Social Media Service Providers Research Articles

Influencing factors of social media addiction: a systematic review

PurposeAs an unhealthy dependence on social media platforms, social media addiction (SMA) has become increasingly commonplace in the digital era. The purpose of this paper is to provide a general overview of SMA research and develop a theoretical model that explains how different types of factors contribute to SMA.Design/methodology/approachConsidering the nascent nature of this research area, this study conducted a systematic review to synthesize the burgeoning literature examining influencing factors of SMA. Based on a comprehensive literature search and screening process, 84 articles were included in the final sample.FindingsAnalyses showed that antecedents of SMA can be classified into three conceptual levels: individual, environmental and platform. The authors further proposed a theoretical framework to explain the underlying mechanisms behind the relationships amongst different types of variables.Originality/valueThe contributions of this review are two-fold. First, it used a systematic and rigorous approach to summarize the empirical landscape of SMA research, providing theoretical insights and future research directions in this area. Second, the findings could help social media service providers and health professionals propose relevant intervention strategies to mitigate SMA.

Deep Ensemble Fake News Detection Model Using Sequential Deep Learning Technique.

Recently, fake news has been widely spread through the Internet due to the increased use of social media for communication. Fake news has become a significant concern due to its harmful impact on individual attitudes and the community’s behavior. Researchers and social media service providers have commonly utilized artificial intelligence techniques in the recent few years to rein in fake news propagation. However, fake news detection is challenging due to the use of political language and the high linguistic similarities between real and fake news. In addition, most news sentences are short, therefore finding valuable representative features that machine learning classifiers can use to distinguish between fake and authentic news is difficult because both false and legitimate news have comparable language traits. Existing fake news solutions suffer from low detection performance due to improper representation and model design. This study aims at improving the detection accuracy by proposing a deep ensemble fake news detection model using the sequential deep learning technique. The proposed model was constructed in three phases. In the first phase, features were extracted from news contents, preprocessed using natural language processing techniques, enriched using n-gram, and represented using the term frequency–inverse term frequency technique. In the second phase, an ensemble model based on deep learning was constructed as follows. Multiple binary classifiers were trained using sequential deep learning networks to extract the representative hidden features that could accurately classify news types. In the third phase, a multi-class classifier was constructed based on multilayer perceptron (MLP) and trained using the features extracted from the aggregated outputs of the deep learning-based binary classifiers for final classification. The two popular and well-known datasets (LIAR and ISOT) were used with different classifiers to benchmark the proposed model. Compared with the state-of-the-art models, which use deep contextualized representation with convolutional neural network (CNN), the proposed model shows significant improvements (2.41%) in the overall performance in terms of the F1score for the LIAR dataset, which is more challenging than other datasets. Meanwhile, the proposed model achieves 100% accuracy with ISOT. The study demonstrates that traditional features extracted from news content with proper model design outperform the existing models that were constructed based on text embedding techniques.

Analyzing Decision-Making Factors for Using Social Media: the Role Trust and Information Sharing

Purpose: This study is aimed at explaining the factors that influence a person to decide to use TikTok in the Jabodetabek (Jakarta-Bogor-Depok-Tangerang-Bekasi) area. This study also uses the variables of self-efficacy, utilitarian value, hedonic value, information sharing, trust, and decision-making.
 Design/Method/Approach: Quantitative approaches and explanatory research are used in this study. Respondents were consumers who used the TikTok application in the Jabodetabek area to determine the number of samples. The present study uses non-probability sampling and convenience sampling techniques with 252 respondents. Data collection methods used questionnaires, and data were analyzed using Exploratory Factor Analysis (EFA) and the Structural Equation Modelling (SEM) method with the help of AMOS 24.
 Findings: The findings of this study indicate that self-efficacy and hedonic value positively affect trust, and trust positively affects information sharing and decision-making. Nevertheless, the results of this study also explain that self-efficacy does not affect information sharing. The utilitarian value does not significantly affect trust, and information sharing does not affect decision-making.
 Practical Implications: Social media service providers should focus on the influence of information sharing and decision-making in the TikTok application, namely trust. One example is making efforts to improve consumer trust by protecting the personal information which consumers provide on social networking sites and developing the TikTok application as advertising for business. This study can be used as a reference for advertisers when choosing advertising media in the TikTok application because hedonic values influence trust in the TikTok application. Advertisers are advised to promote products by providing hedonic value, such as TikTok dance.
 Originality/Value: The use of the TikTok application is a trend that is currently popular. We tried to perform this research by using a dependent variable of decision-making that is not easy to find and is used in marketing studies.
 Paper type: Empirical

A two-factor theoretical model of social media discontinuance: role of regret, inertia, and their antecedents

PurposeAlthough materializing the benefits of social media substantially depends on sustained user participation, social media service providers are experiencing a decline in the number of users. Despite the relevance of studying and managing discontinuance behaviors, a systematic empirical investigation remains lacking. The present study draws on the idea of a two-factor model and aims to examine the enabler, inhibitor and their antecedents in the context of social media discontinuance.Design/methodology/approachThe proposed theoretical model was empirically validated through an online survey study of 238 social media users in China.FindingsFindings indicated that two negative outcomes of social media use (i.e. social overload and invasion of privacy) induce regret experience and ultimately foster discontinuance intentions. The development of discontinuance intentions was undermined by the level of inertia, which is rooted in social media habit, sunk costs and affective commitment.Originality/valueThis study draws attention to the fundamental difference between continuance and discontinuance behaviors, advances the existing understanding of postadoption behaviors by focusing on discontinuance inhibitors (e.g. inertia) and develops the first two-factor model for social media discontinuance by integrating the regret and status quo bias literature.

How does Weibo keep users hooked? A Weibo addictive behavior study based on netnography

Purpose With the rapid development of social media in the past few years, some dark aspects of usage have appeared, e.g., Weibo addiction. Therefore, the purpose of this paper is to address the question of how Weibo keeps users hooked. Design/methodology/approach The study utilizes the netnography method to explore the symptoms of Weibo addiction and how it is formed. Findings First, some Weibo users have typical symptoms of addictive behavior, such as withdrawal, loss of control and general living problems; second, narcissism plays an important role in the process of Weibo addiction and has a stronger effect on content generation than content consumption; third, some users use Weibo as a means to alleviate anxiety, but they can then become more anxious owing to addiction; and fourth, the effect of comments has two sides – on the one hand, comments are one kind of feedback to posts, satisfying posters’ social needs, while on the other hand, a storytelling system consists of one post and its comments, upon which some Weibo users become more dependent. Research limitations/implications This research is only a preliminary, exploratory study. Therefore, care should be taken when interpreting these findings. Practical implications This study should help social media service providers and users to pay attention to the risk of social media addiction. Social media service providers should take social responsibility, design more user-oriented guidelines for marketing ethics and launch more responsible marketing activities. Users should enhance self-control and better balance social media use and offline real life. Originality/value Netnography has not been widely used as an addictive behavior research technique. This study is further bolstered because it has also noticed the difference of addiction mechanisms between addictive micro-bloggers and their followers.

QoE-Assured 4K HTTP Live Streaming via Transient Segment Holding at Mobile Edge

HTTP-based live streaming has become increasingly popular in recent years, and more users have started generating 4K live streams from their devices (e.g., mobile phones) through social-media service providers like Facebook or YouTube. If the audience is located far from a live stream source across the global Internet, TCP throughput becomes substantially suboptimal due to slow start and congestion control mechanisms. This is especially the case when the end-to-end content delivery path involves radio access network at the last mile. As a result, the data rate perceived by a mobile receiver may not meet the high requirement of 4K video streams, which causes deteriorated quality-of-experience (QoE). In this paper, we propose a scheme named edge-based transient holding of live segment (ETHLE), which addresses the abovementioned issue by performing context-aware transient holding of video segments at the mobile edge with virtualized content caching capability. Through holding the minimum number of live video segments at the mobile edge cache in a context-aware manner, the ETHLE scheme is able to achieve seamless 4K live streaming experiences across the global Internet by eliminating buffering and substantially reducing initial startup delay and live stream latency. It has been deployed as a virtual network function at an LTE-A network, and its performance has been evaluated using real live stream sources that are distributed around the world. The significance of this paper is that by leveraging virtualized caching resources at the mobile edge, we address the conventional transport-layer bottleneck and enable QoE-assured Internet-wide live streaming services with high data rate requirements.

Disentangling the factors driving users' continuance intention towards social media: A configurational perspective

Building on perceived value theory, this study employs fuzzy set Qualitative Comparative Analysis (fsQCA) to derive configurational models that embody causal conditions for predicting users' continuance intention towards social media. From reviewing extant literature, we advanced four value dimensions to be gained from social media usage, namely hedonic value (enjoyment), information value (information documentation and information sharing), media value (media appeal), and social value (social interaction), which are measured via a survey questionnaire. Our findings reveal seven distinct configurations of causal conditions for inducing continuance intention towards social media among Chinese users. Particularly, the frequency of social media usage combined with perceptions of enjoyment were found to be core conditions reinforcing users' continuance intention towards social media. In turn, the existence of multiple configurations implies that social media service providers could concurrently pursue differentiated strategies for retaining users.