多维度模式探究语言中的时间距离

发布时间：2020-12-31 22:25

　　语言是心理表征的体现。一些研究发现,人们在描述不同时间距离的客体时,使用的语言在抽象性上有所区别。这类针对时间距离和语言的研究均局限于心理学框架,仅用于证实解释水平理论。本研究通过语言学研究视角,基于更多语言单位和语法特征,为时间距离和语言的关系提供进一步的阐释。多维分析将多项语言特征进行统筹结合,通过语言特征的共现模式来提取潜在的重要语言功能维度,进而分析不同文本的区别,为开放式研究不同心理距离情境下使用语言的区别提供了可行性。多维分析最早由Biber用于多种语体变异研究。经过近30年的应用和改进,多维度分析在揭示文本的语言差异上表现出了高度的灵活性和有效性。本研究将多为分析的应用拓展到了心理语言学层面。本研究基于解释水平理论框架,利用多维分析模式探究表现不同时间距离的英文文本之间的语言差别。旨在揭示自然语言和时间距离之间的功能关系。本研究基于纽约时报标注语料库,经过因子分析总结和阐释64个语言特征的共现模式,抽取了三个因子作为重要语言特征维度,分别定义为:语言低复杂度、概念抽象性和不确定性、文本逻辑性。研究分析了不同时间距离文本在以上三个维度上的差别,得出时间距离与语言复杂度,概念... 

【文章来源】：浙江大学浙江省 211工程院校 985工程院校 教育部直属院校

【文章页数】：79 页

【学位级别】：硕士

【文章目录】：
Acknowledgements
摘要
Abstract
Chapter One Introduction
    1.1 Research background
    1.2 Research purpose
    1.3 Research significance
    1.4 Organization of the thesis
Chapter Two Literature Review
    2.1 Construal level theory of temporal distance
        2.1.1 Time psychology and construal level theory
        2.1.2 Psychological distance and mental representations
        2.1.3 Temporal distance and human responses
    2.2 Psychological distance in Language
        2.2.1 Language as mental representations
        2.2.2 Psychological distance and language
    2.3 Multi-Dimensional approach
        2.3.1 Standard MD analysis
        2.3.2 MD analysis on language variations
Chapter Three Methodology
    3.1 Obtaining a dataset
        3.1.1 Text selection and classification
        3.1.2 Linguistic variable selection
    3.2 Statistical treatment
        3.2.1 Factor analysis
        3.2.2 Factor score analysis
Chapter Four Results and Discussion
    4.1 Determine factors
    4.2 Dimension interpretations
        4.2.1 Dimension 1:reduced discourse complexity
        4.2.2 Dimension 2: conceptual abstractness and uncertainty
        4.2.3 Dimension 3:textual logical relations
        4.2.4 Summary of dimensions
    4.3 Group relations along dimensions
        4.3.1 Group variations along dimension 1
        4.3.2. Group variations along Dimension 2
        4.3.3. Group variations along Dimension 3
        4.3.4. Summary of group variations on dimension scores
    4.4 Dimension scores on time series:
        4.4.1 Moving averages for dimension scores
        4.4.2 Model fitting
Chapter Five Conclusion
    5.1 Conclusion
    5.2 Limitations and Future work
References
Appendices
    Appendix Ⅰ: 64 Linguistic feature
    Appendix Ⅱ: Factor loadings for 64 linguistic features
    Appendix Ⅲ: Descriptive Statistics
        1. Descriptive statistics for 64 Linguistic Features in the Temporal Corpus
        2. Descriptive statistics for dimension scores of each temporal groups



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