基于机器学习的学生社区网络平台评论情感分析

Sentiment Analysis of Comments on Student Community Network Platform Based on Machine Learning

为了识别高校学生在虚拟社交平台中的言论情感,本文提出了一种利用机器学习算法对学生的社区网络平台短文本进行自然语言处理的方法,通过采用情感识别办法,对研究数据进行了分析和讨论。结果表明,在本文的情感分析任务中,五种模型均取得了良好的效果,这证明了机器学习算法能够对学生言论进行动态的定性分析,能帮助教师及时了解学生的思想动态。

In order to identify the sentiment of university students’speech in virtual social platforms,this paper proposes a method for natural language processing of students’short texts on community network platforms using machine learning algorithms,and by adopting a sentiment recognition approach,the research data are analyzed and discussed.The results show that all five models achieved good results in the sentiment analysis task in this paper,which proves that machine learning algorithms are able to perform dynamic qualitative analysis of student speech,and thus can help teachers to understand students’thought dynamics in time.