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Tiêu đề A Comparative Analysis of Adjective Types and Functions in Electronic Media: CNN and The Straits Times Headlines
Tác giả Trương Thị Lan Anh, Nguyễn Diệu Linh, Bùi Thị Minh Hồng, Dương Thị Thanh Trà
Trường học Hanoi University of Science and Technology, School of Foreign Languages
Chuyên ngành Syntax
Thể loại Class Project
Năm xuất bản 2024
Thành phố Hanoi
Định dạng
Số trang 21
Dung lượng 1,01 MB

Nội dung

HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF FOREIGN LANGUAGES ----□□□□ ----FL3221 SYNTAX A Comparative Analysis of Adjective Types and Functions in Electronic Media: CNN and Th

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HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY

SCHOOL OF FOREIGN LANGUAGES

□□□□

FL3221 SYNTAX

A Comparative Analysis of Adjective Types

and Functions in Electronic Media: CNN and The

Straits Times Headlines

by Trương Thị Lan Anh

20204058

Nguyễn Diệu Linh

20204109

Bùi Thị Minh Hồng

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Dương Thị Thanh Trà

20204173

January,

31st, 2024

Contents

Abstract 3

Introduction 3

PAST RELATED STUDIES 4

Methodology 5

5 Findings 6

5.1 Types of adjectives Used in the Headlines of CNN and The Straits Times 6

5.2 Function of the Adjectives Used in the Headlines of CNN and The Straits Times 9

6 Discussion 15

6.1 Similarities of the Adjectives Used in the Headlines of CNN and The Straits Times Electronic Media 15

6.2 Differences of the Adjectives Used in the Headlines of CNN and The Straits Times Electronic Media 17

6.3 Similarities of the Functions of Adjectives Used in the Headlines of CNN and The Straits Times Electronic Media 18

6.4 Differences of Functions of the Adjectives Used in the Headlines of CNN and The Straits Times Electronic Media 18

Conclusion and recommendations 19

References 19

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and The Straits Times Headlines

Abstract

The role of headlines in capturing reader attention within electronic media is significant, often utilizing adjectives to craft engaging content Despite their crucial role, adjectives have not received extensive research attention compared to other lexical categories, particularly in electronic media like CNN and The Straits Times This study aims to scrutinize the types and functions of adjectives in headlines from these sources, focusing on both semantic categories and syntactic functions as per the classification framework of Biber, Conrad, and Leech The analysis involved 50 headlines from both CNN and 50 headlines from The Straits Times, revealing 69 adjectives in CNN headlines, with 46 serving as descriptors and 23 as classifiers.Similarly, 59 adjectives were identified in The Straits Times headlines, comprising 46 descriptors and 13 classifiers Across both media, emotive, miscellaneous, and

size/quantity/extent descriptors predominated in headlines The syntactic functions of adjectives were also explored, with attributive adjectives being most prevalent in both CNN and The Straits Times news headlines This research emphasizes the importance of analyzing

a comprehensive understanding of adjective usage in electronic media, offering valuable insights for future investigations into this linguistic aspect

Introduction

In today's fast-paced society, media functions as an indispensable tool for communication, information dissemination, and advertising Its crucial role lies in providing and distributing diverse types of information, covering areas such as news, health, sports, politics, and education Media is broadly categorized into traditional and new media Traditional media encompasses forms of mass communication predating digital media, including television, radio, newspapers, books, and magazines On the other hand, new media refers to digitally delivered content such as newspaper articles, blogs, music, and podcasts Despite their distinct characteristics, both aim to convey information to mass audiences

Electronic media, a subset of new media, employs electronic devices and technology for communication and information dissemination This includes digital communication through

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information A notable example in Singapore is The Straits Times, established in 1845, recognized as one of Southeast Asia's oldest and most respected newspapers As part of Singapore Press Holdings, The Straits Times has evolved with technological advancements while upholding its commitment to delivering reliable news and engaging content.

CNN, or Cable News Network, is a global leader in news and information since its launch in

1980 Operating under WarnerMedia, CNN has played a pivotal role in shaping the landscape

of 24-hour news broadcasting, offering breaking news, in-depth analysis, and diverse programming across various platforms Renowned for its live coverage of major events, CNN

is a trusted source for news on a global scale

CNN and The Straits Times are two popular electronic media types in Singapore, both utilizing headlines as prominent components Headlines, defined as large-sized text at the top

of an article, news story, or advertisement, serve to grab the reader's attention An effective headline should be short, accurate, and attention-grabbing, often consisting of lexical words These lexical words can be classified into four classes: adjectives, adverbs, lexical verbs, and nouns While adjectives are less common than nouns and verbs, they play a crucial role in modifying nouns and influencing readers' opinions

Despite the significance of adjectives in media, they remain under-researched compared to other word classes This research aims to address this gap by examining the lexical word class of adjectives in CNN and The Straits Times news headlines The comparative analysis

is essential, considering the scarcity of studies involving electronic media and the importance

of understanding how adjectives function in different media types The research explores the potential impact of adjectives on shaping reader opinions and directing attention to specific issues within the context of this field.The classification scheme of adjectives proposed by Biber, Conrad, and Leech (2002) is employed to address the two following research questions:

1 What types of adjectives are predominantly used by writers in CNN and the Straits Times headlines?

2 How are adjectives utilized in CNN and The Straits Times headlines?

This study adds to the field of English grammar research and offers valuable perspectives on the utilization of adjectives in electronic media headlines by concentrating on this specific linguistic feature The examination, which involves a comparative analysis of adjectives in headlines from CNN and The Straits Times, aims to uncover intriguing linguistic trends and preferences The findings may have implications for future research and practical

applications, particularly in the realms of journalism and media

PAST RELATED STUDIES

The use of adjectives to provide readers with more specific information about the color, size, shape, material of objects, etc to attract readers from the first moments with the title is a good writing method As a result, there have been numerous prior studies on the use of adjectives in headlines that have covered a wide range of topics, including websites, online news, science, and travel pieces, and researchers have used a variety of techniques.Using Leech and Short's (1981) lexical categories, Faiz et al (2018) investigated the adjective selection as a lexical category in Mohsin Hamid's book, How to Get Filthy Rich in Rising Asia The majority of the descriptors linked to physical, emotional, color, and aural

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to see how lexical categories—like adjectives—are used in literary text, this study yielded some fascinating results They also found that Hamid gave readers a realistic impression of the imaginary Asian world by using strong and exclusive descriptors.

Jutharat (2017) in "Research on adjective types and functions in popular science articles" alsoresearched this topic His study attempts to examine the kinds of characteristics and roles thatcan be discovered in popular science publications He employed two different approaches: first, he utilized quantitative data to convey the general statistics of the data, and then he usedqualitative data to weave the quantitative data into the questions 25 articles were chosen at random to be surveyed and analyzed using Khamying's (2007) conceptual framework for categories of attributes in English The articles contain ten different categories of discovered features: individual, quantitative, numerical, indicative, owner, distributive, emphatic, emotional, and relative The first level of frequently used adjectives is arranged as follows: primary adjective, count from number (5.20%), possessive adjectives (7.69%), quantitative adjectives (7.57%), determined from definition solely (5.26%), and descriptive adjectives ( 66.51%) In this study, interrogative adjectives were absent, and emotional adjectives were the least frequently utilized Jutharat's research, however, hasn't offered any

recommendations for the best ways to use the term feature in Popular Science Articles.Hermariyanti and Ferawaty (2017) also studied adjectives in headline news online Adjectives in online news headlines are the focus of this study, which attempts to provide answers to queries like: How many adjectives are present in online news? Which adjective kinds are most frequently used in internet news articles? Online news sources were used to get the headline data for this study To acquire an explanation of the data, in this case, internet news, a literature study, and pertinent research were observed According to the findings, the author of the essay employs a wide variety of adjectives, with descriptive adjectives being the most frequently employed This study's primary goal is to supply internet-readable information on online news titles that is relevant to linguistic research regarding adjective usage in online news titles However, the study only uses one method: qualitative method descriptively to conduct the survey, so the results received may not be analyzed much deeper For that reason, this study also does not mention the function of adjectives as well as some recommendations on using adjectives in headlines - something thatmany readers are looking forward to

To explore the subtleties of participial adjective construction in Malaysian English, Chai and Ong (2018) conducted a corpus-based investigation that examined online magazine articles They used Wordsmith Tools 5, a powerful program that provides wordlist and concordance features, to carefully examine 14 articles taken from The Star Online between 2006 and 2012.They were able to determine the favored suffix variant used by Malaysian writers to generate participial adjectives by using this methodological approach Notably, among the seven adjectives examined, their results revealed the predominance of the "-t" suffix, providing important new information about the changing grammatical landscape of Malaysian English Furthermore, the researchers' pedagogical implications highlight how their findings could influence language instruction in the area

As an addition to the current literature, this research stands out for comparing the use of adjectives in CNN and The Straits Times, two different print media sources This research fills in a significant need in the study of English grammar and linguistics while also illuminating the complex roles that adjectives play in newspaper and magazine headlines The recognized classifications of semantic categories and the syntactic roles of adjectives put forward by Biber, Conrad, and Leech (2002) provide the analytical basis for doing this

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This investigation centers on two categories of electronic media: the CNN international news network and The Straits Times local news network The electronic text from both chosen electronic media sources was utilized for the analysis The research methodology integrates textual analysis, encompassing both qualitative and quantitative approaches, to scrutinize the data The objective in selecting CNN and The Straits Times news is to draw comparisons regarding the adjectives used in their respective headlines A qualitative and quantitative analysis was conducted on headlines from both sources A total of 50 samples from CNN news and 50 samples from The Straits Times news were chosen to investigate adjectives in the headlines These adjectives, extracted from both sources, were compiled and presented in

a tabular format within a Word document Subsequently, qualitative analysis was employed

to classify the adjectives based on the syntactic functions proposed by Biber, Conrad, and Leech (2002), followed by quantitative analysis using descriptive statistics, raw frequency, and percentages

The primary research question seeks to determine the prevalent types of adjectives used in theheadlines of CNN international news network and The Straits Times local news network Thesemantic categorization of adjectives, considering descriptors and classifiers, as proposed by Biber, Conrad, and Leech (2002), was utilized to address this question The second research question explores the usage patterns of adjectives in CNN and The Straits Times news headlines To answer this question, the categorization of syntactic functions of adjectives, also proposed by Biber, Conrad, and Leech (2002), was applied According to their framework, adjectives fulfill attributive and predicative functions, as well as five other syntactic functions: noun phrase head, linking expression, exclamation, postposed modifier, and free modifier

5 Findings

5.1 Types of adjectives Used in the Headlines of CNN and The Straits Times

In this research, an analysis was conducted on 2 editions of CNN newspapers to detect headlines incorporating adjectives, which belong to the lexical word-class Subsequently, the distribution of these adjectives was scrutinized and categorized into two principal semantic groups: descriptors and classifiers, in accordance with the framework outlined by Biber, Conrad, and Leech (2002) The compiled data are showcased in Table 1

Table 1 Findings of adjectives in CNN news Headlines

0

11

5

0 15.94%

7.25%

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Eye-catching, prestigious, hard, special, notable, familiar, obvious, unexpected, unexpected, military

Salty, vested, luxury, military, long-term

12

6

5 23

26.08%

7.25% 33.33%

In the examination of 50 headlines gathered from 2 editions of CNN newspapers, a sum of 69

adjectives was discerned These adjectives were then segregated into two primary semantic classifications: descriptors and classifiers Descriptors comprised 46 adjectives, constituting

66.67% of the total adjectives within the newspaper headlines, whereas the remaining 23

adjectives were categorized as classifiers Furthermore, both descriptors and classifiers underwent additional categorization based on their respective types

Hence, the authors and editors of CNN newspapers demonstrated a tendency to utilize descriptors predominantly in the headlines, as evidenced by the identification of 46 descriptors Among descriptor types, emotive emerged as the most prevalent, trailed by descriptors related to size/quantity/extent, miscellaneous descriptors, and time descriptors

Regarding classifiers, the restrictive/relational type stood out as the most frequently employed, succeeded by classifiers offering affiliative and specific classifiers

Conversely, descriptors related to color were the least frequently encountered in the headlines.

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total of 2 printed editions were scrutinized to identify headlines featuring adjectives Like the approach taken with CNN newspapers, the adjectives obtained from The Straits Times were analyzed and categorized into the primary semantic groups: descriptors and classifiers These descriptors and classifiers were subsequently organized based on their individual types The results of this analysis are outlined in Table 2.

Table2 Findings of adjectives in The Straits Times news headlines

repeated, new, new, new, eternal, new, ancient, newrestive, hellish, corrosive, bustling, likely, cautious, unexplained, assertive, bloody, extraordinary, hopeful, raw, deadly, disposable, constructive, significant, sharp, complicated, abnormal, perfect

unmarked, apparent

1 15

non-muslim, British, Malaysian, Hungarian, Portugal

10.17%

8.47%

3,39% 22.03%

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Times newspaper These adjectives were categorized into two primary semantic groups: descriptors and classifiers Predominantly, descriptors were employed, with 46 descriptors representing 77.97% of all adjectives found in the magazine headlines, while classifiers accounted for only 13 adjectives, or 22.03% of the total.

In their headlines, the writers and editors of The Straits Times newspaper exhibited a preference for descriptors, as evidenced by the identification of 46 of them The most commonly utilized descriptor type was emotive, followed by size/quantity/extent, time, and miscellaneous descriptors. Among classifiers, those restrictive/relational classifiers were most frequently employed, followed by affiliative classifiers Less commonly integrated into the headlines were color descriptors and specific classifiers.

Despite analyzing an equal number of copies of both print media, CNN newspapers contained

a greater number of headlines and adjectives Across 2 copies of CNN newspapers, a notable total of 69 adjectives were identified in 50 headlines, in contrast to only 59 adjectives found

in 50 headlines from The Straits Times newspaper

In both CNN newspapers and The Straits Times newspaper, descriptors were favored over classifiers in headlines, typically describing attributes such as color, size, weight, chronology,age, and emotion (Biber, Conrad, and Leech, 2002) The headlines in CNN newspapers predominantly featured emotive descriptors, along with size/quantity/extent, miscellaneous, time, and color descriptors Similarly, The Straits Times newspaper primarily utilized emotive descriptors, followed by size/quantity/extent, time, miscellaneous, and color descriptors No color descriptors appear in The CNN, but The Straits Times uses quite

a few color descriptors in their headlines.

In terms of classifiers, CNN and the Straits Times newspaper headlines predominantly featured restrictive/relational classifiers, while those also included classifiers that provided affiliative subject area or specific type However, the difference in the percentage of use

of specific clarifiers is much more skewed for CNN than for The Straits Times.

5.2 Function of the Adjectives Used in the Headlines of CNN and The Straits Times

To address Research Question 2, which explores how adjectives are utilized in CNN and The Straits Times headlines, the adjectives identified in these publications were examined in context to determine their syntactic roles The classification framework proposed by Biber, Conrad, and Leech (2002) was employed to categorize the adjectives based on their syntactic functions within the headlines

As per Biber, Conrad, and Leech (2002), adjectives can serve seven primary syntactic roles

or functions: attributive, predicative, postposed modifiers, noun phrase heads, linking expressions, exclamations, and free modifiers The outcomes of this analysis are depicted in Figure 1

Attributive: 51 adjectives (73.91%)

Noun Phrase Heads: 2 adjectives ( 2.89%)

Subject Predicative: 7 adjectives (10.15%)

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Linking Expressions: 0 adjectives (0.00%)

Free Modifiers: 1 adjective ( 1.45%)

Postposed Modifier: 1 adjective ( 1.45%)

Figure 1 Syntactic roles/functions of adjectives.

As outlined in the preceding section, a total of 69 adjectives were identified within 50 headlines extracted from two editions of CNN newspapers This section focuses on classifying these adjectives based on their syntactic roles within the headlines The classification follows the framework proposed by Biber, Conrad, and Leech (2002) for categorizing the syntactic functions of adjectives The analysis reveals that the majority of theadjectives, totaling 51 or 73.91%, serve as attributive adjectives in the headlines Attributive adjectives are capable of modifying common nouns, proper place nouns, names of individuals, and personal pronouns (Biber, Conrad, and Leech, 2002) Table 3 provides examples of attributive adjectives found in the headlines

Table 3 Examples of attributive adjectives found in the headlines

Headline Adjective Semantic

category

Syntactic function

China’s wild week in markets: Calm

returns but big challenges remain

Big D: Size Attributive

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