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This study focuses on perceived overload from environmental stimuli and individual psychology and behavioral interactions. It constructs a theoretical model with overload as the key stressor based on the stressor-strain-outcome (SSO) model. The authors argue that system feature overload (SFO), information overload, and social overload lead to two psychological strains: fear of missing out (FoMO) and fatigue among users of short video platforms, affecting their discontinuous usage intentions.

To test the hypotheses, the authors conducted a questionnaire survey on 412 users' short video platform usage and empirically tested the constructed model using the research tool SmartPLS 3.3.2.

The results of data analysis showed that most of the hypotheses were supported. Specifically, system feature overload, information overload and social overload all positively affected FoMO. However, SFO and information overload significantly affected fatigue. There was no significant relationship between social overload and fatigue. In addition, both FoMO and fatigue negatively influenced users' discontinuous usage intentions.

The current research on user behavior in information systems tends to focus on the influence in the positive direction and less on the negative direction. The research on discontinuous usage intention (DUI) is a very new research topic. This research studies the influencing factors of users' discontinuous behavior from the perspective of perceptual overload. It provides a unique view for future short video platform user behavior research, with significant theoretical contributions and essential practice for short video platform operators to improve services.

Considering the popularity and addictive attributes of short-form videos, this study aims to determine mechanisms by which short-form video features affect addiction.

This study conducts empirical research using data collected from 382 Chinese TikTok users. Based on the stimulus–organism–response framework, the research model was constructed from the opponent process theory (OPT) perspective through features and emotional elements.

The results show that short-form video features influence addiction by activating users' perceived enjoyment and feeling of withdrawal. Based on the positive and negative reinforcement of the OPT, users must repeatedly interact with short-form videos to maintain positive emotions or reduce negative emotions. Eventually, this practice will lead to addiction. Additionally, users' procrastination moderates the relationship between feeling of withdrawal and addiction.

This study discussed how features influence addiction through opponent emotions on short-form video from the OPT perspective, enriching scholars' research on social media addiction. Furthermore, this study examined the moderating effects of procrastination and identifies unique features of short-form videos.

Short-form videos have gradually become important marketing tools for tourist destinations. However, chaotic sources and homogenized content have led to poor user experiences. Taking Kulangsu and Xi'an City Wall in China as examples, this study explored the influence of matching short-form video sources with destination types on user engagement and visit intention.

This study selected three short-form videos from different sources for each destination on TikTok and conducted an empirical research using a 3 × 2 experimental design to examine the proposed research model.

The results showed that the matching effect between short-form video sources and destination types will positively affect user engagement and visit intention. (1) the short-form videos with user-generated content (UGC) or professional user-generated content (PUGC) in hedonic destinations can obtain higher user engagement and visit intention; (2) the short-form videos with professionally generated content (PGC) or PUGC in utilitarian destinations can obtain higher user engagement and visit intention and (3) perceived credibility and perceived usefulness played mediating roles in these interactions.

This study considers short-form video sources as antecedent variables influencing user engagement and visit intention and confirms the matching effect between short-form video sources and tourism destination types. The findings will help researchers and marketers better understand the impact of short-form video on destination marketing.

The discontinuous usage behavior of short video social media presents an ongoing challenge to platform development. The purpose of this study is to investigate the antecedents of intentions to short media discontinuous usage.

This study adopts a Cognition–Affection–Conation (CAC) framework to analyze short video social media discontinuous intention on the basis of cognitive dissonance theory (CDT) and self-efficacy theory. The empirical evaluation of the research model was conducted using SmartPLS 2.0 and was based on questionnaire data obtained from participants in China.

The results show information overload and user addiction have a significant positive association with cognitive dissonance, which is, in turn, found to significantly impact discontinuous usage intention. Self-efficacy moderates the relationships between information overload, user addiction, cognitive dissonance and discontinuous usage.

This study contributes to the understanding of the factors that influence short video discontinuous usage intention and it achieves this by engaging from a CDT perspective and by applying Self-Efficacy Theory. Theoretical implications for future short video platform research, as well as practical suggestions for short video platform operators and users, are also discussed.

Middle-aged and elderly users become an important group on short-video platforms, however, the research on determinants of their video-creating intention is limited. Based on lifespan development theories, this study examines the impact of aging experiences on their video-creating intention, considering internal generative motivations as mediators and age as a moderator.

To test this study’s hypotheses, survey data from 321 Chinese middle-aged and elderly short-video users were collected and partial least square-structural equation modelling (PLS-SEM) approach was used to analyze these data.

Middle-aged and elderly users' aging experiences of social loss and personal growth are positively related to their video-creating intention. Aging experiences (i.e. physical loss, social loss, and personal growth) are positively related to internal generative motivations (i.e. need to be needed and symbolic immortality), and need to be needed is positively related to video-creating intention. Via the mediation of need to be needed, physical loss and personal growth are indirectly positively related to video-creating intention. Personal growth strengthens the relationship between physical loss and symbolic immortality, but weakens the associations of social loss with need to be needed and symbolic immortality. Age weakens the relationship between symbolic immortality and video-creating intention.

This study is the first wave to introduce and integrate lifespan theories such as selective optimization with compensation model, socioemotional selectivity theory, and generativity theory to explore the impacts of aging experiences on middle-aged and elderly users' video-creating intention by considering generativity motivations as mediators and age as a moderator.

With the rapid development of short videos in China, the public has become accustomed to using short videos to express their opinions. This paper aims to solve problems such as how to represent the features of different modalities and achieve effective cross-modal feature fusion when analyzing the multi-modal sentiment of Chinese short videos (CSVs).

This paper aims to propose a sentiment analysis model MSCNN-CPL-CAFF using multi-scale convolutional neural network and cross attention fusion mechanism to analyze the CSVs. The audio-visual and textual data of CSVs themed on “COVID-19, catering industry” are collected from CSV platform Douyin first, and then a comparative analysis is conducted with advanced baseline models.

The sample number of the weak negative and neutral sentiment is the largest, and the sample number of the positive and weak positive sentiment is relatively small, accounting for only about 11% of the total samples. The MSCNN-CPL-CAFF model has achieved the Acc-2, Acc-3 and F1 score of 85.01%, 74.16 and 84.84%, respectively, which outperforms the highest value of baseline methods in accuracy and achieves competitive computation speed.

This research offers some implications regarding the impact of COVID-19 on catering industry in China by focusing on multi-modal sentiment of CSVs. The methodology can be utilized to analyze the opinions of the general public on social media platform and to categorize them accordingly.

This paper presents a novel deep-learning multimodal sentiment analysis model, which provides a new perspective for public opinion research on the short video platform.

This study explores whether and how four main factors of short-branded video content (content matching, information relevance, storytelling and emotionality) facilitate consumer engagement (likes, comments and shares), as well as the moderating effect of the release time (morning, afternoon and evening) in such relationships.

This study uses Python to write programs to crawl relevant data information, such as consumer engagement and short video release time. It combines coding methods to empirically analyze the impact of short-branded video content characteristics on consumer engagement. A total of 10,240 Weibo short videos (total duration: 238.645 h) from 122 well-known brands are utilized as research objects.

Empirical results show that the content characteristics of short videos significantly affected consumer engagement. Furthermore, the release time of videos significantly moderated the relationship between the emotionality of short videos and consumer engagement. Content released in the morning enhanced the positive impact of warmth, excitement and joy on consumer engagement, compared to that released in the afternoon.

The findings provide new insights for the dissemination of products and brand culture through short videos. The authors suggest that enterprises that use brand videos consider content matching, information relevance, storytelling and emotionality in their design.

From a broader perspective, this study constructs a new method for comprehensively evaluating short-branded video content, based on four dimensions (content matching, information relevance, storytelling and emotionality) and explores the value of these dimensions for creating social media marketing success, such as via consumer engagement.

Short-form health science videos have become an important medium for disseminating health knowledge and improving public health literacy. However, the factors that determine viewer engagement are not well understood. This study aims to address this research gap by investigating the association between doctor image features and viewer engagement behavior, building on the personal branding theory and information signaling theory.

A sample of 1245 health science short-form videos was collected, and key video features related to doctor images were extracted through manual labeling. Multi-variable regression analysis and SPSS process model were employed to test the hypotheses.

The results show that doctor image features are significantly associated with viewer engagement behavior. Videos featuring doctors in medical uniforms receive more viewer likes, comments and shares. Highlighting the doctor's title can increase viewer collections. Videos shot in a home, white wall, or study room setting receive more like, comments and sharing. The doctor's appearance demonstrates a positive nonlinear relationship with viewer likes and comments. Young doctors with title information tend to attract more video collections than older doctors with title information. The positive effect of the doctor's appearance and showing title information, become more significant among male doctors.

This research provides novel insights into the factors that determine viewer engagement behavior in short-form health science videos. Specific doctor image features can enhance viewer engagement by signaling doctor professionalism. The results also suggest that there may be age and gender biases in viewers' perceptions.

Drawing on information foraging theory and the SERVQUAL model, this study built a research model to investigate the roles of middle-aged and elderly short-video creators' online attributes in attracting short-video viewers to be their followers.

Taking Douyin (a famous short-video platform in China) as an example, this study used a sequential triangulation mixed-methods approach (quantitative → qualitative) to examine the proposed model by investigating both creators and viewers.

Viewers who clicked the “like” button for the middle-aged and elderly creators' videos are more likely to follow the creators. Viewers will believe that middle-aged and elderly creators who received more likes are more popular. Thus, middle-aged and elderly creators with more likes usually have more followers. Viewers usually believe that middle-aged and elderly creators who more frequently publish professional and high-quality videos have invested more effort and who have official verification also have a high level of authority and are recognized by the platform. Thus, middle-aged and elderly creators with more professional videos and verification usually have more followers. Moreover, verification, the number of videos and the professionalism of videos can enhance the transformation of viewers who liked middle-aged and elderly creators' videos into their followers, and thus strengthen the positive relationship between the number of likes and the number of followers; however, the number of bio words will have an opposite effect.

These findings have implications for platform managers, middle-aged and elderly creators and the brands aiming to develop a “silver economy” by attracting more followers.

This study researches short-video platforms by using a mixed-methods approach to develop an understanding of viewers' decision-making when following middle-aged and elderly creators based on information foraging theory and the SERVQUAL model from the perspectives of both short-video creators and viewers.

Although the short-video-based application TikTok and its AI-enhanced technology have achieved enormous success and reshaped the user experience, few studies have focused on the user experience in the TikTok context. This study adopts a technology affordance theory lens to identify the main mechanisms contributing to the user experience in the short-video platform context while including user experience level and video length as moderating effects.

This study collected 401 valid questionnaires from TikTok users and used the structural equation modeling approach to examine the proposed research model.

Three technology affordances (perceived effortlessness, perceived recommendation accuracy, and perceived recommendation serendipity) contribute to TikTok users' optimal flow experience. Multi-group analysis results further indicate that individuals react differently to the same stimuli as their experience level increases. Finally, video length critically influences the impact of technology affordances on users' cognitive responses.

As a burgeoning industry, the mechanisms enabling short-video platforms to engage users remain unclear to practitioners and researchers. Thus, this study's technology affordance lens provides necessary insights into how TikTok's innovative and advanced technologies contribute to user flow experience from a context-dependent perspective. Furthermore, given that most existing studies have neglected possible variations in user preferences when investigating the effects of technology, this study enriches the existing literature by employing user experience level and video length as moderators.