外国语

外国语 ›› 2022, Vol. 45 ›› Issue (5): 65-74.

• 语言研究 • 上一篇    下一篇

基于情感倾向分析的语义韵强度算法探析

李晶洁1, 胡奕阳2, 陶然3   

  1. 1. 上海外国语大学 语料库研究院, 上海 201620;
    2. 东华大学 外语学院, 上海 201620;
    3. 东华大学 计算机科学与技术学院, 上海 201620
  • 收稿日期:2021-03-10 出版日期:2022-09-20 发布日期:2022-10-09
  • 作者简介:李晶洁(1981-),女,博士,教授。研究方向:语料库语言学、学术话语研究、计量语言学。胡奕阳(1995-),女,硕士。研究方向:语料库语言学。陶然(1975-),男,硕士,高级实验师。研究方向:自然语言处理和数据挖掘。
  • 基金资助:
    上海市哲学社会科学规划项目"基于人本智能的学术话语助写系统构建研究"（2021BYY001）

Calculation of Semantic Prosody Strength Based on Sentiment Analysis

LI Jingjie1, HU Yiyang2, TAO Ran3   

  1. 1. Institute of Corpus Studies and Applications, Shanghai International Studies University, Shanghai 201620, China;
    2. College of Foreign Languages, Donghua University, Shanghai 201620, China;
    3. College of Computer Science and Technology, Donghua University, Shanghai 201620, China
  • Received:2021-03-10 Online:2022-09-20 Published:2022-10-09

摘要： 本文将语言情感分析技术应用于语义韵强度计算，并在扩展意义单位的理论框架下，探讨语义韵强度更精细测量的可行性和操作性。现有语义韵强度测量方法多是基于频数的极性占比算法，其共性是默认同一极性范畴的搭配词具有等值的态度或情感强度，却无法深入语义韵极性范畴内部，对同一极性下的语义韵强度做更细致的差异化分析。辅以情感分析技术支撑的语义韵强度测量，能够更精细地展示不同节点词之间，以及同一节点词在不同搭配型式、语义趋向下的语义韵特征异同，帮助研究者更深入了解节点词共现语境的态度意义氛围，以及扩展意义单位构成元素之间的关联。

关键词: 自然语言情感分析, 语义韵强度, 扩展意义单位, 语义趋向, 搭配型式

Abstract: This article applies natural language sentiment analysis technology to the calculation of semantic prosody strength, with a view to exploring the feasibility and operability of a more precise measurement of semantic prosody under the theoretical framework of extended units of meaning.The existing measurement methods of semantic prosody strength are mostly based on the frequency-based polarity ratio calculation.The commonality of this type of methods is that collocation words in the same polarity category have equivalent attitudinal or emotional associations, but they cannot penetrate the inside of a polarity category and perform a more detailed and differentiated analysis of specific semantic prosody strengths under the same polarity category.We hope that the high-precision semantic prosody strength value supported by sentiment analysis technology can more finely describe the similarities and differences of semantic prosodies among different node words and for the same node word in different collocation patterns and semantic preferences, and hence help us better understand the consistent aura of meaning pervading the context around the node word, and the relationship between the elements of extended units of meaning.

Key words: natural language sentiment analysis, strength of semantic prosody, extended unit of meaning, semantic preference, collocation pattern

中图分类号: 

  • H03
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