(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 Field: English Linguistics Code: 8220201 Supervisor : Assoc Prof Dr Nguyễn Thị Thu Hiền download by : skknchat@gmail.com 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 Chuyên ngành: Ngôn ngữ Anh Mã số: 8220201 Người hướng dẫn: PGS TS Nguyễn Thị Thu Hiền download by : skknchat@gmail.com 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 Nguyễn Thị Mộng Vân download by : skknchat@gmail.com 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 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 download by : skknchat@gmail.com 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 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 download by : skknchat@gmail.com 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 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 download by : skknchat@gmail.com 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 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 download by : skknchat@gmail.com vi LIST OF ABBREVIATIONS AT: Apparaisal Theory SFL: Systemetic Functional Linguistics Instance: Ins (-) : Negative (+) : Positive download by : skknchat@gmail.com 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 download by : skknchat@gmail.com 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 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 download by : skknchat@gmail.com 56 be evaluated based on Balance and Complexity As can be seen from Figure 4.8, the rate of instances of Composition Appreciation is 278, amounting to 33% The following examples of Composition are presented as follows (S42O22) Both in Arkansas and across the country, the abortion rate for people of color is disproportionately high (Appreciation, Balance) partly, no doubt because of the racism and limited opportunities facing some who might prefer to bring pregnancies to term It is apparent that the adjective “high‖ in S42O22 expresses the abortion rate for people of color in Arkansas and across the country because of the racism and limited opportunities facing people who like to bring pregnancies to term (S53O23) Of course, it can't be that simple (Appreciation, Complexity) Many Americans don't "accept" the Supreme Court's decisions on guns, campaign finance or voting rights It's hard (Appreciation, Complexity) to imagine Arkansas passing a law specifically geared toward getting the Supreme Court to rethink all those decisions In S53O23, “it can't be that simple‖ and “it's hard‖ are used to express the disagreement of the Supreme Court's decisions on guns, campaign finance or voting rights toward getting the Supreme Court to rethink all those decisions through a law specifically geared 4.4.1.3 Valuation As shown in Figure 4.8, the number of Valuation values is 202, accounting for 24% The following example of Valuation Appreciation is download by : skknchat@gmail.com 57 presented as follow (S25O6) In the eyes of most, Donald Trump's presidency saw the European Union's most important (+Appreciation, Valuation) ally vacillate between uninterest and outright aggression It is apparent that the phrase “most important‖ in S25O6 is applied to express the importance of the European Union ally vacillate between uninterest and outright aggression from Donald Trump's presidency 4.4.2 Linguistic features of Appreciation values in opinion texts in CNN After some figures of occurrence frequency of different sub-categories of Appreciation were revealed, this section focuses on some linguistic features of this resources in terms of Implicit/ Explicit appearance, Positive/ Negative, Authorial/ Non-authorial and lexical features used to express the feelings or emotions 4.4.2.1 Explicit and Implicit Appreciation in opinion texts Similar to expressing feelings and judging people‟s character, evaluating inanimate things can be used Explicitly or Implicitly In opinion texts, both Explicit and Implicit Appreciation can be found The figure below illustrates the use of Explicit and Implicit Appreciation in opinion texts download by : skknchat@gmail.com 58 Appreciation 19.2% Explicit Implicit 80.8% Figure 4.9 Explicit and Implicit Appreciation in opinion texts Figure 4.9 shows that the percentage of Explicit Appreciation is much higher than that of Implicit Appreciation In particular, in 40 texts analyzed, Explicit Appreciation accounts for 80.8% while Implicit Appreciation makes up 19.2% The following examples illustrate the use of this resource (S12O7) The US has already spent trillions of dollars in an attempt to head off a total economic collapse, and it will take years before the final bill is totaled If the global catastrophe of Covid-19 (Implicit, Appreciation) was abetted by intentional wrongdoing or reckless indifference on the part of the Chinese government and its senior officials, it should not be left to American corporations, business owners and taxpayers to bear the brunt of the resulting harm It is noticeable that the explicit and implicit appreciation is used in the extracts above The phrase “the global catastrophe of Covid-19‖ is an Implicit one because it implies the widespread power which the catastrophe of Covid-19 is recognized (S9O35)"The relationship was not perfect (Explicit, Appreciation) download by : skknchat@gmail.com 59 before Trump took office Both [Barack] Obama and [George W.] Bush before him had shifted their geopolitical focus to the Middle East and China," said Tyson Barker, a former State Department official under Obama It can be seen that the adjective “perfect‖ is explicitly used to express relationship between Obama and Buss before Trump‟s office 4.4.2.2 Positive and Negative Appreciation in opinion texts Like Affect and Judgment, things can be appreciated positively or negatively, directly or indirectly (Martin and Rose, 2007) The figure below indicates the use of positive and negative Appreciation of opinion texts 80% 69% 60% 40% 31% 20% 0% Appreciation Positive Negative Figure 4.10 Positive and Negative Appreciation in opinion texts Appreciation is divided into positive and negative evaluations As presented in Figure 4.10 of 842 instances of Appreciation in opinion texts, there are 261 negative instances, accounting for 31% and the rest with 69% of positive ones with 581 instances These statistics suggest that positive instances of Appreciation are much more dominant than negative instances from all 40 texts collected (S15O38) In a health care setting, providing doctors, nurses and download by : skknchat@gmail.com 60 patients with somewhere to clean their hands is one of the most effective (Appreciation, Valuation), ways to halt the spread of disease It is obvious that the adjective ―the most effective‖ in S15O38 is applied to show the positive attitude towards a good health care setting where doctors, nurses and patients can clean their hands (S39O29) As Arizona Secretary of State Katie Hobbs explained, the "process being used is a significant (Appreciation, Valuation) departure from standard best practices utilized by jurisdictions and experts across the county, including here in Arizona, and raise serious doubt about the accuracy and reliability of any result of this process." It is worth the attention that the adjective “significant” in S39O29 is used to express the process being used as an important departure from practices used by experts and jurisdictions (S34O33) It's a small fraction of what's been spent on personal protective equipment this year alone, and it would ensure hospitals and health centers in poor (-Negative, Appreciation, Adjective) countries have clean water for a decade It can be seen that the adjective “poor‖ in S34O33 is used to describe the fact that there are still many countries in the world suffering from poverty Therefore, the word “poor‟ is a negative evaluation of the conditions of many countries in the world 4.2.2.3 Lexical features of Appreciation resources in opinion texts in CNN In terms of Appreciation, there are many types of words such as Nouns, Adjectives, Verbs, Adverbs and Phrases found in Appreciation resources in download by : skknchat@gmail.com 61 opinion texts in CNN The following figure shows the distribution of types of words of Appreciation resources in opinion texts in CNN Appreciation 0% 0% 36.80% Nouns Adjectives Adverbs 63.20% verbs Figure 4.11 Lexical features of Appreciation resources in opinion texts in CNN As seen in Figure 4.11, Appreciation resources appear only in two types of word classes, namely Adjective and Noun with a different proportion While Adjective leads the rank with 63.2%, Noun takes the second position, accounting for 36.8% Adverbs and Verbs are not used as Appreciation Their uses can be seen more clearly in the following examples (S32O33) If the institutional foundations underpinning European stability (Appreciation, Noun) fall back into place, then the EU has some space to think more about the other elements of "strategic autonomy" (S25O19) Another worrying (Appreciation, Adjective) factor is that the age profile of Covid-19 victims has shifted significantly, with more than 60% of infections in the US now under 50 It is clear that the word classes “stability‖ and ―worrying‖ in the above examples are Noun and Adjective used in Appreciation resources download by : skknchat@gmail.com 62 In sum, the findings of Appreciation shows that this attitude resource ranks the second compared with the other two resources All three sub types of Appreciation, namely Reaction, Composition and Valuation appear with the different proportion Most of these are positive attitude resources which are used more explicitly rather than implicitly As for the lexical features, only adjectives which account for 63.2% are used dorminantly The appearance of Noun functioning as this resource is very limited No Verbs and Adverbs are used as Appreciation download by : skknchat@gmail.com 63 CHAPTER CONCLUSIONS AND IMPLICATIONS The previous chapters have presented the necessary information about Attitude Resources used in opinion texts of CNN This chapter will bring a summary of the findings and also suggest some implications Finally, some limitations and recommendations for further studies are presented as the last parts 5.1 Summary of the findings It can be seen that ―Appraisal analysis of Attitudinal Resources in opinion texts in CNN‖ is the study of the all features of Attitude Resources used in opinion texts based on the theoretical background from the perspective of the Appraisal framework developed by Martin and White (2005) From the analysis of 40 samples collected, the study reveals and discusses a lot of qualitative and quantitative information about three attitudinal values in CNN opinion texts It can be said that the study has successfully answer the three research questions As regards research question about what Attitude Resources are used in opinion texts in CNN, the findings in Chapter show that the writers of these texts used a wide range of three types: Affect, Judgment, and Appreciation in providing evaluations and comments to readers However, the rate of distribution of the subtypes is different The common feature shared is that Appreciation items are dominant, followed by Judgment which ranks second and Affects occurs at the lowest rate in the two corpora These findings also indicate that writers mainly focus on describing the things, the events, or the issues rather than showing the emotions or feelings of people involved download by : skknchat@gmail.com 64 As for research question 2, about the frequency of the three sub-types of attitudinal resources used in opinion texts in CNN, the findings show that the subcategories of all three sub-types appear disaproportiontely in the data, In terms of Affect, four sub-categories, namely Un/Happiness, Dis/Inclination, In/Security, and Dis/Satisfaction exist in the data with the dominant figure falling into In/Security More specifically, the writers use more Dis/Satisfaction and In/Security than Dis/Inclination and Un/Happiness Meanwhile, Dis/Inclination is the lowest in percentage and Un/Happiness as well As regards Judgment, the opinion texts involved two sub-categories, namely Social Sanction and Social Esteem The most commonly used judgment value in the samples is the Social Esteem Judgment The predominant use of Social Esteem might explain that the writers tend to emphasise the information-conveying function, which is primarily concerned with facts and truth-values In terms of Appreciation, the high percentage of Reaction values in the Appreciation subtype implies that writers tend to focus most on evaluating the quality and the impact of the background information about potential readers often want to read For question 3, “What are the linguistic features of these attitudinal resources used in opinion texts in CNN?”, it can be seen that the realization of linguistic features in the opinion text has yielded several interesting points Firstly, despite the difference in the occurrence, all the Affect, Judgment and Appreciation values are used more more explicitly than implicitly In addition, more positive evaluations in opinion texts can be seen in Appreciation, Judgement and Affect than the negative ones Finally, the distribution of word classes such as Nouns, Verbs, Adjectives and Adverbs are differently employed as the three Attitude resources download by : skknchat@gmail.com 65 5.2 Implications The study has uncovered sub-types of attitudinal resources in opinion texts of CNN Hopefully, the findings of the study can be of help to language learners of post graduate level This study will deepen their knowledge of Appraisal and the features of the evaluative language employed by writers in their opinion texts Additionally, the English data utilized in this study were collected from reliable sources by the native writers, so this study can be practical for English learners in applying the evaluative language in their writing For scholars interested in AT and Interpersonal meaning explored from attitudinal values, this study contributes a modest part to the knowledge of the evaluative language What is more, the study is expected to reaffirm the importance of Apprail Theory in analyzing and evaluating attitudinal resources in opinion texts in CNN 5.3 Limitations and Suggestions for Further Study In this thesis, the author applied the AT of Martin and White (2005) to analyze the attitudinal resources in opinion texts in CNN Due to limitations in the number of samples and scope of an M.A thesis, a complete description of this genre could not be done, leading to tentative conclusions rather than generalizations The limitation is the scope of the study since the study focuses just on analyzing the Attitude system instead of all the three Appraisal Resources More specifically, the researcher only described the Attitudinal Resources employed in the data rather than other Appraisal items such as Engagement and Graduation Based on these limitations, I would like to offer two suggestions for further research, namely an investigation into the use of Graduation in opinion texts and another study on Engagement of the same genre download by : skknchat@gmail.com 66 REFERENCES Alamsya, A., Rahmah, W and Irawan, H (2015) Sentiment Analysis Based on Appraisal Theory for Marketing Intelligence in Indonesia’s Mobile Market Journal of Theoretical and Applied Information Technology Allison, D and S.M Wu (2005) Evaluative expressions in analytical arguments: aspects of appraisal in assigned English language essays Journal of Applied Linguistics 2(-1), 105-127 Caldwell, D (2009) Working Your Words Australian review of applied linguistics, 2(2), 13.1-13.17 V D Duc (2011) “Style, Structure and Ideology in English and Vietnamese Business Hard News Reporting – A Comparative Study‖ Ph.D Thesis University of Adelaide V D Duc (2017) Appraisal – An Approach to Discourse Analysis Tạp Chí Khoa Học Ngơn Ngữ Văn Hóa, 1(1), 13–24 Halliday, M A K 2004/1994 An Introduction to Functional Grammar London: Edward Arnold (2004 third edition revised by C M I M Matthiessen) N T T Hien (2016) An Appraisal Study of Social Attitudes in News towards President Obama‟s Visit to Vietnam VNU Journal of Science: Foreign Studies, 32(4), 21-29 Lam, S L., & Crosthwaite, P (2018) APPRAISAL resources in L1 and L2 argumentative essays: A contrastive learner corpus-informed study of evaluative stance Journal of Corpora and Discourse Studies, 1, 8–35 Li, X (2016) An Attitudinal Analysis of English Song Discourse from the Perspective of Appraisal Theory Journal of Language Teaching and Research, 7(3), 559 Retrieved from https://doi.org/10.17507/jltr 0703.17 Liu, Xinghua (2013) Evaluation in Chinese university EFL students English argumentative writing: An APPRAISAL study Electronic Journal of Foreign Language Teaching, 10(1), 40–53 Love, K (2006) Appraisal in online discussions of literary texts Text and download by : skknchat@gmail.com 67 Talk 26 (-2), 217-244 Martin, J R., and Rose, D (2003) Working with Discourse: Meaning beyond the clause New York: Continuum Martin, J R (2000) Beyond exchange: Appraisal systems in English In S Hunston and G Thompson (ads) Evaluation in Text:Authorial and the Construction of Discourse, Oxford: Oxford University Press Martin, J R & Rose, D (2007) Working with discourse: Meaning beyond the clause (2nd ed.) London: Continuum Martin, J.R., White, P.R.R., (2005) The language of Evaluation New York: Palgrave Macmillan Pascual, M., & Unger, L (2010) Appraisal in the research genres: An analysis of grant proposals by Argentinean researchers Revista Signos, 43 Wang, H (2010) Interpersonal meanings in Nobel Prise for Literature Acceptance Speeches – An Analysis from Appraisal perspective, M.A thesis, Jiangxi Normal University Zhang, Y (2018) Attitudinal Analysis of President Xi‟s Remarks at Press Conference of BRICS Xiamen Summit from the Perpective of AT Journal of Language Teaching and Research, 9(2), 385-390 V T T Van (2014) Comparative analysis of Interpersonal meaning in Letters to the Editor written in English and in Vietnamese (Master thesis), University of Quy Nhon download by : skknchat@gmail.com APPENDIX Links: https://edition.cnn.com/2020/06/12/opinions/coronavirus-mutationincreased-infectivity-haseltine/index.html https://edition.cnn.com/2020/06/13/opinions/covid-19-pandemic-federalgovernment-information-brown/index.html https://edition.cnn.com/2020/06/17/opinions/trump-pence-two-mancovid-19-gaslighting-act-ghitis/index.html https://edition.cnn.com/2020/06/17/opinions/trump-pence-two-mancovid-19-gaslighting-act-ghitis/index.html https://edition.cnn.com/2020/06/19/opinions/covid-19-pandemic-cdcguidelines-specter/index.html https://edition.cnn.com/2020/06/19/opinions/time-to-reopen-schoolscovid-19-fore/index.html https://edition.cnn.com/2020/06/20/opinions/china-needs-to-be-heldaccountable-for-covid-19s-destruction/index.html https://edition.cnn.com/2020/06/20/opinions/covid-19-unmasks-whatcancer-patients-have-long-known/index.html https://edition.cnn.com/2020/06/22/opinions/20-and-30-year-oldsspreading-covid-19-bromage/index.html 10 https://edition.cnn.com/2020/06/23/opinions/covid-19-reopeningnormal-is-a-gop-fantasy-filipovic/index.html 11 https://edition.cnn.com/2020/06/23/opinions/fixing-long-voting-lineslitt/index.html 12 https://edition.cnn.com/2020/06/23/opinions/work-visa-freeze-healthcost-trump-neill/index.html 13 https://edition.cnn.com/2020/06/24/opinions/trump-misleading-covid19-political-gain-ghitis/index.html 14 https://edition.cnn.com/2020/06/24/opinions/trump-misleading-covid19-political-gain-ghitis/index.html 15 https://edition.cnn.com/2020/06/26/opinions/governors-ignoring-covid- download by : skknchat@gmail.com surge-black-latinx-communities-munoz/index.html 16 https://edition.cnn.com/2020/06/26/opinions/coronavirus-weddingplans-medical-school-rahimi/index.html 17.https://edition.cnn.com/2020/06/27/opinions/nursing-homes-deathscovid-19-egge/index.html 18.https://edition.cnn.com/2020/06/27/opinions/kerala-coronavirusstrategy-success-mathew/index.html 19.https://edition.cnn.com/2020/06/28/opinions/donald-trumps-strangethinking-opinion-weekly-column-galant/index.html 20.https://edition.cnn.com/2020/06/29/opinions/coronavirus-pandemicresilience-francis-godfrey-mead/index.html 21.https://edition.cnn.com/2020/06/29/health/border-hospitalscoronavirus/index.html?utm_medium=social&utm_term=link&utm_so urce=fbCNNi&utm_content=2020-06-30T06%3A00%3A23 22.https://edition.cnn.com/2020/10/03/opinions/how-president-trumpwound-up-in-the-hospital-bergen/index.html 23.https://edition.cnn.com/2020/10/06/opinions/biden-gettysburg-addresscampaign-best-avlon/index.html 24.https://edition.cnn.com/2020/10/06/opinions/us-election-bidenpennsylvania-nutter/index.html 25.https://edition.cnn.com/2020/10/06/opinions/trump-caudillocomparison-castaneda/index.html 26.https://edition.cnn.com/2020/10/06/opinions/biden-town-hallcheckmates-trump-covid-louis/index.html 27.https://edition.cnn.com/2020/10/07/opinions/lindsey-graham-politicalmiscalculation-south-carolina-harrison-bailey/index.html 28.https://edition.cnn.com/2020/10/08/politics/kamala-harris-mike-pencetrump-debate/index.html 29.https://edition.cnn.com/2020/10/09/politics/donald-trump-healthcoronavirus-election-2020/index.html 30.https://edition.cnn.com/2020/10/12/opinions/science-behind-trumppence-bullying-interrupting-klitzman/index.html download by : skknchat@gmail.com 31.https://edition.cnn.com/2020/10/12/opinions/us-elections-2020michigan-conservatives-finley/index.html 32.https://edition.cnn.com/2020/10/25/health/us-coronavirussunday/index.html 33.https://edition.cnn.com/2020/11/02/politics/election-2020-donaldtrump-joe-biden-kamala-harris-battleground-states/index.html 34.https://edition.cnn.com/2020/11/13/world/canada-covid-thanksgivingsurge-trnd/index.html 35.https://edition.cnn.com/2020/11/14/europe/biden-european-uniontransatlantic-reset-analysis-intl/index.html 36.https://edition.cnn.com/2020/12/23/opinions/donald-trump-potentialbizarre-pardons-alonso/index.html 37.https://edition.cnn.com/2020/12/07/americas/venezuela-hospitalscovid-caracas-intl/index.html?iid=ob_article_organicsidebar_expansion 38.https://edition.cnn.com/2020/12/23/opinions/tedros-ghebreyesushenrietta-fore-water-access-health-facilities/index.html 39.https://edition.cnn.com/2021/01/12/politics/biden-confirmationpush/index.html 40.https://edition.cnn.com/2021/02/04/opinions/marjorie-taylor-greenedanger-to-gop-opinion-jennings/index.html download by : skknchat@gmail.com ... 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 ... as an Affect of Disinclination 4.2.1.4 Un/Happiness Un/Happiness Affect rate is the least in opinion texts in CNN The instances of happy feeling surpass those of unhappy feelings in opinion texts. .. both Authorial and Non-authorial Affects can be found in opinion texts in CNN The predominance of Non-authorial Affect in opinion texts in CNN indicates that writers of opinion texts tend people‟s