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网络谐音形式单位的认知研究

发布时间:2018-06-17 12:47

  本文选题:谐音形式单位 + 知识结构 ; 参考:《湖南师范大学》2013年硕士论文


【摘要】:如今网络的发展渗透到社会的方方面面,网络交流成为交流模式的主流。网络谐音形式单位作为网络语言的一种变体越来越受到人们的关注。近年来,众多学者从修辞、社会文化心理、语用学等角度对其进行了研究,但是从认知角度对网络语中谐音词形式单位的系统性研究很少。 本文以网络语中谐音形式单位为研究对象,以知识结构理论,概念转喻和概念隐喻理论为理论基础,运用定性与定量相结合的方法,从分类、特征、生成和识解四个方面对网络语中的谐音形式单位进行了探讨。试图分析网络谐音形式单位的谐音借用理据,探究其生成和识解的认知过程,并归纳出统一的认知框架。有助于人们更好的理解和使用网络语中的谐音形式单位。 本文研究发现,网络谐音形式单位具有以下特点。依据语言的外部形势特征,可以分为四类:语言谐音形式单位、数字谐音形式单位、字母谐音形式单位和语码混用谐音形式单位四类。特征方面,网络谐音形式单位在网络交流中表现出经济简洁、幽默讽刺、新颖形象和表达委婉四个特征。网络语境下,谐音形式单位的生成和识解过程就是语言使用者对其进行的认知加工过程。以语音邻近关系(即语音的相似或者相同)为谐音借用的基础,以物质基础、网络交际语境特征社会文化和心理以及语言使用者的知识结构为依据,以概念隐喻和概念转喻为于段。 通过对网络谐音形式单位的分析,本文认为,日常生活中的一般或特殊经验是网络语谐音形式单位生成和理解的认知基础。语音邻近的基础上,网民们借用指称他们所熟悉的事物或行为的语言单位来表达、命名新事物和新概念,借助概念隐喻和概念转喻生成了各种谐音形式单位。依靠人们的知识结构(即相关的背景知识和语言知识),不需要额外的注解就能获得谐音形式单位的意义。此外,网络谐音形式单位是一种新出现的语言变体,仍处在发展变化的阶段,我们应该用一种历史和发展的语言观来看待这一新兴的语言现象,而不是对其存在和使用盲目地排斥,以便有效地展开网络语言交流。
[Abstract]:Nowadays, the development of network permeates all aspects of society, network communication becomes the mainstream of communication mode. As a variant of network language, network homophonic unit has attracted more and more attention. In recent years, many scholars have studied it from the perspectives of rhetoric, sociocultural psychology, pragmatics and so on. However, there is little systematic research on the form units of homophonic words in network language from the cognitive point of view. Based on the theory of knowledge structure, Conceptual metonymy and Conceptual metaphor, this paper takes the homophonic form unit in network language as the research object, and applies the method of combining qualitative and quantitative, classifying and characterizing. This paper discusses the homophonic form units in network language from four aspects of generation and interpretation. This paper attempts to analyze the motivation of homophonic borrowing of network homophonic units, to explore the cognitive process of its generation and interpretation, and to conclude a unified cognitive framework. It helps people to better understand and use homophonic units in internet language. In this paper, we find that the network homophonic units have the following characteristics. According to the characteristics of the external situation of language, it can be divided into four categories: language homophonic form unit, numerical homophonic form unit, alphabetical homophonic form unit and code-mixed homophonic form unit. In terms of features, network homophonic units show four characteristics: economic simplicity, humor, irony, novel image and euphemism. In the network context, the generation and interpretation of homophonic units is the cognitive process of language users. On the basis of phonological proximity (that is, phonetic similarity or similarity), homophonic borrowing, material basis, social, cultural and psychological characteristics of network communication context and the knowledge structure of language users. Conceptual metaphor and conceptual transformation are used in the paragraph. Through the analysis of the network homophonic form units, this paper holds that the common or special experience in daily life is the cognitive basis for the generation and understanding of the network homophonic form units. On the basis of phonological proximity, Internet users use linguistic units that refer to things or behaviors they are familiar with to express, name new things and new concepts, and generate various homophonic units by means of conceptual metaphors and conceptual metonymy. Depending on people's knowledge structure (that is, relevant background knowledge and language knowledge), the meaning of homophonic units can be obtained without additional annotations. In addition, the network homophonic form unit is a new language variant and is still in the stage of development and change. We should look at this emerging language phenomenon with a historical and developing linguistic perspective. Instead of blindly rejecting their existence and use, they can effectively communicate with each other.
【学位授予单位】:湖南师范大学
【学位级别】:硕士
【学位授予年份】:2013
【分类号】:H136

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