大数据环境下网络舆情文本挖掘技术研究

Research on the Text Mining Technology of Network Public Opinion in Big Data Environment

随着网络的普及,网络已经成为了人们表达意见与观点的重要平台和途径,网络舆情信息是舆情信息的重要构成。与传统舆情相比较,网络舆情具备数量大、突发性强、范围广等显著的特征。与此同时,网络舆情的信息发掘和管控处理的复杂程度也明显高于传统舆情的处理。基于大数据的环境,网络舆情信息的挖掘更加复杂,且难以实现规范化管理操作。因此,通过语义识别技术的运用,在大量的舆情信息中寻找关键因素用于处理突发事件是舆情研究的重要内容。

With the popularity of the internet,it has become an important platform and way for people to express their opinions and opinions.Network public opinion information is an important component of public opinion information.Compared with traditional public opinion,network public opinion is characterized by large quantity,strong suddenness,and wide range.At the same time,the complexity of information mining and control processing of network public opinion is significantly higher than that of traditional public opinion.Based on the environment of big data,the mining of network public opinion information is more complicated,and it is difficult to achieve standardized management operation.Therefore,through the application of semantic recognition technology,it is an important content of public opinion research to find the key factors to deal with emergencies from much public opinion information.