An optimal detection of fake news from Twitter data using dual-stage deep capsule autoencoder

References

• Agarwal, A., Mittal, M., Pathak, A., & Goyal, L. M. (2020). Fake news detection using a blend of neural networks: An application of deep learning. SN Computer Science, 1(3), 1–9. https://doi.org/10.1007/s42979-020-00165-4
   Google Scholar
• Ahmad, I., Yousaf, M., Yousaf, S., Ahmad, M. O., & Uddin, M. I. (2020). Fake news detection using machine learning ensemble methods. Complexity, 2020, 1–11. https://doi.org/10.1155/2020/8885861
   Web of Science ®Google Scholar
• Ahmed, H. (2017) Detecting opinion spam and fake news using n-gram analysis and semantic similarity. PhD diss.
   Google Scholar
• Alonso, M. A., Vilares, D., Gómez-Rodríguez, C., & Vilares, J. (2021). Sentiment analysis for fake news detection. Electronics, 10(11), 1348. https://doi.org/10.3390/electronics10111348
   Web of Science ®Google Scholar
• Braşoveanu, A. M. P., & Andonie, R. (2021). Integrating machine learning techniques in semantic fake news detection. Neural Processing Letters, 53(5), 3055–3072. https://doi.org/10.1007/s11063-020-10365-x
   Web of Science ®Google Scholar
• Chauhan, T., & Palivela, H. (2021). Optimization and improvement of fake news detection using deep learning approaches for societal benefit. International Journal of Information Management Data Insights, 1(2), 100051. https://doi.org/10.1016/j.jjimei.2021.100051
   Google Scholar
• Choudhary, A., & Arora, A. (2021). Linguistic feature based learning model for fake news detection and classification. Expert Systems with Applications, 169, 114171. https://doi.org/10.1016/j.eswa.2020.114171
   Web of Science ®Google Scholar
• Dou, Y., Shu, K., Xia, C., Yu, P. S., & Sun, L. (2021) User preference-aware fake news detection. In Proceedings of the 44th Internat ACM SIGIR Conf on Res and Develop in Inform Retrieval (pp. 2051–2055).
   Google Scholar
• Faustini, P. H. A., & Covoes, T. F. (2020). Fake news detection in multiple platforms and languages. Expert Systems with Applications, 158, 113503. https://doi.org/10.1016/j.eswa.2020.113503
   Web of Science ®Google Scholar
• Gangireddy, S. C. R., Long, C., & Chakraborty, T. (2020). Unsupervised fake news detection: A graph-based approach. Procee of the 31st ACM Confe on Hypertext and Social Media, 75–83.
   Google Scholar
• Goldani, M. H., Momtazi, S., & Safabakhsh, R. (2021). Detecting fake news with capsule neural networks. Applied Soft Computing, 101, 106991. https://doi.org/10.1016/j.asoc.2020.106991
   Web of Science ®Google Scholar
• Goldani, M. H., Safabakhsh, R., & Momtazi, S. (2021). Convolutional neural network with margin loss for fake news detection. Information Processing & Management, 58(1), 102418. https://doi.org/10.1016/j.ipm.2020.102418
   Web of Science ®Google Scholar
• Hakak, S., Alazab, M., Khan, S., Gadekallu, T. R., Maddikunta, P. K. R., & Khan, W. Z. (2021). An ensemble machine learning approach through effective feature extraction to classify fake news. Future Generation Computer Systems, 117, 47–58. https://doi.org/10.1016/j.future.2020.11.022
   Web of Science ®Google Scholar
• Huang, Y. F., & Chen, P. H. (2020). Fake news detection using an ensemble learning model based on self-adaptive harmony search algorithms. Expert Systems with Applications, 159, 113584. https://doi.org/10.1016/j.eswa.2020.113584
   Web of Science ®Google Scholar
• Islam, N., Shaikh, A., Qaiser, A., Asiri, Y., Almakdi, S., Sulaiman, A., Moazzam, V., & Babar, S. A. (2021). Ternion: An autonomous model for fake news detection. Applied Sciences, 11(19), 9292. https://doi.org/10.3390/app11199292
   Google Scholar
• Kaliyar, R. K., Goswami, A., & Narang, P. (2021). FakeBERT: Fake news detection in social media with a BERT-based deep learning approach. Multimedia Tools and Applications, 80(8), 11765–11788. https://doi.org/10.1007/s11042-020-10183-2
   PubMed Web of Science ®Google Scholar
• Kaliyar, R. K., Goswami, A., Narang, P., & Sinha, S. (2020). Fndnet–a deep convolutional neural network for fake news detection. Cognitive Systems Research, 61, 32–44. https://doi.org/10.1016/j.cogsys.2019.12.005
   Web of Science ®Google Scholar
• Kaur, S., Kumar, P., & Kumaraguru, P. (2020). Automating fake news detection system using multi-level voting model. Soft Computing, 24(12), 9049–9069. https://doi.org/10.1007/s00500-019-04436-y
   Web of Science ®Google Scholar
• Kumar, S., Asthana, R., Upadhyay, S., Upreti, N., & Akbar, M. (2020). Fake news detection using deep learning models: A novel approach. Transactions on Emerging Telecommunications Technologies, 31(2), e3767. https://doi.org/10.1002/ett.3767
   Web of Science ®Google Scholar
• Lu, Y. J., & Li, C. T. (2020). GCAN: Graph-aware co-attention networks for explainable fake news detection on social media. arXiv Preprint arXiv: 200411648.
   Google Scholar
• MiarNaeimi, F., Azizyan, G., & Rashki, M. (2021). Horse herd optimization algorithm: A nature-inspired algorithm for high-dimensional optimization problems. Knowledge-Based Systems, 213, 106711. https://doi.org/10.1016/j.knosys.2020.106711
   Web of Science ®Google Scholar
• Mouratidis, D., Nikiforos, M. N., & Kermanidis, K. L. (2021). Deep learning for fake news detection in a pairwise textual input schema. Computation, 9(2), 20. https://doi.org/10.3390/computation9020020
   Web of Science ®Google Scholar
• Nasir, J. A., Khan, O. S., & Varlamis, I. (2021). Fake news detection: A hybrid CNN-RNN based deep learning approach. International Journal of Information Management Data Insights, 1(1), 100007. https://doi.org/10.1016/j.jjimei.2020.100007
   Google Scholar
• Nguyen, V. H., Sugiyama, K., Nakov, P., & Kan, M. Y. (2020). Fang: Leveraging social context for fake news detection using graph representation. In Proceedings of the 29th ACM internat confer on inform & knowle manage (pp. 1165–1174).
   Google Scholar
• Ni, S., Li, J., & Kao, H. Y. (2021). MVAN: Multi-view attention networks for fake news detection on social media. IEEE Access, 9, 106907–106917. https://doi.org/10.1109/ACCESS.2021.3100245
   Web of Science ®Google Scholar
• Ozbay, F. A., & Alatas, B. (2020). Fake news detection within online social media using supervised artificial intelligence algorithms. Physica A: Statistical Mechanics and Its Applications, 540, 123174. https://doi.org/10.1016/j.physa.2019.123174
   Web of Science ®Google Scholar
• Permatasari, R. I., Fauzi, M. A., Adikara, P. P., & Sari, E. D. L. (2018) Twitter sentiment analysis of movie reviews using ensemble features based Naïve Bayes. In 2018 Interna Confer on Sustain Infor Engine and Techno (SIET) (pp. 92–95). IEEE.
   Google Scholar
• Sahoo, S. R., & Gupta, B. B. (2021). Multiple features based approach for automatic fake news detection on social networks using deep learning. Applied Soft Computing, 100, 106983. https://doi.org/10.1016/j.asoc.2020.106983
   Web of Science ®Google Scholar
• Sheikhi, S. (2021). An effective fake news detection method using WOA-xgbTree algorithm and content-based features. Applied Soft Computing, 109, 107559. https://doi.org/10.1016/j.asoc.2021.107559
   Web of Science ®Google Scholar
• Shu, K., Mahudeswaran, D., Wang, S., & Liu, H. (2020). Hierarchical propagation networks for fake news detection: Investigation and exploitation. Proceedings of the International AAAI Conference on Web and Social Media, 14, 626–637. https://doi.org/10.1609/icwsm.v14i1.7329
   Google Scholar
• Shu, K., Wang, S., & Liu, H. (2019). Beyond news contents: The role of social context for fake news detection. Proceed of the Twelfth ACM Interna Conf on Web Search and Data Mining, 312–320.
   Google Scholar
• Verma, P. K., Agrawal, P., Amorim, I., & Prodan, R. (2021). Welfake: Word embedding over linguistic features for fake news detection. IEEE Transactions on Computational Social Systems, 8(4), 881–893. https://doi.org/10.1109/TCSS.2021.3068519
   Web of Science ®Google Scholar
• Vijjali, R., Potluri, P., Kumar, S., & Teki, S. (2020). Two-stage transformer model for COVID-19 fake news detection and fact checking. arXiv Preprint arXiv: 201113253.
   Google Scholar
• Vogel, I., & Meghana, M. (2020). Fake news spreader detection on Twitter using character N-Grams. In CLEF (working notes) (Vol. 2696).
   Google Scholar
• Wang, Y., Yang, W., Ma, F., Xu, J., Zhong, B., Deng, Q., & Gao, J. (2020). Weak supervision for fake news detection via reinforcement learning. Proceedings of the AAAI Conference on Artificial Intelligence, 34(01), 516–523. https://doi.org/10.1609/aaai.v34i01.5389
   Google Scholar
• Wani, A., Joshi, I., Khandve, S., Wagh, V., & Joshi, R. (2021). Evaluating deep learning approaches for COVID-19 fake news detection. In International workshop on combating on line hostile posts in regional languages during emergency situation (pp. 153–163). Springer.
   Google Scholar
• Zhang, J., Dong, B., & Philip, S. Y. (2020). Fakedetector: Effective fake news detection with deep diffusive neural network. In 2020 IEEE 36th Internat Confere on Data Engine (ICDE), (pp. 1826–1829). IEEE.
   Google Scholar
• Zhang, X., & Ghorbani, A. A. (2020). An overview of online fake news: Characterization, detection, and discussion. Information Processing & Management, 57(2), 102025. https://doi.org/10.1016/j.ipm.2019.03.004
   Web of Science ®Google Scholar
• Zhou, X., & Zafarani, R. (2020). A survey of fake news: Fundamental theories, detection methods, and opportunities. ACM Computing Surveys, 53(5), 1–40. https://doi.org/10.1145/3395046
   Web of Science ®Google Scholar