基于RNN的社交网络谣言预测技术研究
Research on Social Network Rumor Prediction Technology Based on RNN

随着科技的迅速发展与经济实力的卓越进步，大数据时代在悄然无息中走进我们的生活，随之而来的是互联网的进步与信息获取的便利，但是，谣言也逐渐地在社交平台上泛滥，严重影响了网络生态环境的健康发展，使得人们难以在种类纷繁的、质量参差不齐的信息中辨别出可靠的信息，大大降低了人们获取信息的质量。本文借助RNN与CNN结合的方法实施谣言预测，即通过CNN将谣言信息向量化，并输入RNN模型进行谣言的预测。根据给定的数据进行高效的训练，从而达到及时地、有效地甄别谣言的目的。
With the rapid development of science and technology and the remarkable progress of economic strength, the era of big data has quietly entered our lives, followed by the progress of the Internet and the convenience of obtaining information. However, rumors have gradually spread on social platforms, seriously affecting the healthy development of the network ecological environment. It makes it difficult for people to distinguish the reliable information among the various kinds and uneven quality information, which greatly reduces the quality of people’s access to information. The method combining RNN and CNN is used to implement rumor prediction and Python machine learning. We utilize CNN to generate feature vector for the rumor information by CNN model, then input the feature vectors to RNN model to obtain the prediction result. Finally, efficient training is carried out according to the given data, so as to achieve the purpose of timely and effective predic-tion of rumors.