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A Novel Hybrid Model for Cantonese Rumor Detection on Twitter

by , , , and *
College of Cybersecurity, Sichuan University, Chengdu 610064, China
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Appl. Sci. 2020, 10(20), 7093;
Received: 31 July 2020 / Revised: 21 August 2020 / Accepted: 26 August 2020 / Published: 12 October 2020
The development of information technology and mobile Internet has spawned the prosperity of online social networks. As the world’s largest microblogging platform, Twitter is popular among people all over the world. However, as the number of users on Twitter increases, rumors have become a serious problem. Therefore, rumor detection is necessary since it can prevent unverified information from causing public panic and disrupting social order. Cantonese is a widely used language in China. However, to the best of our knowledge, little research has been done on Cantonese rumor detection. In this paper, we propose a novel hybrid model XGA (namely XLNet-based Bidirectional Gated Recurrent Unit (BiGRU) network with Attention mechanism) for Cantonese rumor detection on Twitter. Specifically, we take advantage of both semantic and sentiment features for detection. First of all, XLNet is employed to produce text-based and sentiment-based embeddings at the character level. Then we perform joint learning of character and word embeddings to obtain the words’ external contexts and internal structures. In addition, we leverage BiGRU and the attention mechanism to obtain important semantic features and use the Cantonese rumor dataset we constructed to train our proposed model. The experimental results show that the XGA model outperforms the other popular models in Cantonese rumor detection. The research in this paper provides methods and ideas for future work in Cantonese rumor detection on other social networking platforms. View Full-Text
Keywords: online social networks; rumor detection; Cantonese; XGA model online social networks; rumor detection; Cantonese; XGA model
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MDPI and ACS Style

Chen, X.; Ke, L.; Lu, Z.; Su, H.; Wang, H. A Novel Hybrid Model for Cantonese Rumor Detection on Twitter. Appl. Sci. 2020, 10, 7093.

AMA Style

Chen X, Ke L, Lu Z, Su H, Wang H. A Novel Hybrid Model for Cantonese Rumor Detection on Twitter. Applied Sciences. 2020; 10(20):7093.

Chicago/Turabian Style

Chen, Xinyu, Liang Ke, Zhipeng Lu, Hanjian Su, and Haizhou Wang. 2020. "A Novel Hybrid Model for Cantonese Rumor Detection on Twitter" Applied Sciences 10, no. 20: 7093.

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