Negative Words Research Articles

Changing User Behavior in Decisions to Share COVID-19 Misinformation: An Implicit Association Test Study

Making medical decisions while distracted when receiving COVID-19 misinformation can majorly impact a person's life and even lead to death. Blatantly sharing COVID-19 misinformation is a significant problem of human behavior that triggers a speed-up and acceleration in the propagation and diffusion of misinformation in social media. While the latest research has focused on understanding the psychological dimensions of this phenomenon, few studies have explored the role of selective exposure and technological prevention when a person considers sharing COVID-19 misinformation, primarily through an Implicit Association Test (IAT). Our study identified and intervened in the association of user exposure between misinformation and implicit truth evaluations by using the Implicit Association Test (IAT) with "Misinformation vs. Fact Information or Positive vs. Negative Words”, 38 from 150 participants were either exposed to misinformation headlines or actual new headline posts on stimulants, in the form of images. We then measured participants' implicit truth evaluations and self-reported perceived accuracies of actual and of misinformation headlines using the Visual Selective Attention System (VSAS). After intervening, participants exposed to fake news headlines had lower implicit truth evaluations and increased perceived accuracy. This implies that exposure to fake news headlines after the intervention with the VSAS system may have directly affected implicit evaluations and changed user behavior in sharing COVID-19 misinformation.

Perceptions of older and younger adults who wear hearing aids

Objective To investigate older and younger adults’ perceptions of older and younger adults who wear hearing aids. Design Participants completed two Implicit Association Tests: One with images of older adults (OA-IAT) and one with images of younger adults (YA-IAT), either wearing or not wearing hearing aids. Participants also rated age, attractiveness, and intelligence of younger and older adults pictured with or without a hearing aid. Study sample Thirty older adults (M age = 70 years, SD = 4.38) and 30 younger adults (M age = 23 years, SD = 3.01) who reported not having hearing aids or a diagnosed hearing impairment. Results For both IATs, older and younger participants responded faster and more accurately when images of individuals wearing hearing aids were paired with negative words in comparison to positive words. Photo ratings did not vary in relation to the presence or absence of hearing aids for either age group. Conclusion Although the photo rating tasks indicate neutral explicit attitudes towards individuals who wear hearing aids, our interpretation of the IAT results indicates that younger and older adults may hold negative implicit attitudes towards both older and younger hearing aid users.

Social Listening in Gout: Impact of Proactive vs. Reactive Management on Self-Reported Emotional States.

This study aimed to characterize patient-reported outcomes from social media conversations in the gout community. The impact of management strategy differences on the community's emotional states was explored. We analyzed two social media sources using a variety of natural language processing techniques. We isolated conversations with a high probability of discussing disease management (score > 0.99). These conversations were stratified by management type: proactive or reactive. The polarity (positivity/negativity) of language and emotions conveyed in statements shared by community members was assessed by management type. Among the statements related to management, reactive management (e.g., urgent care) was mentioned in 0.5% of statements, and proactive management (e.g., primary care) was mentioned in 0.6% of statements. Reactive management statements had a significantly larger proportion of negative words (59%) than did proactive management statements (44%); "fear" occurred more frequently with reactive statements, whereas "trust" predominated in proactive statements. Allopurinol was the most common medication in proactive management statements, whereas reactive management had significantly higher counts of prednisone/steroid mentions. A unique aspect of examining gout-related social media conversations is the ability to better understand the intersection of clinical management and emotional impacts in the gout community. The effect of social media statements was significantly stratified by management type for gout community members, where proactive management statements were characterized by more positive language than reactive management statements. These results suggest that proactive disease management may result in more positive mental and emotional experiences in patients with gout.

Neural correlates of word processing influenced by painful primes.

The administration of painful primes has been shown to influence the perception of successively presented semantic stimuli. Painful primes lead to more negative valence ratings of pain-related, negative, and positive words than no prime. This effect was greater for pain-related than negative words. The identities of this effect's neural correlates remain unknown. In this EEG experiment, 48 healthy subjects received noxious electrical stimuli of moderate intensity. During this priming, they were presented with adjectives of variable valence (pain-related, negative, positive, and neutral). The triggered event-related potentials were analyzed during N1 (120-180 ms), P2 (170-260 ms), P3 (300-350 ms), N400 (370-550 ms), and two late positive complex components (LPC1 [650-750 ms] and LPC2 [750-1000 ms]). Larger event-related potentials were found for negative and pain-related words compared to positive words in later components (N400, LPC1, and LPC2), mainly in the frontal regions. Early components (N1, P2) were less affected by the word category but were by the prime condition (N1 amplitude was smaller with than without painful stimulation, P2 amplitude was larger with than without painful stimulation). Later components (LPC1, LPC2) were not affected by the prime condition. An interaction effect involving prime and word category was found on the behavioral level but not the electrophysiological level. This finding indicates that the interaction effect does not directly translate from the behavioral to the electrophysiological level. Possible reasons for this discrepancy are discussed.

Analysis of the Image of Wicked Women in Literary and Artistic Work

In the past, the main characteristics of female characters that people came into contact with in books, movies, and TV dramas were mostly kindness, integrity, magnanimity, and selflessness. They not only represented peoples yearning for truth, goodness, and beauty, but also were used as growth templates for countless girls due to their positive images. But in recent years, it is not difficult to find that the most sought-after female characters are mostly bound up with negative words such as revenge, madness, ferocity, and selfishness. When we stand on the standpoint of feminism, it is not difficult to find that these wicked women who do not follow the principles of men in their behavior, whether they go out of their families to participate in social affairs, or face their own desires, boldly breaking through the constraints of ethics and morality, all reflect their sense of autonomy and desire to live the value of being a person. However, the outcome of these women is mostly bleak, even if they spend their entire lives fighting, they still cannot break free from the heavy shackles of patriarchal society. From this, it can be seen the difficulty of traditional customs and the difficulty of womens liberation. This article analyzes the oppression and positive significance of the image of wicked woman in patriarchal and patriarchal societies from an objective perspective through the study of the image of wicked woman and attempts to provide ideas for shaping more diverse female roles in the future.

Effects of perspective taking on attention bias to body-related information among junior high school students with body image disturbance

Using lexical judgment tasks, the present study explored whether perspective taking affected attention bias to body-related information among junior high school students with body image disturbance. Experiment 1 examined the junior high school students' attention bias to body schema-related words; the results showed the body image disturbance group responded significantly more quickly to negative body schema-related words than positive words, whereas the control group did not show a significant difference between positive and negative words. In Experiment 2, participants were asked to judge whether the positive or negative body schema-related words were suitable to describe themselves, when adopting their own perspective or that of another person. The results showed that reaction times to negative words were significantly shorter than to positive words when adopting a self-perspective. When taking another's perspective, there was no significant difference of reaction time between positive and negative words. This result demonstrated that perspective taking reduced attention bias to negative body schema-related information among junior high school students with body image disturbance. The present research suggests that guiding adolescents to view themselves from different perspectives can help them form a more accurate and objective body image.

Linguistic Variables and Gender Differences Within a Messenger-Based Psychosocial Chat Counseling Service for Children and Adolescents: Cross-Sectional Study.

Text messaging is widely used by young people for communicating and seeking mental health support through chat-based helplines. However, written communication lacks nonverbal cues, and language usage is an important source of information about a person's mental health state and is known to be a marker for psychopathology. The aim of the study was to investigate language usage, and its gender differences and associations with the presence of psychiatric symptoms within a chat counseling service for adolescents and young adults. For this study, the anonymized chat content of a German messenger-based psychosocial chat counseling service for children and adolescents ("krisenchat") between May 2020 and July 2021 was analyzed. In total, 661,131 messages from 6962 users were evaluated using Linguistic Inquiry and Word Count, considering the following linguistic variables: first-person singular and plural pronouns, negations, positive and negative emotion words, insight words, and causation words. Descriptive analyses were performed, and gender differences of those variables were evaluated. Finally, a binary logistic regression analysis examined the predictive value of linguistic variables on the presence of psychiatric symptoms. Across all analyzed chats, first-person singular pronouns were used most frequently (965,542/8,328,309, 11.6%), followed by positive emotion words (408,087/8,328,309, 4.9%), insight words (341,460/8,328,309, 4.1%), negations (316,475/8,328,309, 3.8%), negative emotion words (266,505/8,328,309, 3.2%), causation words (241,520/8,328,309, 2.9%), and first-person plural pronouns (499,698/8,328,309, 0.6%). Female users and users identifying as diverse used significantly more first-person singular pronouns and insight words than male users (both P<.001). Negations were significantly more used by female users than male users or users identifying as diverse (P=.007). Similar findings were noted for negative emotion words (P=.01). The regression model of predicting psychiatric symptoms by linguistic variables was significant and indicated that increased use of first-person singular pronouns (odds ratio [OR] 1.05), negations (OR 1.11), and negative emotion words (OR 1.15) was positively associated with the presence of psychiatric symptoms, whereas increased use of first-person plural pronouns (OR 0.39) and causation words (OR 0.90) was negatively associated with the presence of psychiatric symptoms. Suicidality, self-harm, and depression showed the most significant correlations with linguistic variables. This study highlights the importance of examining linguistic features in chat counseling contexts. By integrating psycholinguistic findings into counseling practice, counselors may better understand users' psychological processes and provide more targeted support. For instance, certain linguistic features, such as high use of first-person singular pronouns, negations, or negative emotion words, may indicate the presence of psychiatric symptoms, particularly among female users and users identifying as diverse. Further research is needed to provide an in-depth look into language processes within chat counseling services.

Which Behaviors Generate The Best Reviews? A Sentiment Analysis of Online Reviews on AOSSM Surgeons

Background Online surgeon reviews can significantly influence a patient’s selection of a provider, and are important in the movement towards quality-based physician compensation models. Written reviews, however, are subjective and are thus difficult to quantitatively analyze. Sentiment analysis using artificial intelligence (AI) provides the ability to quantitatively assess surgeon reviews to provide actionable feedback. Purpose The objective of this study is to quantitatively analyze the online written reviews of AOSSM surgeons utilizing sentiment analysis and report trends in the most frequently used words in the best and worst reviews. Study Design Cross-sectional study using publicly-available online reviews Methods Online reviews and star-ratings of AOSSM surgeons were obtained from healthgrades.com and zocdoc.com. A sentiment analysis algorithm was used to compute sentiment analysis scores of each written review. Sentiment scores were validated against star-ratings. Positive and negative word and word-pair frequency analysis was performed to identify common items associated with high and low scores. A multiple logistic regression was run on clinically relevant phrases. Results Following the inclusion and exclusion criteria, 18,386 AOSSM surgeon reviews were analyzed for 2071 surgeons. There was no significant difference in sentiment scores by provider gender. Surgeons who are younger than 50 years old had more positive reviews (mean sentiment = +0.536 versus +0.458, p &lt; 0.01). The most frequently used and meaningful bi-grams used to describe top-rated surgeons are words correlating with kindness, caring personalities, and efficiency in pain management; whereas, those with the worst reviews are often characterized as unable to relieve the pain of their patients. The multiple logistic regression was significant for several clinically relevant words that confer greater or less odds of an improved score. Pain is significantly correlated with a decreased odds of receiving a positive review and positive behavioral factors confer a greater odds of receiving a positive review. Conclusion Sentiment analysis provides a means of quantifying written reviews of surgeons, and analysis of the reviews. This study provides insight into factors contributing to positive reviews, especially surgeon confidence, staff friendliness, warm disposition, and pain relief. Clinical Relevance This study delineates factors that impact the public reviews on AOSSM providers.

Transdiagnostic clustering of self-schema from self-referential judgements identifies subtypes of healthy personality and depression.

The heterogeneity of depressive and anxiety disorders complicates clinical management as it may account for differences in trajectory and treatment response. Self-schemas, which can be determined by Self-Referential Judgements (SRJs), are heterogeneous yet stable. SRJs have been used to characterize personality in the general population and shown to be prognostic in depressive and anxiety disorders. In this study, we used SRJs from a Self-Referential Encoding Task (SRET) to identify clusters from a clinical sample of 119 patients recruited from the Institute of Mental Health presenting with depressive or anxiety symptoms and a non-clinical sample of 115 healthy adults. The generated clusters were examined in terms of most endorsed words, cross-sample correspondence, association with depressive symptoms and the Depressive Experiences Questionnaire and diagnostic category. We identify a 5-cluster solution in each sample and a 7-cluster solution in the combined sample. When perturbed, metrics such as optimum cluster number, criterion value, likelihood, DBI and CHI remained stable and cluster centers appeared stable when using BIC or ICL as criteria. Top endorsed words in clusters were meaningful across theoretical frameworks from personality, psychodynamic concepts of relatedness and self-definition, and valence in self-referential processing. The clinical clusters were labeled "Neurotic" (C1), "Extraverted" (C2), "Anxious to please" (C3), "Self-critical" (C4), "Conscientious" (C5). The non-clinical clusters were labeled "Self-confident" (N1), "Low endorsement" (N2), "Non-neurotic" (N3), "Neurotic" (N4), "High endorsement" (N5). The combined clusters were labeled "Self-confident" (NC1), "Externalising" (NC2), "Neurotic" (NC3), "Secure" (NC4), "Low endorsement" (NC5), "High endorsement" (NC6), "Self-critical" (NC7). Cluster differences were observed in endorsement of positive and negative words, latency biases, recall biases, depressive symptoms, frequency of depressive disorders and self-criticism. Overall, clusters endorsing more negative words tended to endorse fewer positive words, showed more negative biases in reaction time and negative recall bias, reported more severe depressive symptoms and a higher frequency of depressive disorders and more self-criticism in the clinical population. SRJ-based clustering represents a novel transdiagnostic framework for subgrouping patients with depressive and anxiety symptoms that may support the future translation of the science of self-referential processing, personality and psychodynamic concepts of self-definition to clinical applications.

Suicide-related cognitions and emotional bias performance in a community sample

BackgroundSuicide is theorized to be connected to social interactions and feelings of belongingness. Those with suicide-related cognitions (SRCs) demonstrate attentional bias toward negative or suicide-related words, which can lead to increased feelings of rejection or alienation. As social interactions employ both verbal and nonverbal cues, there exists a gap in understanding how perception of emotional expressions can contribute to the development or exacerbation of suicidal ideation. MethodsThe current sample (N = 114, 60.5 % female, 74.6 % white) completed the Suicide Cognitions Scale-Revised (SCS-R) and Patient Health Questionnaire (PHQ-9) to assess SRCs and depression severity. The Emotional Bias Task (EBT) was used to assess emotional response latency. ResultsMultiple regression analyses on EBT results showed that endorsement of SRCs and depression severity were not associated with any particular emotional response bias. However, presence of SRCs showed an association with longer latencies to identify ambiguous emotional expressions, even when controlling for depressive symptoms and age LimitationsMeasures were self-completed online. Relative homogeneity of the sample and cross-sectional design limits interpretation of the results. ConclusionsThose with more severe SRCs take longer to recognize positive, nonverbal cues. Irregular processing of positive emotional stimuli combined with bias toward negative verbal cues could worsen feelings of rejection or alienation in social interactions, therefore increasing risk of developing SI. This suggests that interventions focusing on allocation of attentional resources to process positive social cues may be beneficial for those with SRCs to reduce severity and risk of suicide.

Short Video Blogger "Courtman" in the Face of Negative Word of Mouth Problems and Solutions

This study examines the case of Li Shi Jin, a team member of the basketball short video blogger "Courtman" focusing on his drunk driving incident and the subsequent negative word-of-mouth phenomenon. The aim is to explore effective measures for mitigating the impact of negative online reputation and provide insights into how sports bloggers can address similar situations to minimize the repercussions brought about by unfavorable public perception. Through investigation and research, it is found that the public is more interested in the occurrence of similar negative news, so it is easier to generate negative word-of-mouth in the network environment. Therefore, it is particularly important for the "Courtman" team to dispel the influence of negative word of mouth and negative public opinion. As for the team itself, the team can exert its independent initiative and eliminate the negative effects through active and passive forgetting. At the same time, the team should also attach importance to the interaction with fans, guide fans to play their own attributes from the positive interaction, create a good reputation by carrying out high-quality fan interaction, and give play to the characteristics of opinion leaders among fans.

Advancing delirium classification: A clinical notes-based natural language processing-supported machine learning model

ObjectiveThe study of the epidemiology of delirium in hospitalized patients is challenging. We aimed to identify the presence or absence of delirium from clinical text notes using natural language processing (NLP) techniques and machine learning (ML) models. Materials and methodsWe developed a delirium predictive model using 942 clinical notes from hospitalized patients with an ICD-10 delirium hospital discharge code. Moreover, we implemented ML models using a) delirium-suggestive words from an expert-defined dictionary or b) free text in clinical notes. Both strategies considered positive and negative delirium-associated words. ResultsAt the note level, for the dictionary method, the logistic regression model achieved an area under the receiver-operating curve (AUROC) of 0.917 for positive words and 0.914 for combined positive and negative words. The areas under the precision-recall curve (AUPR) were 0.893 and 0.897, respectively. For the free-text method, the model achieved an AUROC of 0.826 and 0.830 and AUPR of 0.852 and 0.856, respectively. DiscussionNLP-based ML models accurately identified the presence of delirium in clinical notes. The dictionary-based method was superior to the free-text method. The use of negative features improved performance in both methods. ConclusionOur proposed NLP-based ML model identified delirium in clinical notes. This model could automatically screen millions of notes and facilitate the study of the epidemiology of in-hospital delirium.

Atmosphere at Briefing Sessions and Its Influence on Local Residents’ Intention to Participate in Discussion

Although it is widely recognized that atmosphere influences people’s decision‐making process, few studied have examined the effect of atmosphere in the context of consensus building concerning the construction of controversial infrastructures. At local residents’ briefing sessions, the negative words used by certain members of the strong opposition can often create a negative atmosphere, leading to unpleasant arguments. Therefore, in this study, a vignette experiment was conducted to examine the influence of the atmosphere at briefing sessions on local residents’ intention to participate in discussion. The results showed that local residents reported greater intention to participate in discussion in a positive atmosphere compared to a negative atmosphere. As for the cognitive process, however, while in the positive atmosphere only a single factor (i.e., interest) affected local residents’ intention, in the negative atmosphere multifactors (e.g., procedural justice, disbenefit, and mental burden) affected the intention. These findings suggest the importance of choosing an appropriate strategy to increase resident’s intention to participate in discussion depending on the atmosphere (positive or negative). The psychological mechanism of the influence of atmosphere and effective strategies that project implementers should take when the atmosphere becomes negative at a briefing session are discussed.

Dimensionality of the Swahili version of the General Health Questionnaire (GHQ-12) in a Kenyan population: A confirmatory factor analysis.

The current study evaluated the Kiswahili version of General Health Questionnaire (GHQ-12) in a Kenyan context comprising of women exposed to gender-based violence. Participants were randomly drawn from community sampling using household screening methods in peri-urban areas in Nairobi. A total of 1,394 participants with varying levels of literacy (years of education: mean [M] = 9.42; standard deviation [SD] = 3.73) and aged between 18 and 89 years were recruited for the study. The observed factor structure of the GHQ-12 was evaluated using six most tested models querying the dimensionality of the instrument insofar as the impacts of positive and negative wording effects in driving multidimensionality. Results from the confirmatory factor analysis supported a bifactor model, consisting of a general distress factor and two separate factors representing common variance due to the positive and negative wording of items. Overall, the findings support the use of the Kiswahili version of the GHQ-12 as a unidimensional construct with method-specific variance owing to wording effects. Importantly, GHQ-12 responses from a sample of Kenyan women with relatively low levels of literacy are congruent with the factor structure observed in other cross-cultural settings in low- and-middle-income countries.

Exploring explicit and implicit attitudes towards wildlife food

Illegitimate wildlife consumption poses threats to public health, biodiversity and natural ecosystems. Understanding of public attitudes towards wildlife as food can help promote wildlife conservation. However, almost wildlife consumption researches limit insights to subjective attitudes. To address this gap, the present employs a comprehensive approach, combining questionnaires, the Implicit Association Test (IAT) paradigm, and Event-Related Potential (ERP) method. This multi-method strategy enables better exploration of both explicit and implicit attitudes toward wildlife food. Participants who had been exposed to wildlife food consumption were randomly recruited. Compared to non-wildlife foods, people had a lower acceptability of wildlife foods, a longer reaction time when paired with positive words and a smaller N400 component when paired with negative words. These results revealed that public showed negative attitudes towards wildlife food compared to non-wildlife food, and this result was consistent between explicit and implicit attitudes. This outcome also provides a positive signal for wildlife conservation. Leveraging the public's negative perceptions of wildlife food in conjunction with the adverse consequences of eating wildlife food can be employed to further the cause of wildlife conservation.

Progressive Detection of Uncertainty in Natural Language Processing Using a Labeled Variable Dimension Kalman Filter

Owing to rapid advancements in information and communication technology, natural language processing (NLP) methods have attracted considerable attention. Estimating uncertainty is a well‐established problem in NLP. Developing systems capable of automatically detecting uncertain terms within a natural language is critical for developing effective text‐analysis algorithms. Consequently, several NLP tools have been developed for this purpose. However, there are several obstacles to the design of fast and effective NLP technologies that effectively analyze ambiguous terms in natural languages. This work focuses on a particular method for detecting uncertainty, termed progressive detection, which can be accomplished using a dynamic probabilistic graphical model to solve these challenges. We iteratively upgraded the Kalman Filter to Labeled Variable Dimension Kalman Filter (LVDKF) based on observations from real datasets. The LVDKF learns two basic features from positive and negative words. The formula was then derived using a dynamic detection system, designed based on conditional probability. Finally, we simulated progressive detection experimental conditions and assessed the LVDKF on two publicly available datasets. It performs better than the baseline methods in these tests, which shows that it is effective at detecting changes over time.

How does item wording affect participants' responses in Likert scale? Evidence from IRT analysis.

Researchers often combine both positively and negatively worded items when constructing Likert scales. This combination, however, may introduce method effects due to the variances in item wording. Although previous studies have tried to quantify these effects by using factor analysis on scales with different content, the impact of varied item wording on participants' choices among specific options remains unexplored. To address this gap, we utilized four versions of the Undergraduate Learning Burnout (ULB) scale, each characterized by a unique valence of item wording. After collecting responses from 1,131 college students, we employed unidimensional, multidimensional, and bi-factor Graded Response Models for analysis. The results suggested that the ULB scale supports a unidimensional structure for the learning burnout trait. However, the inclusion of different valences of wording within items introduced additional method factors, explaining a considerable degree of variance. Notably, positively worded items demonstrated greater discriminative power and more effectively counteracted the biased outcomes associated with negatively worded items, especially between the "Strongly Disagree" and "Disagree" options. While there were no substantial differences in the overall learning burnout traits among respondents of different scale versions, slight variations were noted in their distributions. The integration of both positive and negative wordings reduced the reliability of the learning burnout trait measurement. Consequently, it is recommended to use exclusively positively worded items and avoid a mix in item wording during scale construction. If a combination is essential, the bi-factor IRT model might help segregate the method effects resulting from the wording valence.

Exploring the Subjectivity of English Academic Discourse in the Context of Big Data

Abstract This study develops a sentiment analysis model for English academic discourse based on word information to effectively understand and analyze the sentiment tendencies in English literary texts. The structure of the model includes word embedding layer, character-level feature extraction, word-level feature extraction and feature fusion and classification layer. The word embedding layer realizes the mapping between word vectors and word vectors by microblogging pre-trained word vectors. The character-level feature extraction session uses a multi-window convolutional layer to capture N-Gram information. In contrast, the word-level feature extraction obtains deeper semantic information through a Bi-LSTM layer and fuses it with character-level information to enhance robustness. The feature fusion and classification layer further combines these features and determines the fusion weights through a linear layer to achieve sentiment classification. In performance tests, the model achieves 92.5% sentiment classification accuracy on the standard dataset, an improvement of about 6% compared to traditional methods. In particular, the accuracy is improved by 5% when dealing with text with sentiment polarity transition, showing good adaptability. In addition, using 657 positive and 679 negative sentiment words as seed words effectively expands the sentiment lexicon and enhances the comprehensiveness and accuracy of sentiment analysis.

ASSESSING GREENWASHING PRACTICES WITH SPECIAL RELEVANCE TO THE FOOD &amp; BEVERAGE INDUSTRY

This paper aims to investigate the concept of greenwashing and its application in various industries, with a specific focus on the food and beverage industry. A systematic Literature Review (SLR) was carried out to identify Greenwashing Practices (GwP). After reviewing more than 20 papers from the Journal of international repute, the definitions related to GwP were studied. It was established that GwP is an unethical marketing practice. Subsequently, all the definitions were run in the WORDITOUT application (Data mining technique) which clearly highlighted the list of negative words attached to this concept. Furthermore, based on SLR, 10 common GwP were identified across various industries. One of the objectives of this research was to study the GwP in Food &amp; beverage (F&amp;B) industry. Content analysis indicated that 5 GwP are highly common and significantly influence consumer behaviour. Key findings highlight the need for stricter regulatory measures and greater consumer awareness to mitigate greenwashing's adverse effects. This study contributes to the existing literature by providing insights into greenwashing trends in South Asia, an area with limited prior research.

부정응답어 ‘아니-’의 활용형에 대한 고찰

The purpose of this study is to discuss the conjugation of the negative response word ‘Ani-’, organize its characteristics, and classify it according to meaning and function. Among the negative response words for analysis, we looked at the usage patterns of 'Ani' and 'Aniya' and 'Aniyo' and 'Anieyo', which are conjugations of 'Ani-' and are located in the same writing style, and organized their characteristics and analyzed them into meaning and function. As a result, it was confirmed that the conjugation of the negative response word 'Ani-' has the function of confirmation and emotional expression. The confirmation function is the function of confirming objective facts and subjective opinions, and the emotional expression is a denial of the description. These were categorized into those showing emotional denial and those showing humility and were schematized. This is meaningful in that it discusses negative response words that have not been actively discussed until now, but it is limited in that it fails to pay attention to the various functions of the negative word ‘Ani’.