(Luận văn thạc sĩ) an appraisal analysis of attitude resourses in opinion texts in cnn

MINISTRY OF EDUCATION AND TRAINING QUY NHON UNIVERSITY NGUYỄN THỊ MỘNG VÂN AN APPRAISAL ANALYSIS OF ATTITUDINAL RESOURCES IN OPINION TEXTS IN CNN h Field: English Linguistics Code: 8220201 Supervisor : Assoc Prof Dr Nguyễn Thị Thu Hiền BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC QUY NHƠN NGUYỄN THỊ MỘNG VÂN NGUỒN NGÔN NGỮ DIỄN TẢ THÁI ĐỘ TRONG CÁC DIỄN NGƠN BÌNH LUẬN TRÊN KÊNH CNN THEO LÝ THUYẾT ĐÁNH GIÁ h Chuyên ngành: Ngôn ngữ Anh Mã số: 8220201 Người hướng dẫn: PGS TS Nguyễn Thị Thu Hiền i STATEMENT OF AUTHORSHIP I hereby ceritfy that this thesis entitled “An Appraisal analysis of Attitudinal Resources in opinion texts in CNN” contains no material published elsewhere or extracted in the whole, or in part from a paper by which I have qualified for or been awarded another degree or diploma Moreover, no one‟s work has been used without acknowledgement in the paper This paper has not been submitted to award any degree or diploma in any other territory institution Binh Dinh, 2021 h Nguyễn Thị Mộng Vân ii ACKNOWLEDGEMENTS In order to complete this thesis, it is not only my efforts but also other assistance of individuals to whom I really want to offer my deepest gratitude First of all, I‟d like to express my special thanks to many people who gave me great help when I completed this thesis I am deeply thankful to my supervisor, Assoc Prof Dr Nguyễn Thị Thu Hiền, who has given me much invaluable advice and encouragement since the very beginning and has been my frequent source of many invaluable insights I am also grateful to her for reading my manuscript and helping me make the necessary changes Secondly, I am also grateful to lecturers who have given the foundation for this thesis and all the staff of the Post-graduate Department at Quy Nhon University for their encouragement, kindness and administrative assistance h Thirdly, I also want to thank my colleagues for their encouragement and support I am grateful to my family and my husband, who have helped me overcome many difficulties throughout the course and the study of this thesis Without them, I could not have overcome the trouble during this journey iii ABSTRACT This thesis presents the analysis of Attitudinal Resources in opinion texts in CNN based on the framework of Appraisal Theory by Martin and White, which is considered as a new approach to evaluating languages The study aims at discovering the linguistic expressions expressing the attitude of Journalists and interpreting linguistic features of these expressions regarding Affect, Judgment, and Appreciation The combination of quantitative and qualitative methods was applied for the data analysis The study shows that three sub-categories of Attitude are disproportionately used in the text Specifically, Judgment occupied the largest proportion, the second highest was Appreciation and Affect was found to occur at the lowest rate Besides, the research outcomes indicated that the more common employment of h Positive and Explicit than Negative and Implicit ones Finally, as for the lexical features of these resources, the findings show a difference in using noun, adjective, adverb or verb to express the attitude iv TABLE CONTENT STATEMENT OF AUTHORSHIP i ACKNOWLEDGEMENTS ii ABSTRACT iii TABLE CONTENT iv LIST OF ABBREVIATIONS vi LIST OF TABLES vii LIST OF FIGURES viii CHAPTER INTRODUCTION 1.1 Rationale 1.2 Aims and objectives 1.2.1 Aims h 1.2.2 Objectives 1.3 Research Questions 1.4 Scope of the study 1.5 Significance of the study 1.6 Organization of the study CHAPTER LITERATURE REVIEW 2.1 An overview of Appraisal 2.1.1 Engagement 2.1.2 Graduation 2.1.3 Attitude 2.2 Previous Studies 22 2.3 Summary 26 CHAPTER RESEARCH METHODOLOGY 27 3.1 Research method 27 v 3.2 Description of data 27 3.3 Data Analysis 28 3.4 Research procedures 29 3.5 Reliability and validity in the research 29 CHAPTER FINDINGS AND DISCUSSION 30 4.1 General findings of the use of Attitudinal resources in opinion texts 30 4.2 Affect in opinion texts in CNN 33 4.2.1 Frequency of Affect and its subcategories in opinion texts in CNN 33 4.2.2 Linguistic features of Affect values in opinion texts in CNN 38 4.3 Judgment in opinion texts in CNN 43 4.3.1 Sub-categories with Social Esteem and Social Sanction 43 4.3.2 Linguistic features of Judgment values in opinion texts in h CNN 48 4.4 Appreciation in Opinion texts in CNN 53 4.4.1 Sub-categories with Appreciation in Opinion texts in CNN 54 4.4.2 Linguistic features of Appreciation values in opinion texts in CNN 57 CHAPTER CONCLUSIONS AND IMPLICATIONS 63 5.1 Summary of the findings 63 5.2 Implications 65 5.3 Limitations and Suggestions for Further Study 65 REFERENCES 66 vi LIST OF ABBREVIATIONS AT: Apparaisal Theory SFL: Systemetic Functional Linguistics Instance: Ins (-) : Negative (+) : Positive h vii LIST OF TABLES Table 2.1 Grammatical realizations of Affect 12 Table 2.2 Sub-systems of Affect (Martin & White, 2005: 51) 14 Table 2.3 Judgements of esteem and sanction (Martin & White, 2005: 53) 18 Table 2.4 Types of Appreciation (Martin and White, 2005: 56) 21 Table 4.1 Authorial and Non-authorial Affect in opinion texts in CNN 40 Table 4.2 The detailed distribution of Social Esteem and Social Sanction in opinion texts in CNN 44 h viii LIST OF FIGURES Figure 2.1 An Overview of appraisal resources (Martin & White, 2005: 38) Figure 2.2 An overview of Attitude resources 10 Figure 2.3 Judgment and Appreciation as Institutionalized Affect 11 Figure 4.1 Frequency of Affect, Judgement and Appreciation in opinion texts in CNN 31 Figure 4.2 Sub-categories of Affect in opinion texts in CNN 34 Figure 4.3 Positive and Negative Affect in opinion texts in CNN 38 Figure 4.4 Lexical features of Affect resources in opinion texts in CNN 42 Figure 4.5 Explicit and Implicit Judgment in opinion texts in CNN 49 Figure 4.6 Positive and Negative Judgments in opinion texts in CNN 50 Figure 4.7 Lexical features of Judgment resources in opinion texts h in CNN 52 Figure 4.8 The distribution of Reaction, Composition and Valuation 54 Figure 4.9 Explicit and Implicit Appreciation in opinion texts 58 Figure 4.10 Positive and Negative Appreciation in opinion texts 59 Figure 4.11 Lexical features of Appreciation resources in opinion texts in CNN 61