Negative Comments Research Articles

Using Patient Experience Surveys to Identify Potential Diagnostic Safety Breakdowns: A Mixed Methods Study.

One in 20 outpatients in the United States experiences a diagnostic error each year, but there are no validated methods for collecting feedback from patients on diagnostic safety. We examined patient experience surveys to determine whether patients' free text comments indicated diagnostic breakdowns. Our objective was to evaluate associations between patient-perceived diagnostic breakdowns reported in free text comments and patients' responses to structured survey questions. We conducted an exploratory mixed methods study using data from patient experience surveys collected from adult ambulatory care patients March 2020 to June 2020 in a large U.S. health system. Data analysis included content analysis of qualitative data and statistical analysis of quantitative data. In 2525 surveys with negative comments, 619 patients (24.5%) identified diagnostic breakdowns, including issues with accuracy (n = 282, 46%), timeliness (n = 243, 39%), or communication (n = 290, 47%); some patients (n = 181) reported breakdowns in multiple categories. Patients who gave a low average score (50 or less on a 100-point scale) on provider questions were almost seven times more likely to perceive a diagnostic breakdown than patients who scored their provider higher. Similarly, patients who gave a low average score on practice-related questions were twice as likely to perceive a diagnostic breakdown. Patient feedback in routinely collected patient experience surveys is a valuable and actionable information source on diagnostic breakdowns in the ambulatory setting. The more easily monitored structured survey data provide a screening method to identify encounters that may have included a patient-perceived diagnostic breakdown and therefore require further examination.

Language and gender in a US reality TV show: An analysis of leadership discourse in single-sex interactions

This paper examines issues relating to language, gender and leadership in the debut season of the reality TV show The Apprentice (USA). In particular, it looks at the ways in which two male and two female project managers ‘do leadership’ through discourse in single-sex interactions. The analysis shows that these project managers display leadership styles which are by and large in accordance with the gendered norms and expectations. It is found that while their leadership styles are not evaluated entirely positively, the male managers receive both positive and negative comments for using predominantly masculine speech styles and the female managers who ‘do leadership’ by employing a largely feminine discourse style are perceived negatively. It is also argued that the singlesex contexts of interactions can be seen as being constructed intentionally in the TV show in order to capture the gender-stereotypical speech styles of ‘doing leadership’.

Feedback in Linear Programming: Students’ Perceptions at AYO Secondary School of Nkeyema District in the Western Part of Zambia: A Hermeneutic Tactic

Abstract: The foundation of teaching strategies in school environments is feedback. Nonetheless, it needs to be communicated clearly because it is frequently misinterpreted. Due to the negative comments, they gained through their actual internships, students lacked confidence and felt unable to practice their talents. They also felt that receiving comments made it difficult for them to finish their useful exercises. In the western Zambian region of Nkeyema, AYO Secondary School was the site of this investigation. An interpretivist approach was used in an exploratory qualitative design. Eleven (11) secondary school pupils in total and each student was questioned separately. With the participants' consent, all interviews were audio recorded using a digital voice recorder and then verbatim transcriptions were made. After that, qualitative content analysis was used to analyse the data thematically.

Microblog Negative Comments Data Analysis Model Based on Multi-scale Convolutional Neural Network and Weighted Naive Bayes Algorithm

As a form of public supervision, Microblog’s negative reviews allow people to share their opinions and experiences and express dissatisfaction with unfair and unreasonable phenomena. This form of supervision has the potential to promote social fairness, drive governments, businesses, and individuals to correct mistakes and enhance transparency. To characterize the sentiment trend and determine the influence of Microblog negative reviews, we propose a multi-scale convolutional neural network and weighted naive bayes algorithm (MCNN–WNB). We define the feature vector characterization index for Microblog negative review data and preprocess the data accordingly. We quantify the relationship between attributes and categories using the weighted Naive Bayes method and use the quantification value as the weighting coefficient for the attributes, addressing the issue of decreased classification performance in traditional methods. We introduce a sentiment classification model based on word vector representation and a multi-scale convolutional neural networks to filter out Microblog negative review data. We conduct simulation experiments using real data, analyzing key influencing parameters such as convergence time, training set sample size, and number of categories. By comparing with K-means, Naive Bayes algorithm, Spectral Clustering algorithm and Autoencoder algorithm, we validate the effectiveness of our proposed method. We discover that the convergence time of the MCNN–WNB algorithm increases as the number of categories increases. The average classification accuracy of the algorithm remains relatively stable with varying test iterations. The algorithm’s precision increases with the number of training set samples and eventually stabilizes.

Examining the Role of Family, Media, Peers in Young Caucasian Men’s Understandings of Body Dissatisfaction: A Thematic Analysis Using the Tripartite Influential Model and Social Comparison Theory

This study explores the factors contributing to body dissatisfaction among young Caucasian men. It focuses on family, peers, and media influences, addressing a gap in the literature that rarely integrates men’s experiences. The research draws on the Tripartite Influence Model and Social Comparison Theory, using thematic analysis to examine semi-structured interviews with eight participants aged 20–21. The research considers participants’ sexual orientation and country of origin when analysing the data. The findings show that family, peers, and the media positively and negatively shape body dissatisfaction among participants. Positive familial support can enhance body image, while negative comments from family members and peers exacerbate dissatisfaction. Social media was found to often reinforce unattainable body standards. The research contributes to the limited literature on men’s body dissatisfaction by expanding the application of the Tripartite Influence Model and Social Comparison Theory to this population. The study underscores the need for greater societal awareness and a more inclusive approach to body image research that considers diverse ethnic backgrounds and sexual orientations. We argue that more attention needs to be paid to men’s body dissatisfaction, as men are often excluded from these discussions. This study provides valuable insights into the dynamics of male body image, offering a foundation for future research and societal discourse on this often-overlooked issue.

Affinity in Adversity: Examining Brand Love and Online Customer Engagement in the Restaurant Industry

Previous studies have investigated brand love in restaurants but have not considered the dynamics of online reviews about restaurant brands. To fill this gap, this study aims to understand how consumers with a high level of love towards restaurant brands defend them in the face of negative reviews on social media. This research, carried out in a Brazilian context, adopts a qualitative approach, analysing 3,979 customer reviews sourced from Instagram through sentiment and categorical content analysis. From the dimensions of brand love, the results showed that customers who love restaurant brands react to negative reviews about them on social media, expressing their positive emotional connection with the companies and acting as their defenders. The study shows that for the restaurant segment, it is relevant to have consumers who love the brand once they help mitigate the effects generated by negative comments online. Furthermore, the research highlights how brand love manifests in restaurant brands' digital context.

Measuring the Success of Grandpa Aki’s Short Video Series in Cross-cultural Transmission of Traditional Chinese Culture

With the development of digitization and online platforms, short videos have become one of the ways to spread traditional Chinese culture. The success of Grandpa Aki’s short videos is a model of cross-cultural transmission of traditional Chinese culture, especially craftsmanship, via short videos. However, few scholars have talked about the implications of cross-cultural transmission of Chinese excellent traditional culture brought by Grandpa Aki’s short video series. The paper collected the title of the video, the view of the video and the proportion of positive comments and negative comments from the top 5 popular videos by using Python. The paper aims to identify (1) the characteristics of Grandpa Aki’s short video series; (2) the reasons for the success of Grandpa Aki’s short video series; (3) the implication of cross-cultural transmission of traditional Chinese culture from the success of Grandpa Aki’s short video series. The results show that 1) these videos are characterized by an immersive experience and spread traditional Chinese culture in detail. 2) The reasons for the success of these videos are the strong curiosity about traditional Chinese culture from overseas citizens, the value of traditional Chinese culture, the entertainment value of these videos and the resonance from people. The paper provides a thinking mode for scholars to solve the dilemma of overseas dissemination of traditional Chinese culture.

Hidden emotional trends on social media regarding the Thailand–China high-speed railway project: a deep learning approach with ChatGPT integration

Leveraging sentiment analysis on social media reveals hidden emotional trends by providing deep insights into the public’s collective opinions and feelings because social media can reflect most opinions based on true feelings. However, there is no time-series analysis of Thai opinions on social media regarding government projects in Thailand. Therefore, the focus of this research is to survey and dynamically analyze sentiment on social media platforms, particularly YouTube, regarding the Thailand–China High-Speed Rail Project (Thai–China HSR Project). This is a major project involving an investment of over 500 billion baht, a collaborative effort between the Thai and Chinese governments aimed at developing transportation infrastructure. It leads the public concerns of Thai people about the potential economic and social impacts. The deep learning (DL) technique was used for this analysis by the Bidirectional Encoder Representations from Transformers (BERT) model, together with WangchanBERTa, a Thai language model specifically designed to analyze opinions from Thai comments received from YouTube from July 2015 to January 2024. The analysis reveals that citizens’ sentiments are primarily neutral, with more negative than positive sentiments with the passing years. Results also indicate that the data volume has increased since 2019 and peaked in 2022. Negative comments peaked in January 2022, and based on our analysis, such negative comments followed news covering the opening of the China–Laos Railway on December 1, 2021. Video contents were related to the Thai–China HSR Project, which provides comparative reviews and analysis of government operations. Additionally, we explore the possibility of integrating AI technology based on the ChatGPT 4 model to support data interpretation. Although the AI model can interpret data quickly and efficiently serve as a convenient method for users, the results lack the in-depth analysis that should be done by experts in the field. The proposed framework could be useful to government agencies and can be used to quickly and efficiently survey and track public opinion. The results can be used for policy planning, strategic decision-making, and improving communications to better inform citizens about projects and operations, leading to the country’s sustainable economic and social development.

Особливості бізнес-планування у сфері гостинності

The article concentrates on the evolving context of business planning in the hospitality industry, exploring flexible strategies for addressing the negative industry-wide factors that have an impact. The hospitality industry is subject to several operational factors, including revenue generation, cost management, human resources, and marketing, which are influenced by seasonal variations. This necessitates the implementation of strategies to mitigate the impact of fluctuating demand. The high level of competition in the hospitality sector requires a clear competitive advantage, which may be achieved through factors such as location, the provision of high-quality service, innovative design, or a thematic focus. These factors must be strategically employed to distinguish businesses from one another. External factors, including economic conditions, political stability, and environmental risks, significantly influence the hospitality industry. Implementing robust scenario planning, risk management, and service diversification strategies is essential to mitigate these risks. Financial planning is critical to business planning and success, as financial obligations in the hospitality industry underscore the importance of a comprehensive investment analysis. The hospitality industry’s primary asset is its human capital. , strategies should be employed to create a positive working environment, invest in staff training, and implement incentive programs to attract, develop, and retain talent. Guests’ safety and maintaining a positive reputation for hospitality establishments are contingent upon monitoring reviews, responding to negative comments, and utilizing a positive image. The study highlights the necessity for an integrated methodology to be employed in planning business operations within the hospitality sector. Keywords: business planning, hotel and restaurant complex, hospitality industry, stages of organizational culture formation, business.

Quitting on TikTok: Effects of Message Themes, Frames, and Sources on Engagement with Vaping Cessation Videos

This study examined how message themes, frames, and sources in vaping cessation videos on TikTok influenced positive (i.e. likes, shares, positive comments regarding quitting vaping) and negative video engagement (i.e. negative comments regarding quitting vaping). TikTok videos (N = 412) with the hashtags #quitvaping and #quittingvaping were analyzed. Aspect-based sentiment analysis was conducted to evaluate the sentiment of quitting vaping in comments. Negative binomial regression models predicted video engagement from six message themes, ratios of gain and loss frames, and message sources. Themes related to nicotine addiction and physical health effectively drove positive engagement, such as likes and shares. The theme of harmful chemicals elicited mixed responses, generating both positive and negative comments regarding quitting vaping. Videos with a higher ratio of gain frames led to more positive engagement, including likes, shares, and positive comments regarding quitting vaping. Sources with informal expertise (e.g. those who have successfully quit vaping) and current e-cigarette users were more effective in engaging the TikTok audience than non-expert and non-user sources. These findings provide insights into messaging strategies that can effectively engage TikTok audiences and encourage vaping cessation.

Influence of Peer Body Shape Norm and Peer Pressure Related to Body Shape on Social Media on Body Image Over-distortion of Early Adolescent Girls

This study aimed to explore the characteristics of early adolescent girls with an over-distorted body image and to examine the influence of peer descriptive norm and peer injunctive norm related to body shape and peer pressure for thinness on social media on body image over-distortion. The participants were 505 female adolescents in the 1st and 2nd grades of middle school. Descriptive statistics, frequency analysis, and binary logistic regression were used to analyze the data with SPSS 26.0. The results were as follows. First, the body image over-distortion group contained more 2nd-grader early adolescent girls than 1st graders and approximately three-quarters of the body image over-distortion group had previously attempted to lose weight. Second, peer pressure for thinness on social media significantly predicted whether early adolescent girls were in the body image over-distortion group compared to the non-distortion group. These outcomes suggest that it is necessary to create a social media culture that encourages early adolescent girls to have a realistic and healthy body shape. The results also highlight the importance of developing social media literacy education programs that inform early adolescents of the potential harm of negative comments on social media, and teach them how to recognize and dismiss indiscriminate and harmful comments and contents on social media.

Unlocking (re)purchase potential through corporate responsiveness on social networks: The role of perceived customer orientation

Social media marketing offers companies a new opportunity to connect with consumers through customer interactions. However, resource constraints may prevent companies from responding to every consumer comment. In light of this, the “reply to random comments strategy” emerges as an innovative approach where companies choose to respond to a mix of positive and negative comments. Yet, there is a lack of research and no standard practice for this strategy. This research used a mixed-method approach and signaling theory as a theoretical framework to provide extensive insights into how consumers react to various corporate response rates to random comments on social networks. Qualitative insights were gained through focus group discussions, while an empirical investigation was conducted using least squares modeling. The findings highlight the advantages of a high corporate response rate and the importance of signaling a strong customer orientation to enhance (re)purchase intentions of commenting and observing social network users. They also reveal the crucial mediating role of perceived customer orientation as a novel variable in this context. This research provides social media managers with guidelines on enhancing social network users' (re)purchase intentions by implementing a customer-oriented response strategy. The insights help practitioners build and maintain customer relationships, contributing to a company’s long-term success.

A Case Study of Negated Adjectives in Commuters’ Twitter Complaints

In today’s digital society, social networks such as Twitter are a preferred place for expressing one’s emotions, especially when they are negative. Despite a growing interest in the variety of linguistic realizations of commuters’ complaints, little attention has so far been paid to writers’ choices, especially when morphologically or syntactically simpler alternative formulations are available. A typical example is the “inference towards the antonym” triggered by the negation of contrary adjectives, an effect that is stronger for positive compared to negative adjectives. In the context of railway transport, a customer could use the negative statement The train is not clean instead of the corresponding affirmative sentence The train is dirty. It remains unclear, in our current state of knowledge, why online customers would prefer more complex constructions to voice their criticisms. Based on a large corpus of tweets sent to the French and Belgian national railway companies by their customers, I have semi-automatically extracted instances of not (very) + adjective (ADJ). Based on previous observations in the literature, I expected positive adjectives to be more frequently used in these negative environments compared to negative ones. As recent research demonstrates that one’s desire to save the interlocutor’s face is not necessarily the only reason why positive adjectives are used in linguistically negative environments, other motivations will also be considered. More precisely, I suggest that in a context where negativity is prevalent, customers using negated positive adjectives kill two birds with one stone: not only do they signal an issue with a product or a service, pointing to expectations that have not been met by the company, but they also mitigate the impact of their negative comments to the positive face of the service managers with whom they are interacting. By offering a quantitative, corpus-based analysis of negative constructions, complemented by a qualitative linguistic analysis of selected examples, this research sheds new light on users’ lexical choices in online negative customer feedback.

SENTIMENT ANALYSIS OF ONLINE LOANS ON TWITTER USING LEXICON BASED METHODS AND SUPPORT VECTOR MACHINE (SVM)

Technological developments are increasingly rapid and moving towards digital, which in the end technology can also help people who are experiencing economic problems, namely with online loan services. Even though there are many conveniences provided by online loan services, of course not all people give positive comments because there are quite a few negative comments about this service.One of the social media that is widely used by the public to provide comments about online loans is Twitter. Sentiment analysis is a data processing process to obtain information about whether an opinion sentence tends to be positive, negative or even neutral. This research contains sentiment analysis towards Online Loans on Twitter using the Lexicon Based and Support Vector Machine methods. From the results of this research, the accuracy for SVM was 82.36%. From these results it can be concluded that the use of the Lexicon Based and Support Vector Machine methods is considered quite good and effective for classifying sentiment

A Mixed-Methods study of the impact of sex and situational pain catastrophizing on pain sensitivity.

It is well established that catastrophic thinking about pain modulates clinical pain severity, but it may also relate to interindividual differences in the pain experience during procedures. This mixed-methods study investigated the relationship between ratings of situational pain catastrophizing and reported pain sensitivity in the context of receiving a nerve block without sedation, and explored participants' experiences. Healthy volunteers (n = 42) completed baseline psychosocial questionnaires, underwent quantitative sensory testing, and received a lower extremity nerve block, followed by further psychosocial assessment and interviews. Associations of catastrophizing scores with pain sensitivity and procedural site pain were assessed using Spearman's correlations. Interviews were reviewed using an immersion/crystallization approach to identify emergent themes. Greater situational catastrophizing scores were associated with higher pain sensitivity, measured as lower pain threshold and tolerance. Although females exhibited greater pain sensitivity generally, moderation analysis revealed a significant association between situational catastrophizing scores and pain sensitivity only among male participants. Qualitative interviews revealed the importance of participants' emotional responses to pain, and a mismatch of expectation and experience with procedural pain. Males also reported more negative comments about procedural pain. Examination of the variable subjective experience while receiving a nerve block in this experimental lab-based study revealed an important relationship between situational pain catastrophizing scores and pain sensitivity, which was more prominent among male participants. These findings reinforce how insight into individual expectations, emotions, and thought processes may impact pain sensitivity during procedures, and may inform strategies to personalize care, improving patient satisfaction and procedural acceptance.

Analisis Sentimen Komentar Konsumen Industri Jamu di Media Sosial menggunakan Artificial Neural Network dan K-Nearest Neighbor

Phytopharmaceutical plants have become one of the main commodities contributing significantly to the economy through their use in the pharmaceutical, cosmetic, and health industries. However, behind this economic potential, traditional herbal medicine businesses often face challenges, particularly in promotion and brand identity. Social media platforms like Instagram have now introduced unique features to support business and marketing, primarily by providing in-depth information about herbal products and offering opportunities for businesses to receive feedback from consumers. Comments on social media are valuable but often unstructured; hence, sentiment analysis is necessary to organize and categorize this data. By combining comment data with information from Google Trends, cause-and-effect relationships from comments during specific periods can be identified using path analysis. This research aims to analyze consumer comments on the Sidomuncul company's Instagram platform, with the hope of benefiting the company and advancing herbal medicine products. The methods used in this study include Artificial Neural Network (ANN) and K-nearest neighbor (KNN) to classify comments into positive, negative, and neutral categories. Both methods show satisfactory results in classification, with an average accuracy of 0.887 for ANN and 0.874 for KNN. However, the ROC curve for the KNN model indicates a relatively low AUC value in classifying negative comments, at 0.598.

The role of sexual partner in women's seeking for labiaplasty: a systematic review and meta-analysis.

The primary reasons for labiaplasty usually revolve around aesthetic, sexual, and functional concerns. Upon delving deeper into these issues, it becomes apparent that sexual partners play a controversial role in influencing women's decisions to undergo surgery. This study aimed to investigate the impact of sexual partners on women's choices to pursue labiaplasty. A comprehensive search was conducted across electronic databases covering the period from January 2000 to February 2024. After removing duplicates, a total of 931 articles were retrieved by searching keywords in titles and abstracts. The meta-analysis revealed that 36.7% of women who sought labiaplasty cited their partners' negative comments as a factor influencing their decision. After applying the eligibility criteria and excluding irrelevant articles, a total of 12 articles involving 962 participants were included in the analysis. With the exception of 2 articles, the majority of the studies suggested a discernible influence of male partners on women's decisions to seek labiaplasty. Frequently, sexual partners are not the primary decision makers, nor do they exert significant pressure when it comes to seeking labiaplasty. In certain instances, women seeking labiaplasty acknowledged that their sexual partners did influence their decisions, either by making disparaging comments about their genitalia or by directly pressuring or requesting them to undergo labiaplasty. Additionally, women might opt for labiaplasty out of fear of their partner's negative remarks or to enhance sexual pleasure for their partners. For a more accurate result, a meta-analysis was conducted noting a considerable heterogeneity. The findings of this study can be applied in prelabiaplasty counseling sessions to acknowledge and explore the role of the sexual partner in women's decision making. This study stands as the inaugural systematic review examining the impact of sexual partners on women seeking labiaplasty, encompassing all original studies exploring the role of the sexual partner. However, a notable limitation lies in the varied interpretations of the sexual partner's role, that the heterogeneous nature of these interpretations poses a challenge to providing a more precise answer through meta-analysis. Based on the findings of this systematic review, it is evident that sexual partners exert multifaceted influences on women's decisions to seek labiaplasty. While not serving as the primary decision makers, women opt for labiaplasty with the aim of enhancing attractiveness in sexual relationships and mitigating potential negative comments from their partners.

Research on the Sexualization or Empowerment of High-heeled Dancing on Social Media

With the rapid development of modern technology and the internet, social media has become the mainstream way to shape groups. Many people will express their ideas online, which can greatly affect their psychology and spirit. Heel dancing has evolved, incorporating different dance styles and cultural influences. In terms of high-heeled dancing, social media also became a hotbed of debate.This article delves into the sexualization of heel dance on social media platforms, highlighting the difficulties dancers, particularly women, encounter as their image shapes society's perceptions. By reviewing and analysing historical insights, we have revealed the social factors that contribute to this phenomenon. In addition, the paper aims to challenge stereotypes and regain the empowering narrative of heel dance as a symbol of strength and self-expression. According to the study, social media, pop culture, and fashion, whether heels dancing or its industry, empower women overall, portraying a powerful, free, and diverse female role. Therefore, eradicating negative comments and stereotypes about heels and other dances would be beneficial.

Emotional contagion on social media and the simulation of intervention strategies after a disaster event: a modeling study

With the advent of climate change and the 5 G era, online communities are increasingly becoming the main medium for information dissemination after emergencies such as natural disasters. The widespread dissemination of negative online information may generate cyber violence or lead to serious adverse psychological outcomes. This study considered a natural disaster event involving avoidable deaths and child casualties as an example to identify emotional contagion and conduct simulation interventions. Data about the aftermath of the 8·13 flash flood in the Longcaogou Scenic Area, Sichuan Province, China, were derived from the Chinese Sina microblog. We analyzed key parameters and modeled them in a dynamic model. We further evaluated the effects of implementing intervention measures (such as transmission path interruption and changing the number of different emotions) on emotional spread. The overall sentiment of posters after this flood was negative, with three epidemic peaks. Negative emotions were more persistent and contagious than positive emotions. Reducing the number of negative blog posts by half could have led to a 14.97% reduction in negative comments and a 7.17% reduction in positive comments. Simultaneously, reducing the number of negative blog posts and increasing the number of positive posts would have helped reduce the relative ratio of negative to positive comments. The findings have theoretical and practical implications for developing an emotional contagion model and formulating intervention strategies to guide public opinion after an emergency that involves extensive online debate.

Metaverse Technologies in Painting Education and Their Influence on Student Creativity and Self-Expression

The role of this study is to establish the influence of multiverse technologies on the self-esteem and creative abilities of painting students. For this, a focus group of 75 first-year students of the City College of Xi’an Jiaotong University studying at the Core level program was created as part of the case study method. The results showed a high percentage of individuals who had previously encountered AI-generated artwork, with 81% saying yes, 17% saying no, and 2% responding not sure about their answer. As a result, 25% of students claimed that they had theoretical information about the use of the multiverse for educational purposes. The practical results of the research can be used in the development of future virtual galleries, taking into account both the positive and negative comments of respondents. Thus, future work may include supplementing the previous findings on consumer acceptance of the metaverse technology.