Media Comments Research Articles

‘A Victimless Crime’? Implications of eSports Extensions of Sport Club Brands for Brand Management From a Multi-Actor-Dominant Logic

Adhering to the multi-actor-dominant logic of sport brands, this study examines the influence of eSports extensions on the dynamic branding processes within the ecosystems of sport club brands (SCB). The findings build on a qualitative multi-case study (N = 11 SCB in the German Bundesliga implementing different types of eSports extensions), using 20 semi-structured interviews and netnographic analysis of more than 70.000 social media comments. SCB preserve but also translate brand identity in the context of eSports. The fine line between both strategies is reflected in internal negotiation processes. eSports extensions receive little attention from extant actors. However, ‘relevant’ eSports extensions initiate discursive processes among extant and novel actors and the development of diverging brand meanings. This research contributes to literature on eSports and brand extensions by enhancing the understanding of the effects of eSports extensions on SCB. In addition, this study offers implications for sport managers, developing and implementing eSports extensions.

The impact of social media reports on nurses’ job satisfaction: A cross-section suvery

This study aims to examine the impact of social media reports (SMR) on nurses' job satisfaction (NJS) and investigate the moderating effect of nurse manager overconfidence (NMO). Focusing on nurses in tertiary public hospitals in Guilin, China, we constructed an analytical dataset using survey data from January to June 2024 and social media comments collected through web scraping technology. Results reveal a significant positive correlation between SMR and NJS, indicating that increases in social media reports are associated with higher job satisfaction among nurses. However, when NMO acts as a moderating factor, the positive effect of SMR on NJS is attenuated, suggesting that overconfidence among nurse managers may diminish the influence of social media feedback. Furthermore, the study employs robustness tests, including the Replace Variables Method, Entropy Balancing Method, Instrumental Variable Method (IV-2LS), and Other Methods, effectively addressing endogeneity issues and confirming the reliability of these findings. This research offers theoretical support for enhancing hospital management and extends the literature on the moderating role of managerial characteristics on job satisfaction, providing practical insights for promoting high-quality hospital development.

Ecoproducts in the Dynamic Era of Digital Communication: A Neuromarketing Study of Users’ Emotional Reactions on Social Media

In the present era, where social media have become a primary tool for interaction between brands and consumers, the importance of emotional reactions triggered by observing public comments is increasingly emphasised. This study analyses how these reactions shape the decision-making process when purchasing eco-friendly products. The aim of this study is to bridge the gap in the analysis of emotional reactions from social media users who are exposed to various unofficial information published on social media while gathering information about eco-products, which can significantly influence their purchasing decisions. The objective is to examine, compare, and evaluate how positive and negative sentiment in user comments affects the perception and value of eco-products amongst other social media users. The findings indicate that posts with positive comments foster increased engagement and a favourable perception of products, while negative comments lead to doubt and frustration. In the neuromarketing experiment, we found that 81.8% of respondents considered the visual design of the eco-product and the ecological brand message attractive, with 63.6% reporting that negative social media comments had a significant impact on their perception of the brand. These results support the hypothesis that emotional reactions to comments are a strong factor in consumer decision-making, suggesting that positive reviews may serve as social proof, while negative comments can cause cognitive dissonance. Through this study, we aim to contribute to a deeper understanding of the dynamics between emotional reactions and the perception of eco-products in the digital communication era, which has significant implications for the marketing strategies of ecological brands.

Is Fairyland for Everyone? Mapping online discourse on gender debates in Hungary

Abstract Over the past decade, Hungary has become a noteworthy example of democratic backsliding, marked by a pronounced shift towards conservative values and traditional gender roles within government policies. This trend, centred around Christian principles, has manifested in political campaigns actively opposing LGBTQ+ rights and the challenging of normative family structure. The resultant media campaigns and policy implementations have ignited extensive public discourse on gender and sexuality, prominently visible on social media platforms. This study conducts a qualitative analysis of the online discussion surrounding the LGBTQ+ children’s book, Fairyland Is for Everyone, to explore the contemporary gender discourse in Hungary. By examining social media comments under Hungarian online news articles, the research identifies three prevailing discursive lenses—heteronormative familism, neocolonialism, and diversity and inclusion—illustrating both the concurrent rise of anti-gender movements and the fortification of LGBTQ+ allyship in Hungary, while also considering broader transnational trends in LGBTQ+ rights and visibility.

The Impact of Comment Slant and Comment Tone on Digital Health Communication Among Polarized Publics: A Web-Based Survey Experiment.

Public attitudes toward health issues are becoming increasingly polarized, as seen in social media comments, which vary from supportive to oppositional and frequently include uncivil language. The combined effects of comment slant and comment tone on health behavior among a polarized public need further examination. This study aims to examine how social media users' prior attitudes toward mask wearing and their exposure to a mask-wearing-promoting post, synchronized with polarized and hostile discussions, affect their compliance with mask wearing. The study was a web-based survey experiment with participants recruited from Amazon Mechanical Turk. A total of 522 participants provided consent and completed the study. Participants were assigned to read a fictitious mask-wearing-promoting social media post with either civil anti-mask-wearing comments (130/522, 24.9%), civil pro-mask-wearing comments (129/522, 24.7%), uncivil anti-mask-wearing comments (131/522, 25.1%), or uncivil pro-mask-wearing comments (132/522, 25.3%). Following this, the participants were asked to complete self-assessed questionnaires. The PROCESS macro in SPSS (model 12; IBM Corp) was used to test the 3-way interaction effects between comment slant, comment tone, and prior attitudes on participants' presumed influence from the post and their behavioral intention to comply with mask-wearing. Anti-mask-wearing comments led social media users to presume less influence about others' acceptance of masks (B=1.49; P<.001; 95% CI 0.98-2.00) and resulted in decreased mask-wearing intention (B=0.07; P=.03; 95% CI 0.01-0.13). Comment tone with incivility also reduced compliance with mask-wearing (B=-0.44; P=.02; 95% CI -0.81 to -0.07). Furthermore, polarized attitudes had a direct impact (B=0.86; P<.001; 95% CI 0.45-1.26) and also interacted with both the slant and tone of comments, influencing mask-wearing intention. Pro-mask-wearing comments enhanced presumed influence and compliance of mask-wearing, but incivility in the comments hindered this positive impact. Antimaskers showed increased compliance when they were unable to find civil support for their opinion in the social media environment. The findings suggest the need to correct and moderate uncivil language and misleading information in online comment sections while encouraging the posting of supportive and civil comments. In addition, information literacy programs are needed to prevent the public from being misled by polarized comments.

Moral Comments in Social Media: Analyzing the Role of Ideology-Matching Moral Framing and Impression Motivation in the Persuasive Effect of User Comments on YouTube

ABSTRACT This research explores how users form attitudes when they are presented with online videos and moral comments from their fellow audience. Based on the Heuristic-Systematic Model (HSM) and Moral Foundations Theory (MFT), the study aims to find out how different moral foundations represented in user comments interact with the motivational state, the political orientation, and the moral beliefs of the viewer. In two pre-registered experiments (N = 314 and N = 1015), the inclusion of moral arguments within comments below a YouTube video (harm vs. authority), their valence (positive vs. negative) and the participants’ motivational states (high vs. low impression motivation) were varied. While Experiment 1 revealed no significant effects regarding the persuasive effect of user comments and accompanying moral arguments, Experiment 2 showed a more general effect of comment valence on viewers’ attitude formation. These results help to specify the conditions under which user comments may lead individuals to construct their attitude in a way that fits the perceived majority opinion.

Empowering Retail Dual Transformer-Based Profound Product Recommendation Using Multi-Model Review

Advancements in technology have significantly changed how we interact on social media platforms, where reviews and comments heavily influence consumer decisions. Traditionally, opinion mining has focused on textual data, overlooking the valuable insights present in customer-uploaded images—a concept we term Multus-Medium. This paper introduces a multimodal strategy for product recommendations that utilizes both text and image data. The proposed approach involves data collection, preprocessing, and sentiment analysis using Vti for images and SpanBERT for text reviews. These outputs are then fused to generate a final recommendation. The proposed model demonstrates superior performance, achieving 91.55% accuracy on the Amazon dataset and 90.89% on the Kaggle dataset. These compelling findings underscore the potential of our approach, offering a comprehensive and precise method for opinion mining in the era of social media-driven product reviews, ultimately aiding consumers in making informed purchasing decisions.

The impact of ChatGPT’s competencies on users’ intention to use

ABSTRACT Driven by ChatGPT’s popularity, generative conversational artificial intelligence (GCAI) has captured global interest. Despite its widespread adoption, the competencies of GCAI and their influence on users’ intention to use it remain underexplored. This study examines the effect of GCAI competencies on users’ intention to use GCAI. Using a mixed-methods approach, we analyze social media comments and identify four key GCAI competencies. Based on media naturalness theory, trust literature, and the stimulus-organism-response model, we propose and test a research model via a survey. Our results show that accuracy of response, self-learning, and natural language interaction enhance users’ intention to use GCAI and trust in it, while human-like empathy influences trust but not intention. Trust fully mediates the relationship between human-like empathy and intention, and partially mediates the relationship between the other three competencies and intention. This study fills a gap in understanding GCAI’s appeal and offers guidance for developers and marketers.

Don’t Read the Comments: Discourse About COVID-19 Vaccines in a State Health Department's Social Media Comments

Don’t Read the Comments: Discourse About COVID-19 Vaccines in a State Health Department's Social Media Comments

Exploring the Impact of E-WOM Information via Social Media on Customer Purchasing Decision: A Mediating Role of Customer Satisfaction

The study investigates the impact of E-WOM information on purchasing decisions, using customer satisfaction as a mediator. It examines E-WOM information as independent variables, such as quality, quantity, and credibility, and as dependent variables, such as consumer satisfaction and purchasing decisions, with customer satisfaction serving as a mediator to investigate the relationship between E-WOM information and purchasing decisions. A questionnaire was issued to 307 social media-active clients, and the hypotheses were tested using quantitative methods. Data analysis comprised descriptive statistics, Cronbach's alpha, skewness and kurtosis, and Pearson correlation coefficient, as well as a fit model for measuring questionnaire reliability and validity, regression for sub-hypotheses, and a path model for evaluating main hypotheses. The findings revealed that all three dimensions of E-WOM information had a positive impact on customer satisfaction and purchase decisions, both individually and jointly. Customer satisfaction has a positive influence on purchasing decisions. Furthermore, E-WOM information has been shown to positively impact purchasing decisions via consumer satisfaction. The study suggests that organizations should understand the dimensions that impact customer satisfaction and purchasing decisions in order to fulfill their goals, remain ahead of the competition, and obtain a competitive advantage. Proper tracking of social media reviews, comments, and recommendations may help organizations deliver answers, increase customer satisfaction, and aid in making purchasing decisions

Application of Topic Modelling Technology to the Analysis of Social Media Comments in the Context of State Identity Politics Research

In the situation of a shrinking field of public politics and a crisis of political trust, citizens may seek an alternative arena for presenting their own point of view. The social Internet space serves as a virtual projection of public contradictions and acts as an arena for the presentation and confrontation of political interests. At the same time, the increasing state presence in virtual space and the growing trust to online sources of information make social media an important channel for promoting certain patterns of political interpretations. The aim of this paper is to analyse the reactions of social media users to discover their attitudes towards the main narratives of contemporary identity politics of the Russian state. We used the Topic modelling method to study citizens’ reactions to various aspects of state identity politics. The total number of comments in the collected database is 8,023 (09/2022‑09/2023). In almost all the identified topics we can note the polarity of citizens’ opinions, examples of which are given in the article. However, there are a few topics where the users’ opinion is quite consolidated; for example, the image of the Crimean bridge on the cover of new textbooks was widely supported in comments, while the topic of traditional values, on the contrary, evokes negative feelings and shows “public tiredness”. Despite the limitations described in the conclusion of the article, the study demonstrates the high potential of applying the method of topic modelling to the analysis of the reactions of social media users.

Stance-Taking and Responses in Selected Social Media Posts and Comments on Arise TV Morning Show

This study investigates stance-taking and responses in selected social media posts and comments on the Arise TV Morning Show. Stance-taking features and engagement responses in the selected texts on Facebook and X (formerly Twitter) were identified and analyzed in the study. Norman Fairclough’s (1989) Critical Discourse Analysis was adopted as the analytical tool for the study. Fairclough’s approach facilitates the investigation of meaning and agendas embedded within texts, thereby enhancing the understanding of discourse. Five (5) posts (three for Facebook and two for X) and twenty-five (25) responses (i.e. fifteen for Facebook and ten for X; five comments under each post) formed the data for the study. Qualitative content analysis was used for the data analysis. The findings reveal that linguistic items are important in positioning oneself as an authority to influence other participants in a discourse on the Facebook and X platforms. It also shows that the most prominent features of stance-taking and responses used by social media users are boosters and self-mention. They serve as discursive strategies employed by writers to convince other discussants to align with their position.

Sense or Sensibility? Netizens’ Choice of Social Media Comments in an Authoritarian Regime

Abstract While the Internet in China is subjected to heavy state regulations, Chinese netizens can still access online comments that deviate from official discourse on many issues. To prevent online discussions from getting out of hand, the Chinese government uses soft propaganda such as online comments to channel public opinions. Which type of online comments appeal to Chinese netizens? Using a survey experimental design, we examine the appeal of 4 distinct types of online comments on certain policies. We find that our survey respondents spend significantly more time in consuming emotional comments that deviate from official discourse. When it comes to the effect on attitude, however, we find that deviating-emotional comments are no more persuasive than deviating-informational comments. Our results call into question the effectiveness of China’s state propaganda in channeling online public opinions while highlighting the importance of alternative information in shaping public opinions in an authoritarian context.

Cascaded Adaptive Dilated Temporal Convolution Network-Based Efficient Sentiment Analysis Model from Social Media Posts

Sentimental analysis is one of the most complicated tasks in text mining. It is the process of converting unstructured text to structural text to identify the meaningful pattern of data. Different kinds of sentiments in social media posts are classified into positive and negative. Natural Language Processing (NLP) plays an imperative task in examining sentiments on social media. Sentimental analysis techniques frequently use text data to help to monitor customer feedback about products and understand the needs of customers in the field of business. The text data are gathered from social media comments that lead to several drawbacks such as spelling errors, noise, and unstructured data, and some of the data are in abbreviation form in which abbreviations are hard to understand from the text data. Therefore, the innovative sentiment analysis method is implemented to identify the kinds of sentiments from the collected social media posts. At first, the text data are assembled from the social media posts. The collected text data are subjected to text preprocessing techniques to improve the data quality. NLP techniques such as a bag of n-grams, glove embedding, and Bidirectional Encoder Representations from Transformers (BERT) are applied to separate the features from the text data. The removed features from these techniques are given to the fusion of the optimal feature stage, where the weight optimization takes place via the Mutated Random Parameter-based Serval Optimization Algorithm (MRP-SOA). The attained optimal weighted fused features contain the most relevant information, and it is fed to the classifier for analyzing the sentiments. For analyzing the sentiments, the Cascaded Adaptive Dilated Temporal Convolutional Network (CADTCN) is utilized, and the parameters from ADTCN are optimized with the same to get higher classification outcomes. The analysis outcomes are compared with the traditional sentiment analysis models in terms of various metrics to show the success of the advanced design.

Enhancing human well-being through cognitive and affective pathways linking landscape sensation to cultural ecosystem services

ContextLandscape sensation is essential for the delivery of cultural ecosystem services (CESs), yet the pathways through which these services are delivered remain inadequately understood. Exploring how people obtain CESs from landscapes facilitates better understanding of the tradeoffs and synergies between ecosystem services and landscape sustainability.ObjectivesThis study aimed to elucidate the sensory pathways that links landscape attributes to CESs, focusing on the roles of cognitive and affective experiences.MethodsWe analyzed social media comments for the measurement scale of cognition. We employed partial least squares structural equation modeling to integrate sensation, cognition, affect, and satisfaction, using questionnaire data (n = 503).ResultsCognitive comprehensions and affective responses play a crucial role in interpreting CESs while sensory experiences do not directly determine people’s satisfaction with CESs. The effective pathways are achieved through the sole mediator of cognition or by serial mediators of cognition and affect. Of the two mediators, cognition has a more profound mediating effect than affect.ConclusionsBoth physical and biological components, such as landscape sensory attributes, as well as cognitive and affective responses, influence human-nature interactions. These components should be considered when promoting the sustainability of human-dominated landscapes.

Integrating Hybrid Neural Networks and Domain-Specific Embeddings for Detecting Hate Content in Code Mixed Social Media Comments

Integrating Hybrid Neural Networks and Domain-Specific Embeddings for Detecting Hate Content in Code Mixed Social Media Comments

Exploring the Influence of Live Streamer s Personality and Features on Customer Purchasing Decisions

With the rapid development of e-commerce, live streaming has become an important channel for marketing as an emerging sales model. As the core of this model, the personality and features of the live streamer have a significant impact on the audience s purchasing decisions. This paper analyzes the impact of the live streamers language, behavior, and interaction methods on customer purchase intention by qualitative analysis and observing live streamer videos and social media comments of Dong Yuhui, a best-known live streamer of the Oriental Selection Live Stream. The study found that the live streamer s professionalism, sense of humor, and trustworthiness are key factors that influence customer purchase decisions.

Aspect-Based Sentiment Analysis on Social Media Comments (Twitter) : The Attributes of Service Robots in the Hotel and Restaurant Industry

ABSTRACT Service robots are becoming more prevalent in the service industry, yet the impact they have on customer experiences is not well-documented. This study identified consumer emotions toward service robots in hotels and restaurants, focusing on how specific attributes of these robots affect consumer emotions. Furthermore, it explored which countries generate the most comments on these service robot attributes and the nature of consumer emotions within these regions. Utilizing sentiment analysis, the study examined 52,513 English-language tweets about hotel and restaurant service robots. Additionally, logistic regression analysis helped quantify the impact of robot attributes – categorized as physical, functional, and relational – on different classes of emotions. The findings reveal that customers of restaurants and hotels were most influenced by the physical and relational attributes of service robots, respectively, with functional attributes having the least impact. The logistic regression analysis offered significant insights into how service robot attributes influence consumer experiences in hotels and restaurants.

Herausforderung Rezeptionsanalyse: zur Wahrnehmung von Wissenschaftskommunikation während der Coronapandemie

Abstract More than ever before, the COVID-19 pandemic has highlighted the importance and challenges of high-quality science communication. In various phases of the pandemic, the public voiced discontent about the way scientific results were communicated. This article is anchored in the field of media linguistic reception research. Its aim is less to shed light on the quality of science communication itself than to pursue the question which methods in reception research are most suitable for illuminating how recipients perceived the pandemic. To this end, we compare the results of a survey with the analysis of comments from the comment sections of four YouTube videos. The results imply that, for this specific case, the analysis of social media comments is more suitable as an addition to the survey rather than constituting an alternative because surveys can elicit targeted responses whereas comment sections contain a whole spectrum of topics addressed. The study also comes to the conclusion that, in addition to target-group-oriented, comprehensible communication, it is above all important to raise awareness for the kind of processes that shape an academic’s work.

Stakeholder engagement and nonprofit organizations' (NPOs) accountability: a social media-based study of the Australian 2019/2020 bushfire crisis

PurposeThis study aims to examine the impact of stakeholder engagement on accountability, within nonprofit organizations (NPOs). Given the pivotal role NPOs play in disaster management and community welfare, it is crucial to gain an understanding of the obligations of NPOs, in terms of their disaster responses and accountability.Design/methodology/approachUsing a case-study approach, the investigation features a content analysis of social media comments regarding the Australian Red Cross’ (ARC) funds’ allocation during the 2019/2020 bushfires, followed by a similar analysis of ARC's reports. Inspired by Carnegie et al.'s (2021) definition of accounting as a social science, this study uses dialogic theory and a transformative participatory framework, to evaluate how interactive stakeholder engagement influenced accountability strategies used by the NPO, to ensure its sustainable development.FindingsThe findings reveal that there was a significant increase in stakeholder engagement on social media, following negative media coverage, with participants voicing concerns over ARC’s method of funds’ allocation, delays in funds distribution and seemingly excessive administrative costs. ARC addressed these concerns by issuing Bushfire Reports, and conducting online Q&A sessions, in a bid to establish transparency. This study emphasizes how dialogic accounting can challenge accounting's limited scope – one that often overlooks ecological concerns and social justice.Originality/valueThis study uses the perspective of dialogic accounting theory to explore the relationship between stakeholder engagement on social media, and NPO accountability. It demonstrates how robust stakeholder engagement can challenge NPOs to establish accountability, thereby bridging the information gap between themselves and the public. The use of dialogic accounting theory allows the study to shift from the traditional focus of accounting research, which is the financial objectives of powerful entities, to the voices of the marginalized, the stakeholders, who are impacted by NPO decisions, and, in doing so, it highlights the potential for NPOs to foster accountability, and so advance sustainable development initiatives.