Search Results (140)

Background/Objectives: For patients with Ulcerative Colitis (UC) requiring surgical treatment, post-operative dietary management can pose significant challenges. TikTok is emerging as a popular social media platform for dissemination of health and nutrition information. The aim of this study is to analyse patient-generated content on TikTok regarding dietary management post-UC surgery, in order to identify recurring themes and highlight patient priorities. Methods: Relevant TikTok videos were identified through a systematic search. Search terms were developed by combining ‘diet UC’ or ‘nutrition UC’ with common UC surgical procedures. From each search term, the first 10 videos were screened. If a search produced fewer than 10 results, all identified videos were retrieved. Inclusion criteria were videos in English, and a strong indication that the content creator was diagnosed with UC and had undergone relevant surgery, and was providing nutrition recommendations. Thematic analysis of video transcripts was conducted using Braun and Clarke’s framework to identify common themes. Results: A total of 89 videos, created between 2021 and 2024, were found on the initial search, of which 12 duplicates were removed, and 77 videos were screened. Sixteen English language videos met the inclusion criteria and were analysed. Thematic analysis identified three overarching themes: (1) adaptive dietary progression in the post-surgical period, where patients described a phased approach to reintroducing foods post-surgery; (2) personalisation of diet, highlighting individualised strategies for symptom and hydration management; and (3) Emotional and social impact of dietary restrictions and modifications, including fear of food and social isolation. Conclusions: This thematic analysis offers an insight into how patients navigate the complex management of diet following UC surgery. It is important for clinicians to discuss the dietary information and online content patients are exposed to in relation to their condition. Additionally, clinical practice should evolve to embrace patient-centred, multidisciplinary approaches that validate lived experience, ensure consistent dietary guidance, and address the psychological burden of dietary restriction. Full article

Amid the prevailing trend of “pan-entertainment” in cyberspace, adults increasingly interpret children’s lives through utilitarian, adult-centric, and entertainment-focused perspectives, leading to the alienation of children’s online images. This study examines child influencer accounts on Douyin—typically managed by parents—and conducts content and discourse analysis on them. Drawing on critical theories by Douglas Kellner, we employed Scrapy and NVivo to analyze 30 popular children’s videos and 15,000 user comments posted beneath them. The analysis identifies five key characteristics in the construction of such images: spectacular visual mechanisms, younger-age production trends, covert commercial penetration, homogenized spectacle types, and adult-centric implicit influence. The study underscores the urgency of strengthening protective mechanisms to counteract platform capitalism’s intrusion into childhood and to uphold children’s digital privacy and agency. Full article

Streaming services have gained popularity due to their vast content library and convenience. To ensure continued patronage, service quality measurement is important. In this study, we ranked and determined how to maintain the competitiveness of streaming services using the analytic hierarchy process. Using focus group discussions and questionnaire administration, Netflix was found to have the highest perceived service quality, as measured by the consistency ratio and rating scales. Content library, quality of experience, and system availability were the top three service quality dimensions, while the top three sub-dimensions were quality of content, frequency of video freezing, and picture quality. These results allow companies to adjust their service strategies to suit the Philippine market. Full article

(1) Background: C-section-related health information is increasingly disseminated through short video platforms such as YouTube and Bilibili, yet the quality and audience engagement of this content remain insufficiently understood. (2) Methods: A cross-sectional study analyzed the top 90 C-section-related videos from each platform (180 total). C-section video characteristics and engagement metrics were collected. Information quality and reliability were assessed using GQS, DISCERN, and JAMA benchmarks. Associations between quality scores and engagement indicators were examined using Spearman’s correlation analysis. (3) Results: YouTube videos were longer and more frequently produced by medical professionals. Although GQS scores were comparable, YouTube content demonstrated higher reliability, with significantly higher DISCERN and JAMA scores (p < 0.001). C-section engagement metrics were strongly intercorrelated but showed weak associations with objective quality measures. (4) Conclusions: Significant cross-platform disparities exist in C-section information quality, with a pronounced dissociation between clinical reliability and audience engagement. This “quality-popularity paradox” underscores a critical mismatch between evidence-based rigor and digital dissemination. Our findings necessitate multi-sectoral interventions, including standardized creator credentialing and algorithm recalibration, to align high-quality obstetric knowledge with public attention. Full article

With artificial intelligence (AI) rapidly increasing in popularity and presence in everyday life, new applications utilizing AI are being explored across virtually all domains, from banking and healthcare to cybersecurity to generative AI for images, voice, and video content creation. With that trend comes an inherent need for increased AI capabilities. One cornerstone of AI applications is the ability of generative AI to consume documents and utilize their content to answer questions, generate new content, correlate it with other data sources, and more. No longer constrained to text alone, we now leverage multimodal AI models to help us understand visual elements within documents, such as images, tables, figures, and charts. Within this realm, capabilities have expanded exponentially from traditional Optical Character Recognition (OCR) approaches towards increasingly utilizing complex AI models for visual content analysis and understanding. Modern approaches, especially those leveraging AI, are now focusing on interpreting more complex diagrams such as flowcharts, block diagrams, Unified Modeling Language (UML) diagrams, electrical schematics, and timing diagrams. These diagram types combine text, symbols, and structured layout, making them challenging to parse and comprehend using conventional techniques. This paper presents a historical analysis and comprehensive survey of scientific literature exploring this domain of visual understanding of complex technical illustrations and diagrams. We explore the use of deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer-based architectures. These models, along with OCR, enable the extraction of both textual and structural information from visually complex sources. Despite these advancements, numerous challenges remain, however. These range from hallucinations, where the content extraction system produces outputs not grounded in the source image, which leads to misinterpretations, to a lack of contextual understanding of diagrammatic elements, such as arrows, grouping, and spatial hierarchy. This survey focuses on five key diagram types: flowcharts, block diagrams, UML diagrams, electrical schematics, and timing diagrams. It evaluates the effectiveness, limitations, and practical solutions—both traditional and AI-driven—that aim to enable the extraction of accurate and meaningful information from complex diagrams in a way that is trustworthy and suitable for real-world, high-accuracy AI applications. This survey reveals that virtually all approaches struggle with accurately extracting technical diagram information. It also illustrates a path forward. Pursuing research to further improve their accuracy is crucial for supporting and enabling various applications, including complex document question answering and Retrieval Augmented Generation (RAG), document-driven AI agents, accessibility applications, and automation. Full article

This entry, which identifies nine paradoxes particular to popular culture in a digital society, begins by distinguishing art and culture, since scholars have historically relied on these terms to differentiate popular culture, mass culture, and mass art. Digital societies, which exist both online and offline, are awash in digital products such as LED signs, digital imagery, video games, film, podcasts, and social media. In a digital society, popular culture is effectively “mass art,” which exhibits five properties: (1) digital media’s low-cost products and low-skill tools are (2) created and distributed to appeal to as broad a cultural sector as possible (qualitative) and thus aim to (3) attract consumers (quantitative) who capably enjoy and deploy cultural content both (4) offline and online, yet “popularity” ultimately depends on (5) efforts to maximize unity and minimize fragmentation. Except for localized events, popular culture has largely disappeared, while mass art will likely flourish until human beings clamor once again for firsthand experiences or go extinct. The next frontier will be finding ways to prevent artificial intelligence from producing cultural products, not because they will be terrible, undesirable, or fake, but because the culture-making process itself engenders human wellbeing. Full article

Background: Mukbang, an online trend featuring individuals eating large amounts of food while interacting with viewers, has become increasingly popular worldwide, including in Saudi Arabia. This study explored how often Saudi adults watch mukbang videos and whether viewing frequency is related to emotional, external, and restrained eating behaviors. Methods: An online survey was completed by 160 participants, of whom 70 had watched mukbang videos in the past 30 days and were included in the analysis. Results: Viewing frequency was not significantly associated with any eating behavior type. Education level showed a significant relationship with viewing habits, with participants who had higher educational attainment reporting less frequent viewing; however, this association should be interpreted cautiously, as media awareness was not directly measured. Conclusions: Overall, the findings provide preliminary insight into how individual characteristics may shape engagement with mukbang content and highlight the need for further research that examines additional psychological and cultural factors. Full article

Background: YouTube has become one of the most widely used platforms for medical education and patient information. However, the accuracy and reliability of such unregulated content remain highly variable and sometimes misleading. This study aimed to evaluate the quality, reliability, and educational value of YouTube videos related to poisonings, insect bites, and envenomations using validated scoring systems. Methods: A cross-sectional analysis of YouTube videos was conducted using the search terms “approach to insect bites and stings,” “approach to poisonings,” “approach to scorpion envenomation,” “approach to snake envenomation,” and “approach to mushroom poisoning.” Searches were performed in incognito mode on August 1, 2025. Only English-language videos shorter than one hour were included. Video quality and reliability were evaluated using the Global Quality Score (GQS), modified DISCERN (mDISCERN), and Journal of the American Medical Association (JAMA) benchmarks, while viewer engagement was measured using the Video Power Index (VPI). Results: A total of 279 videos were analyzed. The mean ± SD scores were as follows: GQS, 3.53 ± 1.09; mDISCERN, 3.53 ± 1.08; and JAMA, 2.63 ± 0.96. Based on the GQS, 59.5% of the videos were high quality, 20.8% moderate quality, and 19.7% low quality; thus, approximately 40% of the evaluated videos (low- and moderate-quality categories combined) did not meet optimal quality standards. Videos on snake envenomation and general poisoning had significantly higher quality and reliability scores (p < 0.001). Educational, physician-sourced, and physician-presented videos achieved higher GQS, JAMA, and mDISCERN values (p < 0.001 for all). However, no significant differences were found in the VPI, indicating that popularity metrics did not correlate with content quality. Conclusions: YouTube provides wide access to poisoning-related educational materials, but content quality varies considerably, and a substantial proportion of videos fall below acceptable quality thresholds. Videos produced or presented by physicians are more reliable, whereas popularity is not a valid indicator of scientific accuracy. Active involvement of healthcare professionals and academic institutions, together with platform-level quality verification and visibility strategies, is essential to improve the credibility and impact of online health information. Full article

This study investigates the key attributes that characterize popular content produced by leading Generation Z TikTok influencers in Israel. The research seeks to identify the content elements that drive user engagement and contribute to the influencers’ widespread appeal. A content analysis was conducted on a sample of 400 videos created by 18 prominent TikTok personalities, enabling a systematic examination of recurring themes and stylistic features. Findings reveal that highly popular posts predominantly emphasize entertainment while avoiding violent content. However, they also tend to lack substantial informational value. Notably, content produced by female influencers features more sexualized elements compared to that of their male counterparts. Furthermore, collaborative videos involving multiple influencers appear to be more successful in garnering audience attention. The study’s practical implications underscore a strategic shift: Generation Z shows a marked preference for TikTok influencers over traditional celebrities. This trend presents opportunities for marketing and public awareness campaigns seeking to engage younger demographics effectively. On a broader social level, the findings suggest that despite TikTok’s perceived novelty and authenticity, its most popular content often mirrors the norms and conventions of mainstream media. Thus, TikTok may reinforce rather than disrupt dominant cultural narratives. Full article

Auditory cues are an important, though often overlooked, component of the multisensory experience of food consumption, directly influencing consumer perception and enjoyment. This study investigates how prior food-related experiences affect the perception and preference for food sounds, with a focus on artisanal bread, a popular staple food with distinctive auditory characteristics. A group of 113 participants was recruited and assigned to one of the two groups: 53 attended a bread-making workshop to establish enriched audiovisual associations, while 60 watched bread-making videos online, which represented a comparatively limited form of sensory engagement. Participants rated their perceived comfort levels for three distinct bread-related food sounds before and after the intervention. Sound recognition performance was also assessed as well as the appeal of the sounds. The results revealed that those who attended the workshop evaluated the close-up food sounds significantly more positively than those who watched the videos instead. Furthermore, regression analyses revealed that greater visual involvement during the workshop/watching videos was associated with increased comfort and decreased annoyance for the close-up bread sounds. These findings underscore the importance of multisensory integration experiences, particularly audiovisual integration, in shaping consumer responses and preferences for food sounds. To make sure that consumers feel comfortable and even hungry when they listen to food-related audial content, it is beneficial to incorporate familiar food sounds and, where possible, reinforce these with visual or experiential cues. Content that leverages multisensory associations and aligns with listeners’ prior experiences is likely to be more effective in eliciting positive sensory and emotional responses. Full article

This study explores the dissemination of Cantonese Opera on Bilibili, a social media platform popular among younger audiences in China, as traditional cultural forms struggle to captivate younger generations. Platforms like Bilibili present opportunities for revitalizing interest in intangible heritage. This research aims to uncover how user engagement metrics influence the visibility and spread of Cantonese Opera content, providing insights for enhancing heritage promotion. Data were collected from 1916 Cantonese Opera videos using Python-based web scraping, focusing on eight user engagement metrics: Likes, Shares, Coins, Comments, Bullet Comments, Fans, Collects, and Plays. In addition to descriptive statistics, exploratory data analyses—including distributional assessment, correlation analysis, and K-means clustering—were conducted to examine engagement heterogeneity and interaction patterns across videos. The structural equation modeling (SEM) was employed to analyze the relationships among these metrics and their impact on content dissemination. Results show that Coins and Likes significantly predict Comments and Shares, indicating the importance of both monetary and non-monetary support in fostering interaction. The clustering results revealed three distinct video groups—high, moderate, and low engagement—demonstrating a long-tail pattern typical of social media visibility. Collects and Shares notably increase Plays counts, underscoring the role of curation and social diffusion. However, the negative impact of Coins on Plays reveals complex user motivations. These multi-level analyses provide a comprehensive understanding of engagement mechanisms and heterogeneity. They contribute to understanding the promotion of traditional cultural content through youth-oriented social media and offer practical implications for content creators and cultural institutions leveraging digital media for cultural preservation. Full article

Social media has emerged as a dominant platform for sharing human–animal interactions, creating a powerful tool for public engagement and wildlife conservation. Consequently, we sought to determine whether analyzing user preferences for animals on social networks could inform the management of effective conservation campaigns. We analyzed 5129 videos from three channels (Brave Wilderness, BBC Earth, and Nat Geo Wild) available on YouTube, which have millions of followers each. The mean number of “likes” was used as a proxy for animal species preferences. Contrary to the general expectation that humans predominantly prefer charismatic animals (e.g., terrestrial mammals), the most preferred animals on these channels were from the classes Amphibia, Arachnida, and Insecta, which significantly outperformed mammals and birds. Viewers most frequently consumed videos of stinging insects or threatening animals, and domestic animals received more likes than wild animals. Furthermore, contrary to expectations, body mass, IUCN conservation status, and daytime activity of mammals and birds did not significantly influence human preferences. Our results suggest that although viewing animal videos may have a negligible direct conservation impact, the analysis of preferences reveals that creators successfully captured human attention toward less popular animal taxa, highlighting potential indirect benefits. Future research should integrate audience enjoyment of frightening content with conservation intentions. Full article

Content Delivery Networks (CDNs) have evolved to meet surging data demands and stringent low-latency requirements driven by emerging applications like high-definition video streaming, virtual reality, and IoT. This paper proposes a hybrid CDN architecture that synergistically combines edge caching, Multi-access Edge Computing (MEC) offloading, and reinforcement learning (Q-learning) for adaptive routing. In the proposed system, popular content is cached at radio access network edges (e.g., base stations) and computation-intensive tasks are offloaded to MEC servers, while a Q-learning agent dynamically routes user requests to the optimal service node (cache, MEC server, or origin) based on the network state. The study presented detailed system design and provided comprehensive simulation-based evaluation. The results demonstrate that the proposed hybrid approach significantly improves cache hit ratios and reduces end-to-end latency compared to traditional CDNs and simpler edge architectures. The Q-learning-enabled routing adapts to changing load and content popularity, converging to efficient policies that outperform static baselines. The proposed hybrid model has been tested against variants lacking MEC, edge caching, or the RL-based controller to isolate each component’s contributions. The paper concludes with a discussion on practical considerations, limitations, and future directions for intelligent CDN networking at the edge. Full article

Objectives: Narratives related to root canal treatment on social media can be problematic. This research examines discourses relating to root canal treatment on the popular platform Instagram. Through this analysis, the way different health discourses relating to endodontics are being communicated to the public and consumers will be explored. Methods: A search was conducted on Instagram to access consumer-focused information related to root canal treatment. Posts were identified, transcribed to capture the audio component in text form, and watched cyclically, with analytical memos being kept on video content. A social semiotic analysis was conducted on posts to capture the multimodal nature of discourse on endodontics. Results: A total of 100 Instagram posts were included in this study. Two overarching themes were used to structure the analysis of posts: (1) presentation of root canal treatment and (2) presentation of expertise. The majority of posts were negative in tone towards root canal treatment. Conclusions: The variety and nature of the misinformation featured in this research present a complex professional challenge for dentistry. The majority of the posts identified and analysed featured sensationalised explanations of dental disease and treatment processes, blended with inaccuracies, many of which were produced by dentists. Conspiracy discourses relating to root canal treatment were also encountered, which questioned the integrity and intentions of the dental profession. Full article

Nowadays, virtual reality is experiencing widespread adoption, and its popularity is expected to grow in the next few decades. A relevant portion of virtual reality content is represented by 360-degree videos, which allow users to be surrounded by the video content and to explore it without limitations. However, 360-degree videos are extremely demanding in terms of storage and streaming requirements. At the same time, users are not able to enjoy the 360-degree content all at once due to the inherent limitations of the human visual system. For this reason, viewport prediction techniques have been proposed: they aim at forecasting where the user will look, thus allowing the transmission of the sole viewport content or the assignment of a different quality level for viewport and non-viewport regions. In this context, artificial intelligence plays a pivotal role in the development of high-performance viewport prediction solutions. In this work, we analyze the evolution of viewport prediction based on machine and deep learning techniques in the last decade, focusing on their classification based on the employed processing technique, as well as the input and output formats. Our review shows common gaps in the existing approaches, thus paving the way for future research. An increase in viewport prediction accuracy and reliability will foster the diffusion of virtual reality content in real-life scenarios. Full article