The future of online social networks (OSN): A measurement analysis using social media tools and application

University students' and educators' perceptions on the use of digital and social media platforms: A sentiment analysis and a multi-country review

Due to Covid-19, an inevitable restructuring of higher education teaching and learning pedagogies ensuring the continuous and effective learning of students is deemed important. Despite such vitality, a prevalent disparity worldwide on the usages and gains of digital and social media integration is still noticeable. Following a Scoping Literature Review and using the Atlas.ti software for a Grounded Theory qualitative analysis, this study aims to ascertain the significance of digital and social media tools during and after the Covid-19 pandemic. The study explains the common challenges and opportunities both students and educators faced in thirty countries. Drawing on the sentiment analysis of these stakeholders, results indicate that despite the acceleration of digital education into a flexible, and student-centered didactic approach, various barriers in effectively fulfilling online learning still exist. Findings also revealed the lack of, and therefore need for, proper teaching and learning material and strategies suitable for digital education.

Spirituality, Personality, and Emotional Distress During COVID-19 Pandemic in Croatia

This study examined the association between spiritual quality of life (QoL), spiritual coping, emotional distress, and personality during the COVID-19 pandemic lockdown in a convenience sample of Croatian adults (n = 2,860, 80.6% women). Participants completed an online questionnaire that collected information on sociodemographic characteristics, distress (the Depression, Anxiety, and Stress Scale 21), spiritual coping and spiritual QoL (the WHO Quality of Life-Spirituality, Religiousness, and Personal Beliefs), and personality (the International Personality Item Pool). The hierarchical regression analysis demonstrated that personality traits, especially emotional stability, were the most significant predictors of mental health outcomes. Spiritual coping styles were a predictor of worse, while spiritual QoL of better psychological outcomes. Results demonstrate the complex relations between different aspects of spirituality/religiosity with personality and emotional outcomes and suggest that distress motivates the engagement of spiritual coping in times of disaster.

Factors Affecting the Success of Social Commerce in Kuwaiti Microbusinesses

Many studies have focused on the adoption of social commerce (s-commerce) by customers but not by businesses or by microbusinesses. Further, they have investigated this adoption from a researcher's perspective while using quantitative approaches. To fill this gap, the study sheds light on the success of Instagram for microbusinesses (IMB) in an Arab country and highlights the need for more investigation in order to understand this complex phenomenon. In this study, the authors use a qualitative approach to 27 microbusiness cases that adopted Instagram for s-commerce. They use technological innovation theories to successfully identify and classify the drivers and inhibitors of success under different contexts. Hence, they find that the success of IMB in Kuwait is contingent on addressing different technological, organizational, and environmental challenges. Further, they find that Instagram initiatives are still evolving and still need assistance from different stakeholders to overcome several hurdles. This study provides different recommendations that advance the theory and practice.

Social Media Improves Students' Academic Performance: Exploring the Role of Social Media Adoption in the Open Learning Environment among International Medical Students in China

Numerous studies have examined the role of social media as an open-learning (OL) tool in the field of education, but the empirical evidence necessary to validate such OL tools is scant, specifically in terms of student academic performance (AP). In today’s digital age, social media platforms are most popular among the student community, and they provide opportunities for OL where they can easily communicate, interact, and collaborate with each other. The authors of this study aimed to minimize the literature gap among student communities who adopt social media for OL, which has positive impacts on their AP in Chinese higher education. We adopted social constructivism theory (SCT) and the technology acceptance model (TAM) to formulate a conceptual framework. Primary data containing 233 questionnaires of international medical students in China were collected in January 2021 through the survey method. The gathered data were analyzed through structural equation modeling techniques with SmartPLS 3. The results revealed that perceived usefulness, perceived ease of use, and interactions with peers have positive and significant influence on OL. In addition, OL was found to have positive and significant influence on students’ AP and engagement. Lastly, engagement showed a positive impact on students’ AP. Thus, this study shows that social media serves as a dynamic tool to expedite the development of OL settings by encouraging collaboration, group discussion, and the exchange of ideas between students that reinforce their learning behavior and performance.

Big data-drive agent-based modeling of online polarized opinions

Under the mobile internet and big data era, more and more people are discussing and interacting online with each other. The forming process and evolutionary dynamics of public opinions online have been heavily investigated. Using agent-based modeling, we expand the Ising model to explore how individuals behave and the evolutionary mechanism of the life cycles. The big data platform of Douban.com is selected as the data source, and the online case “NeiYuanWaiFang” is applied as the real target, for our modeling and simulations to match. We run 10,000 simulations to find possible optimal solutions, and we run 10,000 times again to check the robustness and adaptability. The optimal solution simulations can reflect the whole life cycle process. In terms of different levels and indicators, the fitting or matching degrees achieve the highest levels. At the micro-level, the distributions of individual behaviors under real case and simulations are similar to each other, and they all follow normal distributions; at the middle-level, both discrete and continuous distributions of supportive and oppositive online comments are matched between real case and simulations; at the macro-level, the life cycle process (outbreak, rising, peak, and vanish) and durations can be well matched. Therefore, our model has properly seized the core mechanism of individual behaviors, and precisely simulated the evolutionary dynamics of online cases in reality.

Antecedents and outcomes of enterprise social network usage within UK higher education

Purpose

The purpose of this paper is to investigate factors influencing knowledge sharing on enterprise social network (ESN) use behaviour among academic staff in universities, using the unified theory of acceptance and use of technology (UTAUT) as the underlying research framework

Design/methodology/approach

A conceptual framework was created by extending the UTAUT by incorporating three additional factors, namely, feature value (FV), relationship expectancy (RE) and professional benefits. A quantitative approach based on the survey was used to collect data from 254 academic staff. Data were analysed using structural equation modelling.

Findings

The result indicated significant differences around factors influencing both consumptive and contributive usage patterns within ESNs. These factors suggest more contributive than consumptive use.

Research limitations/implications

Future research should consider a longitudinal study focusing on the change in ESN use behaviour among academic staff and the fundamental aspects influencing this change.

Originality/value

This study extends the UTAUT model by incorporating three additional factors: FV, RE and professional benefits, to study ESN use behaviour in a higher education context. This study has significantly modified UTAUT to include the dynamic nature of ESN usage.

The impact of enterprise social media use on employee performance: a grounded theory approach

Purpose

Enterprise social media (ESM) are frequently used in enterprises for daily operation. Although many researchers have attempted to understand the antecedents and consequences of ESM use, the integrated model, boundary conditions and mechanism of the impact of ESM use on performance are still unclear. This study fill this research gap by adopting a grounded theory approach to study how ESM use affects employee performance.

Design/methodology/approach

Choosing representative cases, the authors collected interview data and analyzed the data using open coding, axial coding and selective coding.

Findings

The results showed four main categories including ESM use, work efficiency, emotional maintenance and work performance, as well as 14 sub-categories. This paper also constructs a model of the impact of ESM use on work performance. In addition, results showed that ESM use affects employees' work performance through work efficiency and emotional maintenance, and frequency of use and individual characteristics may moderate this process.

Originality/value

This study’s results contribute to the existing ESM literature by finding the integrated model, boundary conditions and mechanism of the impact of ESM use on performance. The authors also contributed to the social media literature by finding 14 sub-categories and four main categories including ESM use, work efficiency, emotional maintenance and work performance. The conclusion of this paper provides guidance and reference for the use and management of internal social media in enterprises.

Predictors of emotional distress during the COVID-19 pandemic; a Croatian study

The study aimed to assess relations between coronavirus-related psychological distress and its potentially predictive factors. An online sample of 2860 Croatian adults filled in questionnaires on socio-demographic characteristics, distress (the Depression, Anxiety and Stress Scale 21), coping (the Brief COPE), personality (the International Personality Item Pool), and social support (the Duke-UNC Functional Social Support Questionnaire) during the COVID-19 lockdown and after the capital was hit by an earthquake. Results indicated that 15.9% of the respondents experienced severe to extreme depression, 10.7% severe to extreme anxiety, and 26.2% severe to extreme stress. The hierarchical regressions analysis indicated that the considered variables explained a substantial percentage of the variance in depression (51.4%), anxiety (35.2%), and stress (45.5%). Main predictors of emotional distress were lower scores of Emotional Stability, higher scores of Agreeableness, avoidant coping, lack of active coping and perceived social support. The negative effect of the earthquake was weak. Results provide information on a broad range of potentially protective or vulnerability factors that could help identify those at risk for developing coronavirus-related psychological distress. Findings suggest that promoting active coping styles and social interactions could be preventive and potentially therapeutic in general populations.

Cyberbullying severity detection: A machine learning approach

With widespread usage of online social networks and its popularity, social networking platforms have given us incalculable opportunities than ever before, and its benefits are undeniable. Despite benefits, people may be humiliated, insulted, bullied, and harassed by anonymous users, strangers, or peers. In this study, we have proposed a cyberbullying detection framework to generate features from Twitter content by leveraging a pointwise mutual information technique. Based on these features, we developed a supervised machine learning solution for cyberbullying detection and multi-class categorization of its severity in Twitter. In the study we applied Embedding, Sentiment, and Lexicon features along with PMI-semantic orientation. Extracted features were applied with Naïve Bayes, KNN, Decision Tree, Random Forest, and Support Vector Machine algorithms. Results from experiments with our proposed framework in a multi-class setting are promising both with respect to Kappa, classifier accuracy and f-measure metrics, as well as in a binary setting. These results indicate that our proposed framework provides a feasible solution to detect cyberbullying behavior and its severity in online social networks. Finally, we compared the results of proposed and baseline features with other machine learning algorithms. Findings of the comparison indicate the significance of the proposed features in cyberbullying detection.

How to improve employee satisfaction and efficiency through different enterprise social media use

Purpose

While prior research provides interesting insights into the effect of social media use in enterprises, there is limited research on how use of different social media platforms affects employee job satisfaction and work efficiency. This study developed a research model to investigate how public and private social media platforms used for different motivations affect employee job satisfaction and work efficiency.

Design/methodology/approach

Online surveys were conducted in China, generating 453 valid responses for analysis. Structural equation modeling is performed to test the research model and hypotheses.

Findings

The results suggest that (1) public social media used for both work- and social-related motivations positively affects employee job satisfaction, while private social media only used for social-related motivations can contribute to employee job satisfaction. (2) Public and private social media used for work-related motivations can contribute to employee work efficiency, while social-related motivations for use of public and private social media and employee work efficiency are not significant. (3) In the process of social media usage influencing employee job satisfaction and work efficiency, employees of different genders show significant differences.

Originality/value

First, this paper contributes to information systems social media research by examining the joint effects of different motivations for public and private social media usage on employee job satisfaction and work efficiency in organizations. Second, it contributes to uses and gratification theory by clarifying the relationship between different motivations for enterprise social media use and its needs.

Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media

In the real world, the disclosure of private information to others often occurs after a trustworthy relationship has been established. Conversely, users of Social Network Sites (SNSs) like Facebook or Instagram often disclose large amounts of personal information prematurely to individuals which are not necessarily trustworthy. Such a low privacy-preserving behavior is often exploited by deceptive attackers with harmful intentions. Basically, deceivers approach their victims in online communities using incentives that motivate them to share their private information, and ultimately, their credentials. Since motivations, such as financial or social gain vary from individual to individual, deceivers must wisely choose their incentive strategy to mislead the users. Consequently, attacks are crafted to each victim based on their particular information-sharing motivations. This work analyses, through an online survey, those motivations and cognitive biases which are frequently exploited by deceptive attackers in SNSs. We propose thereafter some countermeasures for each of these biases to provide personalized privacy protection against deceivers.

A Bibliometric Analysis of the Health Field Regarding Social Networks and Young People

Social networks have historically been used to share information and support regarding health-related topics, and this usage has increased with the rise of online social media. Young people are high users of social media, both as passive listeners and as active contributors. This study aimed to map the trends in publications focused on social networks, health, and young people over the last 40 years. Scopus and the program VOSviewer were used to map the frequency of the publications, keywords, and clusters of researchers active in the field internationally. A structured keyword search using the Scopus database yielded 11,966 publications. The results reveal a long history of research on social networks, health, and young people. Research articles were the most common type of publication (68%), most of which described quantitative studies (82%). The main discipline represented in this literature was medicine, with 6062 documents. North American researchers dominate the field, both as authors and partners in international research collaborations. The present article adds to the literature by elucidating the growing importance of social networks in health research as a topic of study. This may help to inform future investments in public health research and surveillance using these novel data sources.

The Impact of Social Media on Learning Behavior for Sustainable Education: Evidence of Students from Selected Universities in Pakistan

In today’s world, social media is playing an indispensable role on the learning behavior of university students to achieve sustainable education. The impact of social media on sustainable education is becoming an essential and impelling factor. The world has become a global village and technology use has made it a smaller world through social media and how it is changing instruction. This original study is amongst the few to perform a focalized investigation on revealing the relationship between positive and negative characteristics of social media and the learning attitude of university students for sustainable education. However, this study aims to examine the constructive and adverse factors that impact on students’ minds and how these helped students to share positive and negative aspects with others. It is increasingly noticeable that social networking sites and their applications present enormous benefits for as well as risks to university students and their implications on students’ psychological adjustment or learning behaviors are not well understood. This study adapted the cluster sampling method, and respondents participated from five selected regions. Researchers distributed 1013 questionnaires among the targeted sample of university students with an age range of 16 to 35 years, and they collected 831 complete/valid responses. This study applied the social gratification theory to examine students’ behavior practicing social media usage. This study specifically identified 18 adversarial and constructive factors of social media from the previous literature. The findings revealed that the usage of social media in Pakistan has a negative influence on a student’s behavior as compared to positive aspects. Results may not be generalized to the entire student community as findings are specific to the specific respondents only. This study presents a relationship between antithetical and creative characteristics of social media and exhibits avenues for future studies by facilitating a better understanding of web-based social network use.

Privacy and Security Issues in Online Social Networks

The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.

Evaluation of Advertising Campaigns on Social Media Networks

As the virtual environment is constantly changing, not only users’ informational and knowledge needs but also the means and channels of communication with customers applied by organizations change. There is a noticeable trend to move more and more advertising campaigns to social media networks because of the opportunities they provide to organizations and users, which results in the ever-increasing popularity of social media networks and a number of their users. Such a transition is explained by one of the main objectives organizations have: to inform their customers in an appropriate way and receive feedback on social media networks, which is difficult when traditional advertising channels and means are applied. Since advertising campaigns on social media networks are evolving rapidly, their assessment factors and methods, which receive controversial opinions in both scientific literature and practice, change too. Researchers assess and interpret the factors that influence the effectiveness of advertising campaigns on social media networks differently. Thus, a problem arises: how should we evaluate which approach is more capable of accurately and fully reflecting and conveying reality? In this research, this problem is studied by connecting approaches of different researchers. These approaches are linked to the effectiveness assessment of advertising campaigns on social media network aspects. To achieve the objective of this study, such research methods as analysis of scientific literature, multiple criteria and expert assessment (a structured survey and an interview) were applied. During the study, out of 39 primary assessment factors, eight primary factors that influence the effectiveness of advertising campaigns on social media networks were identified: sales, content reach, traffic to website, impressions, frequency, relevance score, leads and audience growth.