Search Results (7,023)

Weight stigma remains a pervasive issue in contemporary society, impacting individuals’ psychological well-being, social inclusion, and access to opportunities. This study explored the lived experiences of overweight women, focusing on body image, stigma, and engagement with dominant health and beauty norms. Using a qualitative, phenomenological approach, online in-depth interviews were conducted with 14 women aged 25 to 51, primarily residing in southern and eastern Europe (Greece, Cyprus, Albania, Romania, and Bulgaria), with three participants from the United Kingdom. Thematic analysis revealed four key themes: workplace discrimination, pressures during pregnancy and the postpartum period, ambivalence toward body positivity movements, and the emotional toll of stigma, including extreme coping strategies. Participants described being marginalized professionally, scrutinized publicly and within families, and caught between ideals of inclusivity and persistent societal rejection. The findings emphasize the psychological burden of weight-based discrimination and the superficial nature of many body acceptance campaigns. This study calls for structural changes in healthcare, media, and employment practices to support body diversity and dismantle entrenched biases. By centering the voices of overweight women, the research contributes to broader discussions on embodiment, social justice, and intersectionality within the field of body image scholarship. Full article

The rapid adoption of artificial intelligence (AI) within social media platforms has fundamentally transformed the way Generation Z interacts with and navigates the digital landscape. While AI-driven algorithms enhance user experience through content personalization, they can also reinforce biases that affect the mental health and overall well-being of young individuals. This review delves into the intersections of AI bias, social medial engagement, and youth mental health, with a particular focus on how algorithmic decision-making influences exposure to harmful content, intensifies social comparison and spreads digital misinformation. By addressing these aspects, this article highlights both the risks and opportunities presented by AI-powered social media. It also advocates for evidence-based strategies to mitigate the harms associated with algorithmic bias, urging collaboration among AI developers, mental health experts, policymakers and educators at personal, community (school), and national and international levels to cultivate a safer, more supportive digital ecosystem for future generations. Full article

The relationship between reading exposure and social attitudes across demographic groups remains a pivotal yet underexplored topic in computational social science. This study adopts a machine learning framework to examine the symmetry of reading’s influence on social attitude formation. Models including Random Forest, XGBoost, LightGBM, and linear regression were employed on data from the 2021 Chinese General Social Survey (CGSS). The results show that reading volume is a key predictor of social attitudes. Moreover, a SHAP-based subgroup analysis revealed that the impact of reading exposure remained stable across gender groups, indicating a symmetric pattern of cognitive influence. This study proposes a methodological pipeline for assessing the symmetry of feature importance in social data, offering actionable insights for researchers and policymakers into the equitable role of media consumption in shaping social cognition. Full article

Background: Oral health misinformation has increasingly proliferated across social media platforms in China, prompting rising concerns about the accuracy of health-related content. Fact-checking intent has been identified as a key strategy for mitigating the spread of such misinformation. However, empirical research on the psychological factors shaping engagement in fact-checking behaviors remains limited. Objectives: This study aims to examine the association between misinformation recognition and fact-checking intent among Chinese young adults (aged 18–36). Methods: Guided by status quo bias theory, this study integrates psychological constructs into its theoretical framework. A stimulus-based online survey was conducted, yielding 452 valid responses. Direct, mediated, and serial mediation hypotheses were tested using SPSS 26.0 and Jamovi 2.6.24. Results: The findings indicate a significant positive relationship between misinformation recognition and fact-checking intent. A parallel mediation model involving need for cognition and perceived seriousness was supported, clarifying the psychological mechanisms underlying this relationship. Conclusions: This study contributes valuable empirical evidence to the understanding of fact-checking intent among Chinese young adults in the context of oral health misinformation. The findings offer practical implications for developing targeted interventions to increase misinformation awareness and promote active engagement in fact-checking behaviors. Full article

Non-consensual intimate media sharing (NCIMS)—defined as the non-consensual sharing of sexually explicit images or videos—has notably increased in recent years, despite legislative actions to tackle this. This study aimed to investigate whether the Dark Triad traits of narcissism, Machiavellianism, and psychopathy—as well as sex and social desirability—predicted NCIMS proclivity, enjoyment, and approval in UK university students. A total of 653 participants were recruited through Prolific, the University of Birmingham survey circle, and social media. All participants completed various measures to assess self-reported levels of Dark Triad traits, social desirability, and NCIMS proclivity, enjoyment, and approval. The results showed that the models for each multiple linear regression (NCIMS proclivity, enjoyment, and approval) were statistically significant, though only certain variables were independent predictors for each regression. For proclivity, only psychopathy independently added to the prediction. For enjoyment, significant predictors were sex, Machiavellianism, and psychopathy. For approval, only Machiavellianism added statistically to the prediction. This research adds to the growing literature base around NCIMS, specifically within university students in the UK, and provides strong evidence for the development and implementation of interventions designed to address the likelihood of individuals perpetrating NCIMS. Full article

Although impulsive and hedonic purchasing behaviors may seem to contradict sustainability principles, there are unexplored opportunities through which social media platforms and influencers can redirect these impulses toward sustainable actions. Young consumers, increasingly concerned about the ecological impact of their choices, can be encouraged to adopt responsible and sustainable buying behaviors when these are promoted attractively, enjoyably, and emotionally satisfyingly through social media. This research investigates how social media communication influences hedonic and impulsive purchasing behavior in the Romanian clothing market. In the context where social media is one of the main sources of information and influence for consumers, the research analyzes several determining factors of the purchase decision. Price reductions and the use of credit cards are highlighted as elements that facilitate spontaneous and hedonic targeted purchases, while the attractiveness of clothing items and the need felt play an important role in terms of the desire to buy. In addition, sources of information (such as reviews) have a major impact on consumers’ perceptions and their purchase intentions. Additionally, the study investigates factors such as overall shopping experience and its influence on consumer loyalty. It is approached from two perspectives: attitudinal loyalty, reflected in the preference for brands promoted on social media, and behavioral loyalty, expressed through repeat purchases. The results show that social media acts as an accelerator for hedonic and impulsive buying behaviors, prompting consumers to react quickly to stimuli such as discount campaigns or personalized recommendations. The conclusions highlight the importance of adopting digital marketing strategies that capitalize on the consumers emotional need while also strengthening brand loyalty. These perspectives can guide companies in the clothing industry to adapt their promotion methods to the specifics of the Romanian market and the consumer behavior. Full article

Energy-efficient consumption has become a strategic priority to mitigate global climate change and enhance national energy security. While social media has reshaped online consumption behavior, the mechanisms through which these digital platforms influence energy-efficient purchasing remain underexplored. This study extends the Theory of Planned Behavior (TPB) by integrating price perception variables and applies multi-group structural equation modeling to examine how social media shapes Chinese consumers’ intentions to purchase energy-efficient air conditioning. The results show that (1) social media exposure strengthens energy-efficient purchasing intentions indirectly via behavioral attitude, subjective norm, and perceived behavioral control; (2) price perception is negatively associated with purchase intention; and (3) these effects vary by age cohort, gender, and income—Generation Z and female consumers are more susceptible to social media influence, while low-income groups exhibit heightened price sensitivity. These findings advance TPB theory and offer guidance for digital platform policies aimed at promoting energy-efficient consumption. Full article

In an age of AI-generated content and deepfakes, fake news and disinformation are increasingly spread using manipulated or fabricated images. To address this challenge, we introduce Post-Quantum VerITAS, a cryptographic framework for verifying the authenticity and history of digital images—even in a future where quantum computers threaten classical encryption. Our system supports common image edits, like cropping or resizing, while proving that the image is derived from a legitimate, signed source. Using quantum-resistant tools, like lattice-based hashing, modified Poseidon functions, and zk-SNARK proofs, we ensure fast, privacy-preserving verification without relying on trusted third parties. Post-Quantum VerITAS offers a scalable, post-quantum-ready solution for image integrity, with direct applications in journalism, social media, and secure digital communication. Full article

This study aims to analyze how women’s empowerment in sustainable entrepreneurial leadership transforms social, environmental, and economic challenges into growth opportunities within B Corps-certified companies in Latin America. A total of 9536 companies were identified in the global B Corps registry, of which more than 1000 belonged to the Latin America and Caribbean directory. Particular attention was given to 130 companies located in Chile, with a presence in countries such as Peru, Mexico, Colombia, Brazil, Uruguay, Paraguay, and Argentina. The methodology adopted a post-positivist approach with a hermeneutic analysis rooted in organizational studies, using the Straussian grounded theory method. Testimonies from 16 female entrepreneurs were explored, identified through the B Corps directory and the main social media networks of the B system in Latin America. This approach enabled a deeper understanding of the human complexity surrounding sustainability, equity, and gender equality. Findings show that female leadership promotes inclusive and strategic actions that challenge traditional structures and generate positive impacts. Five categories emerged: female entrepreneurial leadership; gender equality stakeholders; social contribution; women’s economic development; and sustainable decision-making. These converge in the central category of female empowerment in sustainable entrepreneurial leadership. In conclusion, the emerging theory expands the understanding of women-led leadership in Latin America, revealing socially responsible business models that promote sustainability, inclusion, and challenge dominant power structures in the business world. Full article

Due to the rapid development of China’s economy, the current situation of fishing villages in the southeastern coastal areas is spatial disorder caused by changes in population composition and industrial transformation. This study analyses the differences between the clan structure and the multi-stakeholder engagement model in traditional fishing villages. The main aim is to illustrate contemporary issues that fishing villages’ spaces need to deal with in governance and decision making. With the development of information technology, social media has become an important platform through which stakeholders can communicate and make decisions. The aims of this paper were as follows: (1) Identify the stakeholders involved in the governance of fishing villages; (2) explore how stakeholders participate in the planning and governance of fishing villages through social media; (3) examine the mechanisms of social media and its impact on the spatial planning of fishing villages. Through qualitative research methods such as field surveys and in-depth interviews, the following results were obtained: (1) Social media subverts the traditional fishing village governance model, and the scope of the governance subject is expanded; (2) spatial changes in fishing villages are affected by the joint influence of people, the environment, and the economy, and a social network acts as an intermediary to compensate for the deficiencies that existed in previous fishing village governance processes. Full article

The synthesis of large language models (LLMs) and recommender systems has been a game-changer in tailored content onslaught with applications ranging from e-commerce, social media, and education to health care. This survey covers the usage of LLMs for content recommendations (LLM4Rec). LLM4Rec has opened up a whole set of challenges in terms of scale, real-time processing, and data privacy, all of which we touch upon along with potential future directions for research in areas such as multimodal recommendations and reinforcement learning for long-term engagement. This survey combines existing developments and outlines possible future developments, thus becoming a point of reference for other researchers and practitioners in developing the future of LLM-based recommendation systems. Full article

This article explores the challenges surrounding the Scottish media graduate landscape after the COVID-19 pandemic. Contributing factors that impact Scotland-based students and educators include a shift in the jobs market, altering pedagogies during and post-pandemic, and social drivers including fewer students choosing media pathways of study due to the cost-of-living crisis. This study draws on insights from 40 students at five Scottish universities, all of whom graduated in the summer of 2023. The research presents a window into the mindset and expectations of this post-pandemic graduating class while drawing on current and relevant literature. In addition, the paper includes reaction from industry and academic experts in Scotland and questions what can be done to address trends surrounding the stability and sustainability of journalism education. The experts include senior broadcasters, an established media educator who has worked across further education and higher education in Scotland while also being a national news editor, and one of Scotland’s most experienced journalism educators who is the chair of the World Journalism Education Council. This work is predominantly qualitative, drawing on a mixed research approach of expert interviewing and surveys while providing recommendations for journalism educators. Full article

In modern communication technology, short videos are increasingly used on social media platforms. The advancement of video codecs is pivotal in communication. In this study, we developed a new scheme to encode the residue of intraframes. For the H.264 baseline profile, we used context-based arithmetic variable-length coding (CAVLC) to encode the residue of integer transforms in a block-wise manner. In the developed method, the DC and AC coefficients are separated. In addition, context assignment, adaptive scanning, range increment, and mutual learning are adopted in a mixture of fixed-length and variable-length schemes, and block-wise compressions of the frequency table are applied to obtain improved compression rates. Compressing the frequency prevents CAVLC from being hindered by horizontally/vertically dominated blocks. The developed method outperforms CAVLC, with average reductions of 7.81, 8.58, and 7.88% in quarter common intermediate format (QCIF), common intermediate format (CIF), and full high-definition (FHD) inputs. Full article

Personalized travel experiences have become a growing priority for tourists, while the built environment increasingly shapes tourists’ behavior. However, limited research has integrated behavioral drivers with algorithmic travel route optimization, particularly in the context of Generation Z tourists. To address this gap, this study proposes a hybrid framework that combines behavioral modeling with enhanced algorithmic techniques to generate customized travel itineraries for Generation Z. A behavioral influencing factors model is first constructed based on the Theory of Planned Behavior (TPB) and Social Influence Theory (SIT), identifying media influence (MI), subjective norms (SNs), and perceived built environment (PBE) as potential determinants of travel behavioral intention (BI). A Structural Equation Model (SEM) is then applied to empirically validate the hypothesized relationships. Results reveal that all three factors have a significant and positive impact on BI (p < 0.05). Building on this behavioral mechanism, an interest-based Ant Colony Optimization (ACO) algorithm is implemented by incorporating point-of-interest (POI) preferences and distance matrices to improve personalized route generation. Comparative analysis using social media keyword data demonstrates that the proposed method outperforms conventional travel route planning approaches in terms of route relevance and overall path satisfaction. This study offers a novel integration of psychological theory and computational optimization, providing both theoretical insights and practical implications for urban tourism planning and the development of smart tourism services. Full article

Social media sites, particularly Instagram, have recently developed effective instruments for influencing customer behavior, particularly regarding eating experiences and cuisine. This study examines the influence of posting food-related content on Instagram on customers’ intention to visit casual dining restaurants in Saudi Arabia. This study also examined the mediating role of credibility in shaping this intention. A quantitative approach was used through online surveys gathered from 685 Saudi Arabian customers. The major findings of this study revealed that foodstagramming attributes such aesthetic appeal (AA) and post popularity (PP) positively influence customers’ visit intention (VI) in the context of casual dining restaurants in Saudi Arabia. Furthermore, the content credibility (CC) of foodstagramming positively influences customers’ VI. In addition, the CC of foodstagramming partially mediates the relationship between AA, PP, and customers’ VI. Theoretical contributions and practical implications are also provided. Full article