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面向长时跨度自由叙事文本的少儿情感挖掘方法

The Rule of Children’s Sentiment Development Based on the Sentiment Analysis of Free Narrative Text
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摘要 【目的/意义】少儿情感的发展规律一直是各方关注的问题,现有研究在长期、准确和高效地收集、处理、分析情感数据上存在不足,本研究尝试采用自由叙事文本进行情感分析。【方法/过程】研究通过收集少儿从小学1年级持续到6年级的自由叙事文本数据,使用文本情感分析对叙事文本情感状态进行判别,最后使用多项式回归来研究情感发展的线性和非线性趋势。【结果/结论】结果表明,随着年级的增长,积极情感大体上呈现曲线下降趋势,消极情感呈曲线上升趋势,中性情感在整个发展过程中呈正弦型。在整体情感趋势上,女童比男童更为积极。【创新/局限】尽管存在学生本身能力限制、无法从文本中确定直接因果关系等局限,自由叙事文本情感分析依然为研究人员提供了利用“大数据+AI”技术,来便捷、准确、高效探索少儿长时跨度情感发展规律的机会。 【Purpose/significance】The rule of the development of children’s sentiment has always been a concern of various parties.However,existing researches have shortcomings in the long-term,accurate and efficient collection,processing and analysis of sentimental data.【Method/process】The research firstly collects the data of children’s free narrative text from grade 1 to grade 6 in primary school,then uses the text sentiment analysis to identify the sentimental state of narrative text,and finally uses polynomial regression to study the linear and nonlinear trend of sentimental development.【Result/conclusion】The results show that,with the increase of grades,positive sentiment generally presents a curve downward trend,negative sentiment presents a curve upward trend,and neutral sentiment presents a sinusoidal shape in the whole development process.【Innovation/limitation】Although there are limitations such as the inability to determine direct causality from the text,free-narrative text sentiment analysis still provides researchers with the opportunity to use "big data +AI" technology to conveniently,accurately and efficiently explore the rules of children’s long-span sentimental development.
作者 王一凡 张冰冰 刘梦君 潘利琴 WANG Yi-fan;ZHANG Bing-bing;LIU Meng-jun;PAN Li-qin(Education College,Central China Normal University,Wuhan 430079,China;Teachers College,Hubei University,Wuhan 430062,China;Chang Qing Shu Experimental School of Wuhan City,Wuhan 430023,China)
出处 《情报科学》 CSSCI 北大核心 2022年第3期109-116,135,共9页 Information Science
基金 湖北中小学素质教育研究中心开放基金“基于自由写作大数据的湖北小学生情感发展研究”(2020HBSZA08) 教育部重点课题“大数据智能采集终端赋能区域教育质量评测实践研究”(DHA210338)。
关键词 少儿情感 长时跨度 情感发展 情感分析 自由叙事文本 children’s sentiments a long span of time sentimental development sentiment analysis free narrative text
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