Social Networking Services Platforms Research Articles

Value Communication Model of Social Networking Services: Research on the Depth Value Communication Patterns of Short Video Cultural Hotspots

Based on social networking services (SNS) platforms, the value communication of short videos rapidly expands its dissemination scale with low participation costs. The recipients of value, acting as both receivers and transmitters, generate and propagate the depth value of short videos through the interactive process. This paper takes the phenomenon-level short drama Escape from the British Museum on domestic short video platforms as the research object. Grounded in the Four Segments Three Relationships model, which articulates the development laws of online public opinion, this study establishes a value communication model for short videos on social networking service platforms. It explores the depth value communication patterns of short video cultural hotspots, and consequently, proposes the SNS Value Communication Model for short video dissemination. This model, with stages of value presentation, value judgment, value interaction, and value dissemination as its core, provides feasible paths for the deepening of positive value communication and the guidance of negative value in short video cultural hotspots.

Personality traits and mental health of social networking service users: A cross-sectional exploratory study among Japanese undergraduates

In this study, we investigated personality and mental health variables for users of three popular social networking services (SNS): Twitter, Instagram, and Facebook, among Japanese undergraduate students (N = 1030). Compared to non-users, Twitter users scored significantly lower in extraversion, conscientiousness, openness, and self-esteem, and higher in neuroticism, behavioral inhibition system (BIS) sensitivity, and social comparison orientation. Instagram users scored significantly higher in extraversion, behavioral approach system (BAS) -drive, BAS-reward responsiveness, BAS-fun seeking, narcissism, self-esteem, and subjective happiness, and lower in neuroticism, anxiety, and to a marginal extent, depression. Facebook users scored significantly higher in extraversion, openness, BAS-fun seeking, self-esteem, and to a marginal extent, narcissism. Within SNS users, extraversion, agreeableness, and self-esteem were negatively associated with negative mental health variables, and positively associated with positive mental health variables. Neuroticism was positively associated with negative mental health variables, and negatively associated with positive mental health variables. Further, some associations were found within specific SNS users. Differences in personality and mental health were discussed based on the characteristics of each SNS platform.

To Disclose or Not to Disclose: An Evaluation of the Effects of Information Control and Social Network Transparency

Self-disclosure on Social Network Service (SNS) platforms has attracted attention in Information Systems (IS) research. While studies have investigated the effects of individual factors such as privacy concern, and trust, on SNS users’ self-disclosure intention, less research has examined how characteristics of the SNS platform shape such intention. In this study, we focus on one critical characteristic of SNS platform, SNS transparency, and investigate its impact (direct and indirect via Information Control) on individuals’ self-disclosure intention and the moderating role of privacy disposition. Specifically, we identify three SNS transparency features—Network Transparency, Social Presence, and Monitoring. Drawing from Communication Privacy Management Theory and Social Penetration Theory, we empirically test how these SNS transparency features directly and indirectly via Information Control influence users’ self-disclosure intention. The results of our experiment show that network transparency has negative effects while social presence, as well as monitoring, have positive effects on information control. Network transparency, social presence, and information control have positive effects on self-disclosure intention. This study extends the literature by enhancing our understanding of how the SNS platform features and individual privacy disposition shape SNS users’ self-disclosure intention.

Telegram as Social Networking Service (SNS) For Enhancing Students’ English: A Systematic Review

<em>Social Networking Services (SNS) has become part of English learning, providing educators and students with free service and wide usage applicable to synchronous and asynchronous instruction. This study intended to critically review previous studies on the use of Telegram as one of the SNS platforms for enhancing students' reading, writing, speaking, and listening skills. Following George’s (2008) Literature Reviews model, 20 manuscripts were reviewed. The selection was taken from reputable International Journals indexed by Scopus quartile 1, 2, and 3, published between 2016-2020. It was revealed that Telegram is argued to have positively affect the students' four language skills in learning English. Telegram is claimed to benefit the students in terms of vocabulary, reading comprehension, content, and organization in writing, grammar, language style, pronunciation, and listening comprehension. Experts highlighted the relaxed and informal nature of Telegram as SNS to be one of the main factors that contributed positively to students' reduced anxiety and raised motivation in learning. Reflecting on those positive effects of Telegram on students' scholastics progress, the present study implies that Telegram may be an alternative for online learning and extensive learning of English.</em>

SNS Big Data Analysis Framework for COVID-19 Outbreak Prediction in Smart Healthy City

Nowadays, the world is experiencing a pandemic crisis due to the spread of COVID-19, a novel coronavirus disease. The contamination rate and death cases are expeditiously increasing. Simultaneously, people are no longer relying on traditional news channels to enlighten themselves about the epidemic situation. Alternately, smart cities citizens are relying more on Social Network Service (SNS) to follow the latest news and information regarding the outbreak, share their opinions, and express their feelings and symptoms. In this paper, we propose an SNS Big Data Analysis Framework for COVID-19 Outbreak Prediction in Smart Sustainable Healthy City, where Twitter platform is adopted. Over 10000 Tweets were collected during two months, 38% of users aged between 18 and 29, while 26% are between 30 and 49 years old. 56% of them are males and 44% are females. The geospatial location is USA, and the used language is English. Natural Language Processing (NLP) is deployed to filter the tweets. Results demonstrated an outbreak cluster predicted seven days earlier than the confirmed cases with an indicator of 0.989. Analyzing data from SNS platforms enabled predicting future outbreaks several days earlier, and scientifically reduce the infection rate in a smart sustainable healthy city environment.

Audience management, online turbulence and lurking in social networking services: A transactional process of stress perspective

• We explore the antecedents and outcomes of online turbulence based on the transactional process of stress. • The concept of neglected unintended audience in SNS is conceptualized. • Online turbulence is a significant stressor impacting neglected unintended audience concern. • Neglected unintended audience concern leads to lurking. • Different types of audience management strategies have different impacts on online turbulence. In social networking services (SNSs), users’ unclear understanding of the large and invisible audience increases the chances of online turbulence, which is a key source of SNS-induced stress. This growing phenomenon has gained increasing attention in academia and industry due to the undesirable consequences for users and SNS platforms. In this study, we draw from the transactional model of stress to examine how audience management strategies impact online turbulence and lead to neglected unintended audience concern and lurking. We also investigate the role of self-monitoring as a stress inhibitor. We test our model with data collected from 301 SNS users. The results show that the four types of audience management strategies have different effects on online turbulence, which significantly impacts neglected unintended audience concern especially when users have high self-monitoring skills. We believe that this work contributes, both from scientific and practical standpoints, to the understanding of the interventions and stressful responses of online turbulence in SNSs.

Understanding How People Select Social Networking Services: Media Trait, Social Influences and Situational Factors

Social networking services (SNSs) have become very popular, and many Internet users use two or more SNSs. However, little research has been done to understand how and when users select multiple SNSs in series. This study investigates Internet users’ SNS selection behavior in daily life. We adopt the notion of media repertoire to explore how Internet users select SNSs in combination, and we adopt uses and gratifications theory to identify the values that drive these users to choose specific SNSs. We interviewed 40 Taiwanese people to explore the media traits, situational factors and social influences that affect users’ SNS selection behavior. The findings of this study can help SNS companies to improve SNS functions, and help marketers devise marketing strategies for target audiences and find suitable SNS platforms on which to communicate with consumers.

A New Cognitive Framework for Understanding Social Commerce: A Service Ecosystem Perspective

Under the background of social network, Social Commerce has become one of the most popular front issues in business transformation and digital commerce. Based on the idea of Service Science and ecosystem, this paper abstracts social business network into a service system, and proposes a new cognitive framework of Social Commerce Ecosystem Model. From the five aspects of common support, social network service platform, service ontology and resource, service operating and collaborating, and service application, an open, dynamic and collaborative ecosystem is constructed to lay an important foundation for further research and disclosure of the ecological structure and business model of Social Commerce industry.

Facial Expressions of Visitors in Forests along the Urbanization Gradient: What Can We Learn from Selfies on Social Networking Services?

People’s satisfaction towards the experience in forests is one of most important feedbacks that forest park managers need to meet positive visitors’ experiences. Although the drawbacks of questionnaire methodology are obvious for data collection from self-reported scores at the landscape scale, few alternative methods have been proposed. In this study, nine urban forest parks along the urbanization gradients in three capital cities of Northeast China were targeted to investigate their visitors’ selfies from social networking services (SNS) by assessing facial expressions. A total of 935 photos with location records were obtained from the SNS platform of Sina Micro-Blog in a social hot-event of ‘Golden Week Holidays of National Day of China’ of 2017. Images were recognized by FireFace software to assess scores of neutral, happy, sad, angry, surprised, scared, disgusted, and contempt expressions. Data were ranked in descending order and analyzed by Friedman’s test, correlation analysis, and Poisson regression. Visitors in downtown-forests showed fewer negative expressions at the most northern city than at the southern most one. The negative expressions tended to be alleviated with the increasing distance of forest parks from downtown. However, when the distance reached over 10 km no geographical effect was found. Female visitors showed positive emotional expressions to urban forests while male visitors showed no response. In conclusion, using data from SNS, this study found an experience in forest park less than 10 km from the downtown of a northern city resulted in female visitors showing the most positive expressions.

Requirements for private communications over public spheres

Purpose In the Web 2.0 era, users massively communicate through social networking services (SNS), often under false expectations that their communications and personal data are private. This paper aims to analyze privacy requirements of personal communications over a public medium. Design/methodology/approach This paper systematically analyzes SNS services as communication models and considers privacy as an attribute of users’ communication. A privacy threat analysis for each communication model is performed, based on misuse scenarios, to elicit privacy requirements per communication type. Findings This paper identifies all communication attributes and privacy threats and provides a comprehensive list of privacy requirements concerning all stakeholders: platform providers, users and third parties. Originality/value Elicitation of privacy requirements focuses on the protection of both the communication’s message and metadata and takes into account the public–private character of the medium (SNS platform). The paper proposes a model of SNS functionality as communication patterns, along with a method to analyze privacy threats. Moreover, a comprehensive set of privacy requirements for SNS designers, third parties and users involved in SNS is identified, including voluntary sharing of personal data, the role of the SNS platforms and the various types of communications instantiating in SNS.

Construction and Performance Analysis of Image Steganography-Based Botnet in KakaoTalk Openchat

Once a botnet is constructed over the network, a bot master and bots start communicating by periodically exchanging messages, which is known as botnet C&C communication, in order to send botnet commands to bots, collect critical information stored in bots, upgrade software functions of malwares installed in bots, and so on. For this reason, most existing botnet detection techniques focus on monitoring and capturing suspicious communications between the bot master and bots. Meanwhile, botnets continue to evolve to hide their C&C communication. Recently, a novel type of botnet using image steganography techniques and SNS (Social Network Service) platforms, which is known as image steganography-based botnet or stegobotnet, has emerged to make its C&C communications undetectable by existing botnet detection systems. In stegobotnets, image files used in SNSs carry messages (between the bot master and bots) which are hidden in them by using image steganography techniques. In this paper, we first investigate whether major SNS platforms such as KakaoTalk, Facebook, and Twitter can be suitable for constructing image steganography-based botnets. Next, we construct a part of stegobotnet based on KakaoTalk, and conduct extensive experiments including digital forensic analysis (1) to validate stegobotnet C&C communication can be successful in KakaoTalk and (2) to examine its performance in terms of C&C communication reliability.

The Effects of Social Information Cues Featured in SNS Ads on Unfamiliar Product Adoption

This study tests the effects of social information cues on ad responses and consumer decision making processes in the domain of unfamiliar product adoption. The findings show that participants having a huge size of the social network are particularly responsive to social information cues featured in the ads, showing an inverted U-shape pattern of purchasing intentions as the number of prior product purchasers increased. Findings suggest targeting and marketing strategies on social network service platforms.

Twitter-Based Influenza Detection After Flu Peak via Tweets With Indirect Information: Text Mining Study.

BackgroundThe recent rise in popularity and scale of social networking services (SNSs) has resulted in an increasing need for SNS-based information extraction systems. A popular application of SNS data is health surveillance for predicting an outbreak of epidemics by detecting diseases from text messages posted on SNS platforms. Such applications share the following logic: they incorporate SNS users as social sensors. These social sensor–based approaches also share a common problem: SNS-based surveillance are much more reliable if sufficient numbers of users are active, and small or inactive populations produce inconsistent results.ObjectiveThis study proposes a novel approach to estimate the trend of patient numbers using indirect information covering both urban areas and rural areas within the posts.MethodsWe presented a TRAP model by embedding both direct information and indirect information. A collection of tweets spanning 3 years (7 million influenza-related tweets in Japanese) was used to evaluate the model. Both direct information and indirect information that mention other places were used. As indirect information is less reliable (too noisy or too old) than direct information, the indirect information data were not used directly and were considered as inhibiting direct information. For example, when indirect information appeared often, it was considered as signifying that everyone already had a known disease, leading to a small amount of direct information.ResultsThe estimation performance of our approach was evaluated using the correlation coefficient between the number of influenza cases as the gold standard values and the estimated values by the proposed models. The results revealed that the baseline model (BASELINE+NLP) shows .36 and that the proposed model (TRAP+NLP) improved the accuracy (.70, +.34 points).ConclusionsThe proposed approach by which the indirect information inhibits direct information exhibited improved estimation performance not only in rural cities but also in urban cities, which demonstrated the effectiveness of the proposed method consisting of a TRAP model and natural language processing (NLP) classification.

Contingency Model of Multiple SNSs Running Strategy in Art and Cultural Institutions

Social Network Service (SNS) is getting popular among various organizations as a powerful tool for communication and promotion. Recently, cultural and art institutions began to employ multiple SNS platforms for a variety of applications such as marketing, communication, customer services, and even program development. It is a challenging task to run multiple SNSs platforms to execute many different applications. Although this is a more common trend, there have been few studies to explore the factors that might influence the successful running of multiple SNSs, in particular in the art and cultural institutions. As critical factors, our study considered three factors, 1) the applications of SNS use, 2) the features of SNS platform, and 3) the characteristics of SNS. From the perspective of contingency theory, we suggested the integrative model that when the fit among these three factors will result in the best outcomes. Using a case study method, we analyzed the case of Daelim museum in order to test our proposed model. We found that the fitness among the target audience, the selection of platform, and the purposes of usage lead to the increased number of audiences and the satisfaction with the services.

Social constructivist approach of motivation: social media messages recommendation system

Contemporary learning theories and their implementations associated with information and communication technologies increasingly integrate social constructivist approaches in order to assist and facilitate the construction of knowledge. Social constructivism also highlights the important role of culture, learning attitude and behavior in the cognitive process. Modern e-learning systems need to include these psychological aspects in addition to knowledge construction in order to connect with long-standing pedagogical issues such as the decrease and lack of motivation for education. Current Social Networking Services (SNS) provide a platform where peers can express their passion, emotion, and motivation toward learning. Therefore, this research utilizes this platform to recommend motivational contents from peers for learning motivation enhancement (i.e., learners’ perception of their goal and purpose for learning). The proposed system consists of an SNS platform for learners to (1) express and evaluate their own goals for learning, (2) observe motivational messages from peers recommended from an LDA-based (latent Dirichlet allocation) model, and (3) evaluate their perceptions on motivational and psychological attributes. The LDA-based model recommends messages expressing diverse purposes for a shared goal by maximizing the topic divergence of Twitter messages. Learners’ self-evaluations show the positive and significant impact of observing diverse learning purposes from peers on intrinsic motivational attributes such as goal specificity, attainability, and on the confidence to achieve the desired outcome.

Towards a New Digital Era: Observing Local E-Government Services Adoption in a Chinese Municipality

As electronic government services (e-government) evolve, traditional applications such as online portals are encountering challenges in a new digital era in which people thirst for more convenient, diverse channels of communication with their government. Despite the efforts devoted to the promotion of Social Networking Service (SNS) use in e-government for the past few years, empirical studies regarding this ongoing trend are still insufficient. In the local administration of China, a special collaboration between local governments and private Internet enterprises is happening: government services are imported into commercial SNS platforms known as WeChat and Weibo. This research conducts a case study of a Chinese municipality premised upon survey data (N = 605) collected in Chongqing. It examines the determinants of e-services adoption in four major local applications: two traditional government-led services “Government website portal” and “Government official app” (traditional government-led services), and two built-in government services on social networking applications “Weibo Government official account” “WeChat Public Services”. The paper aims to provide a closer understanding of current trends in local government e-services, or in this case, an innovative trial of Chinese e-government practices.

Examining the scope and patterns of deliberate self-injurious cutting content in popular social media.

Social networking services (SNS) have rapidly become a central platform for adolescents' social interactions and media consumption patterns. The present study examined a representative sample of publicly accessible content related to deliberate self-injurious cutting across three SNS platforms: Twitter, Tumblr, and Instagram. Data collection simulated searches for publicly available deliberate self-injury content on Twitter, Tumblr, and Instagram. Over a six-month period at randomly generated time points, data were obtained by searching "#cutting" on each SNS platform and collecting the first 10 posts generated. Independent evaluators coded posts for presence of the following: (a) graphic content, (b) negative self-evaluations, (c) references to mental health terms, (d) discouragement of deliberate self-injury, and (e) recovery-oriented resources. Differences across platforms were examined. Data collection yielded a sample of 1,155 public posts (770 of which were related to mental health). Roughly 60% of sampled posts depicted graphic content, almost half included negative self-evaluations, only 9.5% discouraged self-injury, and <1% included formal recovery resources. Instagram posts displayed the greatest proportion of graphic content and negative self-evaluations, whereas Twitter exhibited the smallest proportion of each. Findings characterize the graphic nature of online SNS deliberate self-injury content and the relative absence of SNS-posted resources for populations seeking out deliberate self-injurious cutting content. Mental health professionals must recognize the rapidly changing landscape of adolescent media consumption, influences, and social interaction as they may pertain to self-harm patterns.

Social Crowdsourcing to Friends: An Incentive Mechanism for Multi-Resource Sharing

In this paper, we propose a novel game-based incentive mechanism for multi-resource sharing, where users are motivated to share their idle resources in view of conditional voluntary. Through social networking service platforms, such a crowdsourcing service fully explores the significant influence and computing potential of mobile social networks. Specifically, a combination of task allocation process, profit transfer process, and reputation updating process are involved in this sharing incentive mechanism, satisfying truthfulness, individual rationality, and robustness. To maintain the social fairness-efficiency tradeoff, we further develop a resource sharing algorithm on the basis of dominant resource fairness, revealing that the sacrifice of fairness properties is necessary for the improvement of efficiency. Real-world traces from Facebook are numerically studied, validating social fairness and efficiency of our social crowdsourcing mechanism.

An Empirical Study of Knowledge Sharing Behavior of the SNS : A Case Study of “Sina Weibo”

SNS (social networking services) is a significant platform for Internet users to get knowledge and information , and users can share messages mutually via this platform. This kind of sharing can make user exchanges and gain useful information to benefit themselves. However, in recent years, the crisis of stickness has appeared in SNS, which raised the attention of the social network industry. Relevant professionals explain that most users may gradually reduce the interest of sharing knowledge on SNS websites and applications and then give it up because the platforms utilize simple and uninterested methods to attract the users to participate actively on them. But factors influencing the knowledge sharing on SNS websites and applications should be identified clearly through researches. Sina Weibo is one of the largest SNS platforms in the world, and the researches on the factors influencing the knowledge sharing of users could be valuable for the issue. This paper establishes the theoretical analysis model of knowledge sharing in SNS sites and applications, analyzes the influencing factors of knowledge sharing on them, and puts forward the corresponding strategies thereof. With the questionnaire surveys of Sina Weibo users, this article will discuss the influencing factors of knowledge sharing, and analyze the influencing factors on social network site as well as improving the stickness of users, so as to achieve the aim that SNS platforms capable of expanding the mount of users. It will firstly discuss the theoretical foundations, from which the hypotheses are put for. After that, the method of the study is discussed. Finally, it would be concluded with the theoretical implications, practical implications, limitations, and future researc h opportunities. The results of this study could be helpful for researchers in understanding the underlying reasons for social network activities as well as for SNS developers in improving SNS services.

Social networking services: A digital extension of the surveillance state?

This paper investigates whether or not corporate social networking services (SNS) possess the potential to act as surveillance tools within contemporary society and, as a corollary, operate as coercive and exploitative technologies for the individuals who employ such devices in their daily lives. By relying on an interdisciplinary framework, this investigation argues that exploitative surveillance practices are indeed evident within the digital world of SNS platforms, along with how a performativity pressure (in the form of continuous self-surveillance) has been engendered within the user of such platforms. This has resulted in the creation of coercive digital structures that are then exploited for commercial gain. As such, these SNS technologies can be said to facilitate the expansion of what Foucault terms a disciplinary society, which has then also led to the proliferation of certain “free-floating” forms of control which play a significant part in Deleuze’s societies of control. Furthermore, this paper argues for the continuing relevance of both Foucault’s insights regarding the panoptic schema, and Deleuze’s commentary regarding mechanisms of control, in order to attain a critical understanding of how the practice of online surveillance occurs and from where it is that such an invasive practice derives its impetus.