Abstract
Social media platforms such as Twitter have become a breeding ground for unverified information or rumors. These rumors can threaten people’s health, endanger the economy, and affect the stability of a country. Many researchers have developed models to classify rumors using traditional machine learning or vanilla deep learning models. However, previous studies on rumor detection have achieved low precision and are time consuming. Inspired by the hierarchical model and multitask learning, a multiloss hierarchical BiLSTM model with an attenuation factor is proposed in this paper. The model is divided into two BiLSTM modules: post level and event level. By means of this hierarchical structure, the model can extract deep information from limited quantities of text. Each module has a loss function that helps to learn bilateral features and reduce the training time. An attenuation factor is added at the post level to increase the accuracy. The results on two rumor datasets demonstrate that our model achieves better performance than that of state-of-the-art machine learning and vanilla deep learning models.- Anthology ID:
- 2020.aacl-main.3
- Volume:
- Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing
- Month:
- December
- Year:
- 2020
- Address:
- Suzhou, China
- Editors:
- Kam-Fai Wong, Kevin Knight, Hua Wu
- Venue:
- AACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 18–26
- Language:
- URL:
- https://aclanthology.org/2020.aacl-main.3
- DOI:
- Cite (ACL):
- Yudianto Sujana, Jiawen Li, and Hung-Yu Kao. 2020. Rumor Detection on Twitter Using Multiloss Hierarchical BiLSTM with an Attenuation Factor. In Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, pages 18–26, Suzhou, China. Association for Computational Linguistics.
- Cite (Informal):
- Rumor Detection on Twitter Using Multiloss Hierarchical BiLSTM with an Attenuation Factor (Sujana et al., AACL 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.aacl-main.3.pdf