Search Results (144)

Short-form video platforms have become embedded in adolescents’ everyday lives, and rural left-behind children may be particularly vulnerable to problematic use in the context of prolonged parental absence. This cross-sectional study examined associations between family, peer, and school adversity and short video addiction (SVA), as well as whether these associations differed between left-behind children (LBC) and non-left-behind children (NLBC). Guided by selected components of the I-PACE model and ecological systems theory, we surveyed 1839 rural Chinese secondary school students, including 876 LBC and 963 NLBC. Bullying victimization, academic stress, parental rejection, stress, anxiety, social anxiety, online social support (OSS), and SVA were measured. Partial least squares structural equation modelling and multi-group analysis were used. LBC reported higher mean levels of bullying victimization, academic stress, stress, anxiety, social anxiety, and SVA than NLBC, although the corresponding effect sizes were small. Among LBC, significant indirect associations linked bullying victimization and academic stress with SVA through social anxiety, both independently and serially through OSS; academic stress was also indirectly associated with SVA through OSS alone. Among NLBC, significant indirect associations involving general stress and social anxiety linked adversity with SVA, whereas OSS alone was involved only in the academic stress–SVA association. No between-group path difference remained significant after Bonferroni or false discovery rate correction. The findings identify social anxiety and academic stress as relevant prevention targets but do not establish causal pathways or robust structural differences between LBC and NLBC. Full article

This study aims to identify the key destination-related factors associated with tourists’ revisit behavior in peri-urban rural areas within Chinese metropolitan regions in the context of short-video marketing, and to reveal the structural relationships and hierarchical characteristics among these factors. First, the LDA topic model was employed to conduct text mining on authentic tourist-generated comments posted on Douyin, through which the core factors related to revisit behavior were identified and conceptually standardized based on tourists’ expressions. Building on this process, 153 experts in relevant fields were invited to evaluate the direction and strength of the relationships among these factors. An integrated DEMATEL–ISM–MICMAC approach was then applied to analyze their causal attributes, hierarchical structure, and systemic roles. The results indicate that the identified factors do not operate independently but instead form a multilayered structure with clear hierarchical characteristics. Among them, rural visual imagery, escape-oriented experience, rural lifestyle experience, and rural industry integration occupy deeper structural levels and exert relatively strong structural influences on factors located at intermediate and surface levels. The findings further suggest that the sustained attractiveness of rural tourism destinations in metropolitan regions cannot rely solely on short-video exposure or isolated “internet-famous” attractions; rather, it requires coordinated alignment among digital communication content, rural industries, lifestyle experiences, and tourism supply. By integrating tourist-generated content, natural language processing, and expert-based structural assessment, this study extends research on short-video tourism marketing from a systems perspective and provides practical insights for peri-urban rural destinations in Chinese metropolitan regions seeking to optimize the structural configuration of tourism resources, products and services, and marketing communication. Full article

Care settings need short, accessible digital activities that encourage older adults to participate while generating process data during ordinary interaction. We developed a game-based platform with four activities: reflective choice, guided breathing, reminiscence, and artistic expression. Session video, interaction logs, and field notes were organized in a context-preserving multimodal framework. This exploratory seven-module field study included 12 older adults aged 65–90 years in a hospital-affiliated care setting. Ten participants completed all seven scheduled modules, and 81 of 84 planned module sessions were completed; some participants completed multiple modules on the same calendar day. Seventy-two videos were analyzable, representing 88.9% of completed module sessions (72/81). Across 251 activity selections, reminiscence was selected most often; mouse control and navigation were the main operating difficulties. Two raters independently annotated forty 10 s field-video clips. Target-face tracking was stable or basically stable in 90% of clips. Gaze-deviation detection achieved 87.5% accuracy and a macro-F1 of 0.871, while macro-expression classification achieved 67.5% accuracy and a macro-F1 of 0.610. The findings demonstrate a context-preserving field method for structured process records. The algorithms are auxiliary tools, and facial-expression outputs should not be interpreted as direct measures of emotion, cognition, or clinical status. Full article

The losses caused by frequent natural disasters are increasing day by day, and the short-video platform has become the core digital space for the public to pay attention to disasters and express their demands. In the face of massive multimodal data, how to automatically extract features and quantify their impact on public behavior is a key technical challenge facing information systems and computational social sciences. To address this issue, this study proposes an automated multimodal data mining and modeling framework that integrates YOLOv11-based computer vision with BERT-based natural language processing for disaster short-video analysis. Real-world short-video and interaction data were automatically collected using web crawling. YOLOv11 was employed to identify and quantify two types of visual information—relief information and suffering information—while BERT was used to extract a text-based rescue satisfaction index. Then, the partial least squares structural equation model was used to explore the driving mechanism of information characteristics on public engagement. It was found that the content of relief information in videos has a significant positive impact on satisfaction but a significant negative impact on engagement. The content of suffering information has a significant negative impact on satisfaction but a significant positive impact on engagement. In addition, satisfaction has a significant negative impact on engagement and plays an intermediary role between the two types of information content and engagement. By integrating YOLOv11 and BERT into a unified short-video analytics framework, this study extends automated multimodal disaster information analysis and provides practical support for optimizing emergency communication and disaster information-release strategies. Full article

Digital wellness policies in universities often rely on uniform daily screen time caps, yet platform-specific risks may shape student outcomes as strongly as total time online. This paper presents a methodological proof of concept: it demonstrates an analytical pipeline that converts multi-platform outcome data into a graduated, affordance-informed policy typology, rather than offering validated platform-risk classifications or ready-to-implement policy. Using a publicly available student dataset covering twelve social networks, we aggregate four harm-aligned outcomes—addictive use, poorer mental health, shorter sleep duration, and interpersonal conflict—to the platform level and apply hierarchical clustering to derive a four-tier risk typology. We stress that the clustering and the subsequent principal component analysis operate on only twelve platform-level observations, not on the 705 individual students. We then project the tiers onto a two-dimensional risk map and simulate three illustrative policy regimes: a uniform daily cap, a tier-calibrated cap, and an affordance-targeted short-video cap. In this illustrative dataset, the tier-calibrated cap reproduces roughly seventy percent of the harm reduction in a blanket cap while directly affecting about three-quarters of students, and the three regimes deliver near-equivalent harm reduction per percent of students affected. Because the source data show characteristics consistent with synthetic or semi-synthetic simulation and lack established provenance, all quantitative results are presented as demonstrations of the pipeline. We describe the sensitivity of the typology to clustering choices, the ethical risks of tiered classification, and the replication required before any tier could inform practice. Full article

Introduction: Fitness short videos have become an increasingly popular form of digital health communication, yet the factors influencing users’ continued usage remain insufficiently understood. This study integrates the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the Health Belief Model (HBM), and the Theory of Planned Behavior (TPB) to examine the determinants of users’ continuous intention and actual use of fitness short videos. Methods: A cross-sectional questionnaire survey was conducted using a convenience sampling approach among Chinese fitness short video users. A total of 550 valid questionnaires were collected. Structural equation modeling (SEM) and bootstrapping analysis were employed to examine the proposed research model and test the hypothesized relationships among constructs. Results: The results indicate that performance expectancy, hedonic motivation, habit, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, perceived behavioral control, and behavioral intention significantly influenced users’ continued fitness short video usage. Habit exerted significant effects on both behavioral intention and actual use behavior. In contrast, attitude, subjective norm, and self-efficacy did not show significant direct effects. Conclusions: This study extends current understanding of continuous fitness short video usage by integrating technology acceptance, health belief, and planned behavior perspectives into a unified framework. The findings provide theoretical insights into digital health behavior and offer practical implications for the design of fitness short-video platforms and digital health intervention strategies. Full article

TikTok is a short-form video-sharing platform launched in 2016 by the China-based ByteDance under the name Douyin. Following its merger with Musical.ly in 2018, it rapidly gained global popularity. The platform has influenced individuals’ digital communication habits through its short video format and user-centric content creation capabilities. TikTok’s rapid access to its young user base presents significant opportunities for organizations and brands, but also brings risks such as data privacy and content security. TikTok’s dynamic algorithm prioritizes content based on users’ interests, enabling rapid access to a wide audience. A qualitative phenomenological research design was employed. Semi-structured interviews were conducted with 15 influencers collaborating with brands on TikTok. The content was analyzed using MAXQDA Analytics Pro 24 (Release 24.1.1). TikTok provides significant advantages such as visibility, viral content, and engagement with young audiences. However, challenges include content moderation, algorithmic uncertainty, and payment and trust issues. TikTok should be considered a priority channel, especially for campaigns targeting young audiences. Influencer collaborations have a positive impact on brand awareness, consumer trust, and engagement. The platform’s user-friendly tools, trending structure, and short video format allow brands to run creative campaigns on a low budget. However, some structural challenges, such as content control and trust issues, necessitate a professional and transparent collaboration model. Full article

The global popularity of short-form video applications such as TikTok has increased rapidly. However, longitudinal evidence on how distinct usage patterns affect mental health outcomes, particularly depression, remains limited. The present study investigated whether active versus passive TikTok use differentially predicts depression through the mediating roles of autistic traits and self-esteem. A three-wave longitudinal survey was conducted in China at six-month intervals. A total of 590 university students (aged 17–24 years) completed questionnaires assessing active/passive TikTok use and depression at Time 1 (T1), autistic traits and self-esteem at Time 2 (T2), and depression again at Time 3 (T3). Mediation analyses were performed using PROCESS macro (Model 6), controlling for gender, age, daily TikTok usage time, and T1 depression. Active TikTok use indirectly predicted lower depression through increased self-esteem, but not through autistic traits. In contrast, passive TikTok use predicted higher depression via three distinct pathways: through elevated autistic traits, through reduced self-esteem, and through the serial mediation of autistic traits leading to reduced self-esteem. Active and passive TikTok use exhibit divergent longitudinal associations with depression, mediated by distinct socio-cognitive mechanisms. These findings highlight the importance of distinguishing between usage modes when evaluating the mental health implications of short-video platforms. Full article

Identifying the spatio-temporal evolutionary patterns and driving mechanisms of rural tourism network attention is essential for predicting the development trends of the rural tourism industry and delivering refined industrial governance. Taking 356 prefecture-level cities in China from 2015 to 2024 as basic research units, this paper constructs a comprehensive evaluation system for rural tourism network attention based on multi-source data. Furthermore, its spatio-temporal evolution characteristics and internal influencing factors are systematically investigated by means of spatial autocorrelation analysis and geographically weighted regression. The results indicate that the overall level of rural tourism network attention in China shows an obvious fluctuating growth trend, which can be divided into three successive stages, namely steady growth (from 0.8530 in 2015 to 1.2028 in 2019), explosive growth (from 1.9563 in 2020 to 3.7471 in 2021) and high-level fluctuation (maintained in the high range of 2.4–3.4). In addition, with the continuous iteration of internet communication media, the guiding influence of traditional search platforms has gradually weakened, while emerging social media and short-video platforms have become the core carriers of online tourism traffic. Correspondingly, media innovation persistently reshapes the spatial distribution pattern of rural tourism network attention. In terms of spatial characteristics, rural tourism network attention has undergone a significant transformation from geographical gradient polarization to overall regional equilibrium. Specifically, from 2015 to 2024, the overall Moran’s I index remained positive, with values ranging from 0.0116 to 0.1358, indicating an overall trend of gradual decline. High-attention areas are predominantly concentrated in economically developed urban agglomerations, whereas remote and economically underdeveloped regions exhibit contiguous low-value aggregation characteristics, which reveals a remarkable trend of balanced development nationwide. In view of driving mechanisms, highway network density, tourism income, rural tourism resource and enrollment of university students are identified as the core driving factors dominating the spatio-temporal evolution of rural tourism network attention. Moreover, the intensity of the influence of each factor presents distinct spatial heterogeneity. This study further reveals that the spatial heterogeneity of rural tourism network attention calculated using multi-source fused data shows a remarkable convergent characteristic, which can reflect the actual distribution of the rural tourism market more objectively and accurately. Meanwhile, rural tourism network attention is typically characterized by scale-dependent with the spatial distribution at the macro-scale being more balanced than that at the meso- and micro-scales. Full article

Short-video addiction has emerged as a growing behavioral concern in the context of the widespread use of platforms such as Douyin and TikTok, posing potential risks to young adults’ psychological well-being. Psychological resilience and rejection sensitivity are considered important psychological characteristics that may function as protective and risk factors, respectively, in the development of addictive media use. However, the longitudinal interplay among these variables remains insufficiently understood. This study examined the longitudinal relationships among psychological resilience, rejection sensitivity, and short-video addiction over time among university students. A two-wave longitudinal design with a six-month interval was conducted among 1394 Chinese university students. Participants completed validated measures assessing short-video addiction, psychological resilience (CD-RISC-10), and rejection sensitivity (RSQ). Cross-lagged panel modeling (CLPM) was employed to investigate the bidirectional predictive associations among these variables while controlling for autoregressive effects. All three constructs demonstrated substantial temporal stability across the two measurement waves. Cross-lagged analyses indicated that higher psychological resilience at Time 1 predicted lower rejection sensitivity and lower short-video addiction at Time 2, whereas higher rejection sensitivity at Time 1 predicted lower psychological resilience and higher short-video addiction over time. Although these longitudinal associations were statistically significant, their effect sizes were modest. These findings suggest that psychological resilience and rejection sensitivity may represent protective and vulnerability-related psychological characteristics associated with short-video addiction over time. The findings support the I-PACE model by highlighting the dynamic and longitudinal associations among psychological resources, interpersonal vulnerability, and addictive digital behaviors. Interventions aimed at strengthening psychological resilience and reducing rejection sensitivity may contribute to preventing short-video addiction and promoting healthier digital engagement among university students. Full article

Despite increasing scholarly attention to short-video platforms as tourism communication tools, the mechanism through which sustainability-oriented persuasive cues shape Sustainable Tourism Intention remains insufficiently theorized. This article integrates the Elaboration Likelihood Model (ELM) and the Stimulus–Organism–Response (SOR) framework to explain how short-video persuasive cues may influence Sustainable Tourism Intention through Environmental Attitude. Methodologically, the paper adopts a theory synthesis and conceptual integration approach to connect insights from short-video persuasion, sustainability communication, environmental attitude research, and tourism intention studies. The framework treats short-video sustainability communication as a cue-dense persuasive environment, identifies key cue families, organizes selected cues according to likely central/peripheral processing tendencies, and positions Environmental Attitude as the sustainability-specific organismic evaluative state through which cue exposure translates into intention. It proposes that both central route-oriented and peripheral route-oriented cues may strengthen Environmental Attitude and may thereby shape Sustainable Tourism Intention, although they do so through different processing tendencies. The article concludes that integrating ELM and SOR provides a clearer and more bounded explanation of short-video sustainability persuasion and offers a structured basis for future empirical research. Full article

Beginning with the notion that short-form video sites represent key digital commerce destinations for food influencers in general, there is very little research explaining how specific persuasion cues lead to varying degrees of consumer engagement. Based upon the Elaboration Likelihood Model (ELM), Social Proof theory and the COBRA framework, this study aims to understand whether argument quality as a central-route cue and perceived emotional appeal as a peripheral-route cue affect consumption, contribution, creation engagement behaviors. Additionally, the study will determine if perceived post popularity, a platform-generated social proof signal, affects these relationships. A survey was conducted of 386 users of short food influencer videos. PLS-SEM analysis was performed on the survey data. Results indicated that both argument quality and perceived emotional appeal positively influence all three engagement levels. Perceived emotional appeal exerts a stronger effect, particularly on higher-engagement behaviors. The moderating effects of perceived post popularity were limited and applied solely to contribution, where it weakened the positive relationship between argument quality and contribution but strengthened the positive relationship between perceived emotional appeal and contribution. This study builds upon existing knowledge of how consumers respond to food influencer content by exploring differences between types of engagement and integrating platform-generated signals within an ELM-based theoretical model. Full article

Recommendation systems reorganize culture by linking classification, visibility, and value. This article analyzes Douyin’s #tuwei ecology as a socio-technical system in which platform architecture, creator formatting, audience evaluation, and urban-rural symbolic hierarchies interact through recursive feedback. We formalize this system as four coupled operators—commensuration, sign packaging, metricized valuation, and reception feedback—and derive two observable indices: an item-level transfer-efficiency ratio and a class-level diffusion–appreciation asymmetry index. Using 123,300 public #tuwei videos collected between May and November 2024, multimodal coding of 500 videos, and sentiment analysis of 61,284 comments, we identify a stable diffusion-appreciation asymmetry. Practice-oriented rural videos receive relatively strong approval after encounter, but they diffuse less widely than spectacle-oriented performances optimized for rapid recognition, ironic forwarding, and interaction density. Corpus-level tests (${\chi }^2$, N = 123,300; Cramér’s $V\approx 0.32$) and an outlier-sensitivity analysis confirm the pattern independently of the coded-sample size. To explain this pattern, we propose hyperreal differential order (HDO), a systems concept describing how platform infrastructures repackage embedded cultural practices into feed-compatible sign forms and then differentially amplify them across segmented attention circuits. We position HDO against algorithmic visibility, platformization, and metric power, showing what each leaves underspecified. The study offers a mechanism-based account of how short-video systems reorganize vernacular culture, symbolic power, and interpretive authority without relying on overt exclusion. Full article

The rapid expansion of online health information channels, particularly emerging artificial intelligence (AI) platforms, is transforming how individuals access and evaluate health information. Drawing on an extended Comprehensive Model of Information Seeking (CMIS), this research examined how different channel types (AI-based, short-video, and text-based) influence online health information-seeking behavior (OHISB) through a pilot validation (N = 258), a cross-sectional survey (Study 1; N = 300), and a between-subjects experiment (Study 2; N = 300). Study 1 tested an extended CMIS model incorporating channel type, source credibility, information credibility, and perceived usefulness, while Study 2 examined the causal effects of channel exposure. Structural equation modeling in Studies 1 and 2 consistently showed that source and information credibility predicted OHISB indirectly through perceived usefulness. AI channels showed no advantage in Study 1, whereas Study 2 found that participants perceived AI sources as more credible and useful, which indirectly predicted stronger intentions for SAMC and information seeking through the credibility–usefulness pathway. This change may reflect methodological differences between self-report recall-based and direct exposure designs, and the public’s growing familiarity with AI technologies. By integrating channel characteristics and credibility perceptions, this study extends the CMIS framework and provides evidence for AI’s enhanced perceived credibility in health information contexts, offering insights for improving AI-driven health communication. Full article

Professional UAV thermal imaging systems are widely used for inspection, environmental monitoring, search and rescue, agriculture, and technical diagnostics. However, their cost limits their use in education, preliminary field screening, rapid prototyping, and low-resource applications. This study evaluates a minimum-cost indirect UAV thermal sensing workflow based on a DJI Mini 4K consumer drone, a lightweight Servo King9000 smartphone, and a UTi260M smartphone-connected infrared thermal camera. In the proposed configuration, the smartphone displayed and recorded the thermal stream, while the onboard RGB camera of the UAV recorded the smartphone-displayed infrared video during flight. The aim was not to develop a radiometric UAV thermal imaging platform, but to determine whether such a low-cost configuration can provide qualitative presence/absence indication of clear thermal hotspots and to identify its operational limits. The system was experimentally assessed under no-payload and payload conditions, daylight and nighttime illumination, and several low-altitude operating heights. Additional motor-region thermal observations were performed using a UTi260T handheld thermal camera under loaded and unloaded operating conditions. The complete UAV–payload configuration had a measured mass of approximately 340 g, corresponding to an effective added payload of 91 g and a payload-to-UAV mass ratio of 36.5%. Payload operation reduced near-ground flight endurance from approximately 25 min to 14 min 40 s. The maximum observed motor-region temperature increased from 24.9 °C under unloaded operation to 42.0 °C under loaded operation, while motor thermal asymmetry increased from 4.8 °C to 7.6 °C. Nighttime and low-glare operation improved the readability of the smartphone-displayed thermal stream, with the most practical usability observed at approximately 10–20 m. The results show that the proposed workflow is feasible only for short-range qualitative thermal screening and clear hotspot presence/absence indication. The UAV-recorded video should not be interpreted as direct thermal data, but as an RGB recording of a smartphone display showing thermal information. Therefore, the workflow is not suitable for quantitative temperature measurement, radiometric thermal mapping, or accurate thermal shape delineation. The main operational limits are payload mass, suspended-load oscillation, display readability, reduced endurance, motor-region thermal loading, sensitivity to payload alignment, and the absence of raw radiometric data. Direct UTi260M smartphone-recorded thermal frames were additionally used for pixel-size-assisted qualitative verification of practical reference thermal targets, including a human-sized target and a vehicle-sized target, at selected low-altitude operating heights. Full article