User-generated Research Articles

Social media brand engagement and perceived risk in purchase: a conceptual framework

Objective of the study: This research paper aims to develop a conceptual framework based on an extensive literature review in the area of social media communication (SMC) consisting of Firm Generated Content (FGC) and User Generated Content (UGC) to unearth their influences on social media brand engagement (SMBE) and customer-based brand equity (CBBE). The role played by perceived risk is also highlighted. Methodology/approach: This study has critically evaluated the literature to propose the conceptual framework using 101 research articles from 1974 to 2023 that directly or indirectly comprised at least one of the constructs. Main results: This literature review found contradictory results regarding which source is more credible on social media, the firm or the user. This empirical gap is firstly deliberated. Secondly, the disparity on whether engagement drives equity or equity drives engagement on social media led to the conceptual gap. The conceptual model is formulated based on this debate. Theoretical/methodological contributions: While the independent constructs are drawn from the elaboration likelihood model and source credibility theory, the mediating role of SMBE is posited based on the social identity theory. Relevance/originality: In the context of social media, this conceptual model highlights the mediating effect of brand engagement and the moderating effect of perceived risk between social media communication and CBBE. The influence of mediation and moderation could explain the path to CBBE more explicitly.

A simple and cost-effective sample preparation and storage method for stable isotope analysis of atmospheric CO2 for GasBench II/continuous flow isotope ratio mass spectrometry.

The stable isotope compositions of atmospheric CO2 can provide useful insight into various geochemical processes and carbon cycles on Earth, which is critical for understanding of Earth's changing climate. Here, we present a simple and cost-effective analytical method for the collection and measurement of carbon and oxygen isotope compositions of atmospheric CO2. Air samples of ~150 mL were collected individually or collectively using our simple active air collection system and then extracted on a vacuum purification line to remove noncondensable gases and atmospheric water vapor. The efficiency of removing atmospheric water vapor was tested by using a magnesium perchlorate desiccant trap and a dry ice/ethanol trap. Lastly, a "J-Cut tube sealing/cracking method" was developed to store and transfer purified atmospheric CO2 to the GasBench II and CF-IRMS system for δ13C and δ18O measurements. The collective active air collection method combined with the full sample air extraction method for a 3-min transfer time or "Full 3m TE" yields the best analytical precision of 0.07‰ (δ13C) and 0.04‰ (δ18O). Removing atmospheric water vapor from air samples is not necessary for δ13C, but essential for δ18O measurements. The J-Cut tube sealing/cracking method shows a near 100% effectiveness for the storage and transfer of atmospheric or any CO2. A simple and cost-effect method was developed for the collection, purification, storage, and isotopic analysis of indoor/outdoor atmospheric CO2 samples for general users. This method utilizes a popular headspace gas sample preparation system for CF-IRMS and an easy-to-build vacuum purification line without involving complex and high-cost devices for the preparation of atmospheric CO2.

User generated content in the context of autonomous AI analysis of comparative sstudy of copyright law in the US and India

In today’s rapidly evolving tech landscape, social media’s exponential growth has revolutionized how people create, share, and engage with content. User-generated content (UGC) has become a key part of social networking, empowering individuals to showcase their creativity. However, it also raises significant legal concerns, particularly around copyright. Intellectual property rights and potential copyright infringement issues have become more complex as vast amounts of content are shared publicly across diverse platforms. This paper examines the current state of copyright law in the digital era, focusing on major legal frameworks such as the Digital Millennium Copyright Act (DMCA) in the United States and the Copyright Act of 1957 in India. These frameworks aim to regulate the sharing and protection of online content, though they also face criticism regarding their effectiveness in safeguarding rights while promoting free expression and digital culture. By analyzing these laws, this study seeks to highlight the gap between protecting copyright holders’ rights and fostering a digital space conducive to innovation. Ultimately, the paper argues that while existing laws provide a foundation, they need to evolve to accommodate the unique demands of digital content sharing, balancing creators’ rights with the public interest.

Strategi Pemasaran Efektif Untuk Meningkatkan Penjualan di Era Digital

This study aims to analyze effective marketing strategies for increasing sales in the digital era based on literature review and to identify challenges and solutions in implementing digital marketing strategies. The research employs a literature study approach, with primary data sourced from books, scientific journals, theses, dissertations, e-books, and other written materials. The findings indicate that effective digital marketing strategies include the utilization of social media, email marketing, SEO, product diversification, and e-commerce to reach a broader audience and boost sales. Common challenges include limited resources, lack of technology training, and shifts in consumer behavior. Proposed solutions involve intensive training, creative content management, the use of advanced technologies such as Artificial Neural Networks, as well as optimizing social media and user-generated content. Thus, digital marketing strategies can be a powerful tool for enhancing a company's competitiveness in the digital era, provided the existing challenges are effectively addressed

Rethinking digital entrepreneurship in a digital transformation era: leveraging on brand avatars to boost brand experiences and loyal communities

PurposeThis paper delves into the transformative role of brand avatars within the digital transformation landscape, focusing on their capacity to enhance brand experiences and foster dedicated communities. Brand avatars that allow consumers to customize their appearance hold the potential to elevate various brand attributes, including trust, commitment, loyalty and overall business performance.Design/methodology/approachThis paper aims to gain insights into consumers’ perceptions, attitudes and experiences concerning brand avatars and their influence on brand experiences and community engagement, the study employs quantitative data collection methods, particularly surveys involving consumers.FindingsThe findings have yield both theoretical and practical implications. They will benefit digital entrepreneurs and brand managers aiming to harness the potential of personalized brand avatars in the digital innovation realm, thereby, contributing to the existing body of knowledge in the fields of brand and innovation management. This study, like any empirical endeavor, has its limitations. One significant constraint lies in the reliance on self-reported survey data, which may introduce response biases and potential overestimation of positive perceptions due to the novelty of brand avatars.Practical implicationsThe research explores how personalized brand avatars, with their visually appealing representations, interactive functionalities and emotional expressions, contribute to enrich the innovation management perspective. Moreover, these avatars play a pivotal role in supporting community development, driving user engagement and facilitating the creation of user-generated content within brand communities.Originality/valueThis exploration illuminates the role played by brand avatars in shaping contemporary brand–consumer interactions and community dynamics in the digital environment.

Meta-Morphosis of Copyright and User-Generated Content: Can East Asia’s Emerging Policies Navigate through the Metaverse?

Abstract Social-creative metaverses, which foster user creativity and encourage user-generated content, promise a revolution in digital creativity. However, metaverse developers often enforce strict regulations on user-generated content through user terms and conditions, restricting or permitting its reuse. These rules place an artificial barrier between users and their copyright, often waiving moral rights and making economic rights subject to mandatory licences. Using Second Life as a case study, this article demonstrates how metaverse regulations undermine users’ intellectual property rights and control over their creations. Furthermore, it examines emerging intellectual property policies in Japan, South Korea, and China, noting a lack of awareness regarding the impact of these regulatory layers on user creativity. Highlighting the importance of the external regulation of user terms and conditions, the article proposes potential policies and strategies for East Asia and beyond to protect users’ copyright ownership and mitigate the negative effects of restrictive metaverse terms and conditions.

Exploring User-Generated Content Motivations: A Systematic Review of Theoretical Perspectives and Empirical Gaps in Online Learning

Exploring User-Generated Content Motivations: A Systematic Review of Theoretical Perspectives and Empirical Gaps in Online Learning

The Influence of Social Media Brand-Related Communication on Brand Equity and Consumer Response Towards Online Bootcamp Brands in Indonesia

Education technology industry in Indonesia is experiencing rapid growth, marked by increased adoption and projected revenues, leading to the emergence of companies offering bootcamp services and using social media as a primary promotional tool. This study aims to examine the impact of social media brand-related communication, specifically Firm-Created Content (FCC) and User-Generated Content (UGC), on Brand Equity and consumer response in the online bootcamp market in Indonesia. Using a quantitative approach and online survey method, data were collected from 203 respondents and analyzed using Structural Equation Modeling (SEM). The study reveals that both FCC and UGC are effective tools for building brand equity and enhancing consumer response. Therefore, online bootcamps should focus on developing and implementing effective FCC and UGC strategies to achieve success in this competitive market

Large Language Model Enhanced Logic Tensor Network for Stance Detection

Social media platforms, rich in user-generated content, offer a unique perspective on public opinion, making stance detection an essential task in opinion mining. However, traditional deep neural networks for stance detection often suffer from limitations, including the requirement for large amounts of labeled data, uninterpretability of prediction results, and difficulty in incorporating human intentions and domain knowledge. This paper introduces the First-Order Logic Aggregated Reasoning framework (FOLAR), an innovative approach that integrates first-order logic (FOL) with large language models (LLMs) to enhance the interpretability and efficacy of stance detection. FOLAR comprises three key components: a Knowledge Elicitation module that generates FOL rules using a chain-of-thought prompting method, a Logic Tensor Network (LTN) that encodes these rules for stance detection, and a Multi-Decision Fusion mechanism that aggregates LTNs’ outputs to minimize biases and improve robustness. Our experiments on standard benchmarks demonstrate the effectiveness of FOLAR, showing it as a promising solution for explainable and accurate stance detection. The source code will be made publicly available to foster further research.

The Impact of Augmented Reality Through User-Platform Interactions Towards Continuance Intention with the Effect of User Generation

When users interact with mobile platforms in an Augmented Reality (AR) environment, cognitive and emotional engagements change through different stimuli cues that respond to users’ behavioral intentions. Although AR engages more interactions in mobile platforms, there is a significant gap in assessing UX, considering the physical distance between users and virtual products in a mobile platform. Considering the effect of user generation, the impacts of perceived engagements toward continuance intention through user-platform interactions are unexplored. This study investigated a nuanced understanding of how stimuli cues in augmented reality affect sense of immersion and sense of presence, followed by an Interaction-Engagement-Intention (I-E-I) model. A quantitative method was used to validate the proposed model. Based on an online survey with 886 responses, product fit, network quality, and Artificial Intelligence-driven Recommendation (AIR) influences were assessed for cognitive engagements. This study examined the importance of engaging satisfaction and trust as emotional engagements, influencing users’ continuance intention. The findings showed that sense of presence has a more significant influence on building trust and satisfaction. Also, trust has a more significant impact on the continuance intention to use AR mobile platforms. This study also explored the positive effects of user generation on continuance intention. This could enhance the capabilities of information system designers, researchers, marketing professionals, and solution providers to attain sustainable user retention.

The Impact of Social Media on the Perception and Purchase of Luxury Brands

The rise of social media has significantly transformed the luxury marketing landscape, presenting opportunities and challenges for luxury brands striving to balance accessibility and exclusivity. This study examines the impact of social media on consumer perception and purchasing behavior in the luxury segment. It explores how platforms like Instagram, TikTok, and Pinterest have redefined brand visibility, consumer engagement, and aspirational value. Through a mixed-methods approach involving surveys of luxury consumers and interviews with industry professionals, this research identifies key factors influencing perception, such as visual storytelling, influencer collaborations, and user-generated content (UGC). The findings reveal that while social media enhances brand awareness and purchase intent, it also poses risks of diluting exclusivity if not managed carefully. This study underscores the need for luxury brands to adopt platform-specific strategies, focusing on high-quality content and authentic partnerships. It highlights the importance of preserving the aspirational appeal central to luxury branding while leveraging digital channels to connect with modern consumers. These insights offer actionable recommendations for luxury brands to optimize their social media presence without compromising their premium identity.

Influence of Brand Generated Content’s Credibility on Customer Behavior Response Through Positive User Generated Content

This paper investigates the mixed influence of brand-generated and credible usergenerated content on customer behaviour response. The research involved surveying 400 people buying online, aged 18 years and over, in the Pathum Thani province, Thailand. Primary demographic data were collected between October and December 2022 and analysed employing descriptive statistics and structural equation modelling. The result of study indicated that the credibility business generated content has no significant influences on consumer behaviour response. The research also revealed that the credibility of brand generated content has significant influences on customer behavior response through positive user generated content. Consequently, businesses must prioritize the quality of their content and consider integrating user generated content into their marketing strategy for ––customer engagement effectively.

Incorporating Digital Media Platforms to Enhance Sustainability Insights in the UI GreenMetric World University Rankings Network

Conventional ways of delivering sustainability content often fail to capture the breadth and dynamism of university challenges. To overcome the issue, UI GreenMetric has proposed a new way of delivering content by using digital media. This study investigates the integration of digital mediaincluding Instagram, YouTube, Facebook, and Website to augment sustainability insights within the UI GreenMetric World University Rankings Network. This study analyzes the results, effects, and further implications of UI GreenMetric’s practices in incorporating user-generated content from those digital media platforms into the sustainability assessment framework to leverage the ubiquity and the richness of the content. The analysis is conducted for various activities, such as podcast/live discussions, event streaming, posts and videos related to sustainability initiatives. The findings show that integrating digital media has significantly boosted sustainability outreach within the UI GreenMetric network. UI GreenMetric not only drives the transformation of individuals, communities, and universities toward sustainability but also extends its impact through dozens of online events, such as webinars, workshops, courses, live discussions, and podcasts throughout the year. These efforts have successfully reached a wider audience, leading to meaningful behavioral changes as participants engage in campaigns and actively contribute to rankings and events.

Review on Application of Chi-square Statistic in Text Classification in Recent Five Years

Review on Application of Chi-square Statistic in Text Classification in Recent Five Years

Harnessing prompt-based large language models for disaster monitoring and automated reporting from social media feedback

In recent years, social media has emerged as one of the main platforms for real-time reporting of issues during disasters and catastrophic events. While great strides have been made in collecting such information, there remains an urgent need to improve user reports’ automation, aggregation, and organization to streamline various tasks, including rescue operations, resource allocation, and communication with the press. This paper introduces an innovative methodology that leverages the power of prompt-based Large Language Models (LLMs) to strengthen disaster response and management. By analyzing large volumes of user-generated content, our methodology identifies issues reported by citizens who have experienced a disastrous event, such as damaged buildings, broken gas pipelines, and flooding. It also localizes all posts containing references to geographic information in the text, allowing for aggregation of posts that occurred nearby. By leveraging these localized citizen-reported issues, the methodology generates insightful reports full of essential information for emergency services, news agencies, and other interested parties. Extensive experimentation on large datasets validates the accuracy and efficiency of our methodology in classifying posts, detecting sub-events, and producing real-time reports. These findings highlight the practical value of prompt-based LLMs in disaster response, emphasizing their flexibility and adaptability in delivering timely insights that support more effective interventions.

Borders of belonging: how Chinese nationalism constructs exclusion in the age of populism

This paper investigates how state-led and popular nationalism in China construct borders as tools of exclusion, reinforcing national identity amidst global populist movements. Using the Belt and Road Initiative (BRI) as a case study, the analysis examines Global Times articles and corresponding user-generated content to reveal how geopolitical, ideological, and emotional borders are created and maintained through nationalist discourse. State-led nationalism emphasizes cooperation and diplomacy, framing borders to position China as a global leader promoting shared prosperity. In contrast, popular nationalism—expressed through user-generated comments—manifests in a confrontational, exclusionary discourse that delineates China from external adversaries, particularly Western powers. Through a mixed-methods approach—combining word frequency, sentiment, and emotional categorization using the NRC Emotion Lexicon—this study uncovers key differences between the two forms of nationalism. State narratives construct inclusive borders that foster international engagement, aligning with China’s diplomatic ambitions. Meanwhile, popular nationalism reflects heightened emotional intensity, especially through expressions of fear, anger, and opposition, creating rigid borders that emphasize ideological conflict and national pride. The research contributes to the literature on populism and border studies by demonstrating how Chinese nationalism functions as both a state strategy and a grassroots expression, delineating “the people” from “the other.” It highlights the critical role of media—both state-controlled outlets and user-generated platforms—in constructing and reinforcing these boundaries. As populism continues to shape political discourse globally, the study offers valuable insights into how nationalism in non-Western contexts mirrors broader populist strategies of identity formation through the construction of symbolic and emotional borders.

Social Media Misinformaton

Social media misinformation refers to false or misleading information spread across social networks, impacting public opinion and behavior. With the vast reach and rapid dissemination capabilities of social media platforms, misinformation can quickly go viral, causing significant societal harm. Factors such as user-generated content, lack of fact-checking, and engagement-driven algorithms contribute to the spread. This research paper explores how social media misinformation occurs and discusses potential solutions, including technological interventions, media literacy, and regulatory measures to protect the integrity of information.

Multidimensional User Experience Analysis of Chinese Battery Electric Vehicles’ Competition: An Integrated Association Mining Framework

This study introduces an integrative framework for association mining within the Chinese battery electric vehicle market, aiming to reveal key user experience (UX) factors and their interrelationships through multidimensional analysis. Utilizing latent Dirichlet allocation (LDA), the study discerned primary themes from user-generated content (UGC). The entropy weight method categorized level 2 factors, while domain-adaptive sentiment analysis quantified emotional responses to BEV user experience dimensions, highlighting significant sentiment disparities among competitors. Co-occurrence network analysis deepened insights into the emotional fabric of UX by exploring tertiary factor associations. Theoretically, this study advances a novel framework informed by Norman’s UX theory, integrating analytical techniques to capture the complexity of UX. Practically, it delivers strategic guidance for BEV manufacturers by analyzing emotional polarities and attribute associations, guiding product innovation and responding to market dynamics. The empirical evidence corroborates the framework’s efficacy in revealing the emotional associations within BEVUX factors, offering valuable implications for both theoretical development and practical application.

Online Depression Communities as a Complementary Approach to Improving the Attitudes of Patients With Depression Toward Medication Adherence: Cross-Sectional Survey Study.

Lack of adherence to prescribed medication is common among patients with depression in China, posing serious challenges to the health care system. Online health communities have been found to be effective in enhancing patient compliance. However, empirical evidence supporting this effect in the context of depression treatment is absent, and the influence of online health community content on patients' attitudes toward medication adherence is also underexplored. This study aims to explore whether online depression communities (ODCs) can help ameliorate the problem of poor medication taking among patients with depression. Drawing on the stimulus-organism-response and feelings-as-information theories, we established a research model to examine the influence of useful institution-generated content (IGC) and positive user-generated content (UGC) on attitudes toward medication adherence when combined with the mediating role of perceived social support, perceived value of antidepressants, and the moderating role of hopelessness. A cross-sectional questionnaire survey method was used in this research. Participants were recruited from various Chinese ODCs, generating data for a main study and 2 robustness checks. Hierarchical multiple regression analyses and bootstrapping analyses were adopted as the primary methods to test the hypotheses. We received 1515 valid responses in total, contributing to 5 different datasets: model IGC (n=353, 23.3%), model UGC (n=358, 23.63%), model IGC+UGC (n=270, 17.82%), model IGC-B (n=266, 17.56%), and model UGC-B (n=268, 17.69%). Models IGC and UGC were used for the main study. Model IGC+UGC was used for robustness check A. Models IGC-B and UGC-B were used for robustness check B. Useful IGC and positive UGC were proven to have positive impact on the attitudes of patients with depression toward medication adherence through the mediations of perceived social support and perceived value of antidepressants. The findings corroborated the role of hopelessness in weakening or even negating the positive effects of ODC content on the attitudes of patients with depression toward medication adherence. This study provides the first empirical evidence demonstrating the relationship between ODC content and attitudes toward medication adherence, through which we offer a novel solution to the problem of poor medication adherence among patients with depression in China. Our findings also provide suggestions about how to optimize this new approach-health care practitioners should generate online content that precisely matches the informational needs of patients with depression, and ODC service providers should endeavor to regulate the community atmosphere. Nonetheless, we warn that ODC interventions cannot be used as the only approach to addressing the problem of poor medication taking among patients with severe depressive symptoms.

A Fuzzy AHP and PCA Approach to the Role of Media in Improving Education and the Labor Market in the 21st Century

In a hyperproductive interactive environment, where speed and cost-effectiveness often overshadow accuracy, the media’s role is increasingly shifting towards an educational function, beyond its traditional informative and entertaining roles. This shift, particularly through the promotion of science and education, aims to bridge the gap between educational institutions and the labor market. In this context, the importance of 21st-century competencies—encompassing a broad range of knowledge and skills—becomes increasingly clear. Educational institutions are now expected to equip students with relevant, universally applicable, and market-competitive competencies. This paper proposes using a combination of principal component analysis (PCA) and fuzzy analytic hierarchy process (FAHP) to rank 21st-century competencies developed throughout the educational process to improve the system. The highest-ranked competency identified is the ability to manage information—specifically, gathering and analyzing information from diverse sources. It has been shown that respondents who developed “soft skills” and media literacy during their studies are better able to critically assess content on social networks and distinguish between credible and false information. The significance of this work lies in its focus on the damaged credibility of online media caused by user-generated content and the rapid spread of unverified and fake news. Denying such discourse or erasing digital traces is therefore futile. Developing a critical approach to information is essential for consistently identifying fake news, doctored images, and recordings taken out of context, as well as preventing their spread.