Health rumors detection based on deep learning

Wei Zhao, Qian Zhan, Yujin Yan
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Abstract

In this paper, we use the open source paddlepaddle framework, choose the LSTM algorithm to build a health rumor detection platform, and train the model through a self-built Chinese health rumor data set, so as to predict whether the social media information is a health type rumor, and provide a theoretical exploration and effective implementation for the automatic judgement of health rumors.
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基于深度学习的健康谣言检测
本文采用开源的paddlepaddle框架,选择LSTM算法构建健康谣言检测平台,并通过自建的中国健康谣言数据集对模型进行训练,从而预测社交媒体信息是否为健康类谣言,为健康谣言的自动判断提供理论探索和有效实现。
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