Trained RPDNN LOO-CV models for early rumor detection

This is the release of our RPDNN trained LOO-CV model for early rumor detection.Dataset *_full.zip contains our trained RPDNN models that is developed to predict social media rumor in early stage.The purpose of this release is for research only and for reproducing our results in the paper.For how to load and use the model, please our Allennlp and Pytorch based source code via https://github.com/jerrygaoLondon/RPDNNFor more details, please read our paper:Gao. J., Han S., Song X., Ciravegna, F. (2020). “RP-DNN: A Tweet level propagation context based deep neural networks for early rumor detection in Social Media”, In: The LREC 2020 Proceedings. The International Conference on Language Resources and Evaluation, 11-16 May 2020, Marseille. LREC 2020.

本发布版包含我们基于 RPDNN 训练的 LOO-CV 模型，旨在早期检测社交媒体谣言。数据集 *_full.zip 包含了用于预测社交媒体早期谣言的 RPDNN 模型。本发布的目的是供研究使用，以便在论文中重现我们的结果。关于如何加载和使用该模型，请参考我们的基于 Allennlp 和 Pytorch 的源代码，代码仓库地址为 https://github.com/jerrygaoLondon/RPDNN。如需了解更多详情，请参阅我们的论文：Gao, J., Han, S., Song, X., & Ciravegna, F. (2020). “RP-DNN: 基于 Tweet 层传播上下文的深度神经网络在社交媒体早期谣言检测中的应用”，载于《LREC 2020 会议论文集》。国际语言资源与评估会议，2020年5月11日至16日，马赛。LREC 2020。