人际功能视域下语言性别差异多视角识解——基于机器学习理论的数据分析

A Multivariate Investigation of Gender and Language from an Interpersonal Metafunction Perspective:Machine Learning Theory Based Statistical Analyses

针对语言性别差异这一特殊语言现象,基于系统功能语言学话语分析方法,建立一个适用于语言性别差异分析的人际功能特征框架。采用特定人物话语语料,结合语用学相关理论,并借助于计算机科学领域中的机器学习方法——支持向量机,对所选取语料进行定量及定性分析,探究男女人物的话语风格差异,揭示人际功能特征与语言性别特征之间的联系,为语言性别差异的研究提供一个系统功能语言学视角下的新途径。研究结果表明:不同性别人物使用的语言存在一些显著的人际功能特征,这些显著特征与语言使用的社会文化语境一致性较高。因此,人际功能特征能为语言性别差异的研究提供一种极为有效的理论方法。

This paper offers an alternative to investigating gender variations across language by using the interpersonal metafunction of Halliday’s systemic functional grammar.Focusing on two male and two female characters’utterances in the Water Margins novel,we explore interpersonal language features from the MOOD and MODALITY systems with the aid of the Support Vector Machine(SVM).Our findings show gender variations in how participants use interpersonal resources and illustrate the affordances of Systemic Functional Linguistics in studying gender differences across language.Our research thus sheds light on a multi-dimensional understanding of gender and language,by using a rigorous and advanced algorithm.It also reveals the ways male and female characters’interpersonal language features are influenced by gender,character and distinct cultural and social background.