language understanding, 5753 Yu, 2017, A convolutional approach for misinformation identification, 3901 Zhang, 2019, Multi-modal knowledge-aware event memory network for social media rumor detection, 1942 Zhang, 2020, An overview of online fake news: Characterization, detection, and discussion, Information Processing & Management, 57, 102025, 10.1016/j.ipm.2019.03.004 Zhao, 2019, An image-text consistency driven multimodal sentiment analysis approach for social media, Information Processing & Management, 56, 102097, 10.1016/j.ipm.2019.102097 Zhou, 2019, Early rumour detection, 1614 Zhou, 2019, Fake news: fundamental theories, detection strategies and challenges, 836