大数据背景下的学生情感词典构建方法

Construction of students' emotion lexicon in big data

学生的情感教育一直是教育界的研究热点和难点,由于学生个人情感的隐秘性,教师很难获取学生的情感状况.研究通过学生大量使用的社会交互网站中的文本信息分析学生的情感状态,核心是针对学生常用情感词构建情感词典,根据学生大量使用新词、伪词的特点,结合新浪微博提供的情感符号,以现有情感词典为基础,在动态更新的新浪微博大数据中应用文本相似度计算方法,扩充情感词典,构建符合学生语言特点和新浪微博风格的学生情感词典.词典包括情感极性和强度,为基于学生微博文本的情感感知和进一步的情感教育奠定基础.

Student emotion has been a focus in education, but due to respect for student privacy, it is difficult for teachers and tutors to catch student emotion condition. This research aims to analyze student emotion by student text in SNS （Social Network Site）. Constructing student emotion lexicon is core. As students use a large number of new-words, pseudo-words and emotional symbols of tweets, existing dictionary was expanded to construct an emotional lexicon by text similarity computing, appropriate for student language feature and twitter-style. Emotional lexicon including polarity and intensity is prepared for student emotion analysis and emotional education.