Font Size: a A A

A Contrastive Study Of Affect System Between English And Chinese Hard News

Posted on:2010-10-19Degree:MasterType:Thesis
Country:ChinaCandidate:R J XuFull Text:PDF
GTID:2178360278972276Subject:English Language and Literature
Abstract/Summary:PDF Full Text Request
Emotions,as an important aspect of human experience,are at the center of human mental and social life.In the past two decades,extensive researches have been conducted from various aspects such as cognitive linguistics,psychological linguistics, and systemic functional linguistics etc.This thesis,with Affect system,investigates the distributions and frequencies of affective resources;similarities and dissimilarities between English and Chinese by means of qualitative and quantitative study based on English and Chinese hard news corpuses.Appraisal Theory(AT) is a new approach to Discourse Analysis(DA) in Systemic Functional Linguistics,which is a part of Interpersonal Metafunction of Systemic Functional Linguistics(SFL).It is concerned with linguistic resources for and by which texts/speakers come to express,negotiate and naturalize particular inter-subjective and ultimately ideological positions(White,1998).AT concerns types of attitudes,the strength of the involved feelings and the ways in which values and readers aligned in the discourse.Appraisal Theory(AT) consists of three sub-categories:Attitude,Engagement and Graduation.Attitude is the core of AT, which can be further divided into three sub-categories:Affect,Judgment and Appreciation.This paper makes a contrastive study between English and Chinese hard news corpuses based on the sub-category of Attitude—Affect system.This study chooses 114 pieces of hard news from People's Daily and New York Times(the total number of English words are 55,572,and Chinese characters are 51, 169,both are international news).With the help of statistical tool-Systemic Coder, both qualitative and quantitative approaches are employed to make a detailed analysis. It can be clearly shown from the statistics that there are many affective resources in both Chinese and English hard news corpora,and the latter has higher frequency than the former.The similarities between two corpora are follows:among all the seven categories of Affect system,both English and Chinese hard news prefer to employ insecurity affect(in English 23%,in Chinese 22%);complex affect(in English 25%,in Chinese 23%).In terms of negative affect,there are similar frequencies.What's more, behavioral surge,median affect,realis affect and directed affect are mostly employed, accounting for 35%,53%,33%,31%in English and 43%,50%,43%,38%in Chinese respectively.As far as the differences are concerned,with the help of 'compare files' study conducted by Systemic Coder,this paper concludes that dissatisfaction affect, behavioral surge,realis affect,and directed affect are more employed in Chinese hard news than those in English hard news(10 percent>7 percent;43 percent>35 percent; 43 percent>33 percent;38 percent>31 percent).While low affect,high affect and undirected affect are more used in English news report than in Chinese news report(7 percent>3 percent;12 percent>7 percent;6 percent>2 percent).Compared with Chinese,English prefers to employ affective resources to express reporters' emotions,arousing emotional resonance and making a better communication with readers.What's more,I manage to give reasons for the differences from social and cultural point of views.Besides,this study also reveals that some emotional Chinese words are difficult to be categorized,which needs going further study.This paper conducts a contrastive study of affective resources based on Chinese and English hard news corpora from the perspective of AT aiming to bring new light to other genres and make a contribution to the application of affect system in DA. What's more,it hopes to provide pedagogical implications to the writing, understanding and translation of news discourse.
Keywords/Search Tags:Systemic Functional Linguistics, Appraisal Theory, Affective Resources, Classifications of Affect, Hard News, Corpus
PDF Full Text Request
Related items