Social Network Environment Research Articles

The status quo and influencing factors of intrinsic capacity among community-dwelling older adults from the perspective of Ecological Systems Theory: A cross-sectional study

BackgroundAs intrinsic capacity (IC) declines, older adults are at a significantly increased risk of frailty, care dependency, and death. Currently, the research on IC among older adults in China was still insufficient. We aimed to identify the status quo and influencing factors among community-dwelling older adults in China and explore the relationship between IC, external environment, and social network.MethodsA convenience sampling method was used to collect 312 older people from May 2023 to February 2024 in five communities in Chengdu, Sichuan Province. Data were collected using the general information questionnaire, Integrated Care of the Elderly (ICOPE) screening tool, World Health Organization Quality of live scale (WHOQOL-100), and Social Network Scale (LSNS-6).ResultsThe IC score among Chinese community-dwelling older adults was 3.39 ± 1.60, and the prevalence of IC decline was 86.9%. Marital status, age, number of chronic diseases, social network, and external environment were influencing factors of IC, which explained 35.7% of the total variance. External environment and social network were positively correlated with IC.ConclusionsChinese community-dwelling older adults had low IC scores and a high prevalence of IC decline. The government should focus on IC for older adults, especially those who are older, not married or widowed, and suffering from multiple chronic diseases. In addition, the richer the external resources available to older adults, the more social support they received, and the better the IC. These findings could provide a theoretical basis for managing and improving IC in older adults.

The Impact of Posting and Viewing Selfies on Social Media on Self-Identity: A Case Study of xiaohongshu

The emergence of new social media platforms has significantly influenced adolescent mental health through their engagement in selfie-related behaviours. This paper uses xiaohongshu as a research platform to explore the impact of users’ selfie-related behaviour on their body satisfaction and self-identity on social media. This study employed a questionnaire-based survey to examine 60 xiaohongshu users, aged 19-59, utilizing the selfie-posting frequency scale, self-viewing scale, verbal commentary on physical appearance Scale, body Image states scale, and body surveillance subscale. The results show that selfie editing and posting, selfie viewing, and positive appearance-related commentary positively affect body satisfaction, while negative appearance-related commentary negatively affect body satisfaction. There is no statistically significant association identified between body satisfaction and self-objectification. Adolescents’ psychological issues are influenced, in part, by their selfie-related activities within social networking environments. However, a mindful and rational engagement with these platforms can foster self-identity and contribute to the positive development of youth mental health.

Influence of social capital on happiness of multicultural family: A cross-sectional study using the 2019 Korea community health survey

This study aims to identify factors related to the impact of social capital on happiness among multicultural families using the 2019 Community Health Survey, which represents the South Korean population. The study utilized data from the 2019 Korea Community Health Survey, and the study participants, aged 20 years or older, included 3524 members of multicultural families from a total of 229,099 adult households. The study found a significant difference in happiness scores across different age groups (t = 57.00, p < 0.01). Based on the median value of happiness, significant relationships were found with the independent variables: Physical Environment of Trust (t = −5.13, p < 0.001), Social Networks (t = −5.51, p < 0.001), and Social Participation (t = −5.47, p < 0.001). Happiness was found to have a positive correlation with the Physical Environment of Trust (r = 0.12, p < .001), Social Participation (r = 0.11, p < 0.001), and Social Network (r = 0.13, p ≤ 0.001). In contrast, Age (r = −0.13, p ≤ 0.001) and Stress (r = −0.14, p ≤ 0.001) showed negative correlations with happiness (r = 0.57, p < 0.001). The analysis identified a positive community physical environment (t = 3.85, p < 0.01), increased social networks (t = 4.27, p < 0.01), and higher social participation (t = 6.88, p < 0.01) as significant predictors of happiness. This model suggests that the explanation power is 15%, which is statistically significant (R2 = 0.15, F = 57.72, p < 0.001). This study highlights the influence of social capital on the happiness of multicultural families living in Korea. Given the increasing number of multicultural families in the country, strategic interventions aimed at enhancing social networks and participation are necessary to promote their happiness.

Sound in mode on: how sound stimuli influence customer engagement?

AbstractThe objectives of this research are as follows: (i) to study whether the presence of sound stimuli influences customer engagement; (ii) to assess this effect on different dimensions of customer engagement (sensory experience, approach-avoidance response, and emotional response); and (iii) to study whether product type and customer involvement moderate the effect of sound on customer engagement. This research analyzes the effect of two different sound stimuli for two different product types on two digital channels. The experimental design for Study 1 is a 2 sound (sound associated with the product vs. no sound) × 2 product type (hedonic vs. utilitarian) displayed in a social network (Instagram) environment. The experimental design for Study 2 is a 2 sound (voiceover vs. no sound) × 2 product type (hedonic vs. utilitarian) displayed in a blog. Both studies additionally incorporate measured variables, with a particular focus on customer involvement (low and high). A total of 512 participants interacted with a condition and then completed a questionnaire. The presence of sound increases customer engagement in the sensory experience and approaching response. The interaction of sound (voice-over) and the hedonic product positively influences the emotional response, and customer involvement negatively moderates the influence of sound on the sensory experience.

A Systematic Review on Extended Reality-Mediated Multi-User Social Engagement

The metaverse represents a post-reality universe that seamlessly merges physical reality with digital virtuality. It provides a continuous and immersive social networking environment, enabling multi-user engagement and interaction through Extended Reality (XR) technologies, which include Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). As a novel solution distinct from traditional methods such as mobile-based applications, the technical affordance of XR technologies in shaping multi-user social experiences remains a complex, multifaceted, and multivariate issue that has not yet been thoroughly explored. Additionally, there is a notable absence of mature frameworks and guidelines for designing and developing these multi-user socio-technical systems. Enhancing multi-user social engagement through these technologies remains a significant research challenge. This systematic review aims to address this gap by establishing an analytical framework guided by the PRISMA protocol. It analyzes 88 studies from various disciplines, including computer science, social science, psychology, and the arts, to define the mechanisms and effectiveness of XR technologies in multi-user social engagement. Quantitative methods such as descriptive statistics, correlation statistics, and text mining are used to examine the manifestation of mechanisms, potential system factors, and their effectiveness. Meanwhile, qualitative case studies identify specific measures by which system factors enhance multi-user social engagement. The study provides a pioneering framework for theoretical research and offers practical insights for developing cross-spatiotemporal co-present activities in the metaverse. It also promotes critical reflection on the evolving relationship between humans and this emerging digital universe.

DIGITAL COMPETENCE OF STUDENTS AS A FACTOR OF THE FORMATION OF SOCIO-POLITICAL ATTITUDES

In the presented article, the authors consider the political and ideological intentions of the student youth associated with the activation of the network environment in order to predict the socio-political sustainability of civil society and assess possible risks. The process of political socialization of young people has undergone serious transformations in recent years: with the advent of new technologies, the forms of political activity and interaction have changed, the geopolitical situation has caused the activation of socio-political and patriotic movements. This led to a gradual transition even of the early stages of political socialization from a family environment to a social network environment. The changes also affected the processes of formation of civic culture, which are closely related to political socialization. The picture of the future of Russian society depends on how this has affected the specifics of the political worldview of students who are deeply immersed in the online environment. Based on the data of the All-Russian sociological research, an assessment was made of the dependence of the vector of socio-political attitudes of student youth on the level of their digital competence and network activity. As the analysis showed, students with increased network activity and developed digital competencies also have a great potential for dissatisfaction compared to a group of less digitalized students. Given the demand for labor personnel with skills to work in the digital environment, there is a need to take steps to reduce possible risks and channel them into positive forms of manifestation, since the current positioning of student youth can contribute to the growth of tension in society.

Improving automatic cyberbullying detection in social network environments by fine-tuning a pre-trained sentence transformer language model

The internet use among children and adolescents has increased massively recently. This situation has promoted harmful situations such as cyberbullying, which is becoming a worldwide problem that entails serious consequences for well-being. The detection of these attitudes is essential to prevent and act accordingly. Groundbreaking techniques based on deep learning, like pre-trained language models, have achieved state-of-the-art results in many downstream Natural Language Processing tasks. This paper presents a simple but effective approach to improve the detection of cyberbullying situations by fine-tuning a pre-trained sentence transformer language model. We experimented on three datasets, and the results surpassed the state-of-the-art results. The approach could help prevent cyberbullying, filter those messages, and detect those children involved in the situation, providing opportunities to develop intervention programs to address this problem.

A multi-period intuitionistic fuzzy consensus reaching model for group decision making problem in social network

A new intuitionistic fuzzy consensus reaching model is developed with multi-period public opinions and expert evaluation values in social network environment. First, the public opinions are obtained by using the crawler software and sentiment analysis technology is used to transform public opinions into intuitionistic fuzzy decision matrix in each period. Attribute weights are calculated by using the time attenuation factor and changes in public opinion. Second, the social trust relationship is modeled and incomplete social trust relationships are completed by using Archimedean t-norm. The expert weights are calculated by using the dynamic trust degree and similarity degree. Third, a consensus framework is proposed for multiple-period decision making problem, which coordinates conflicts between experts through dual feedback paths. The collective opinion scores are calculated by using weights of periods and attribute weights obtained from the word frequency of public opinions. The tourism attraction recommendation method is used to illustrate the proposed method.

The influence of homophily and social identity on eWOM in streaming consumption behaviour

Purpose The purpose of this paper is to identify the influence of homophily and social identity in eWOM adoption and influence on music consumption in streaming platforms. The study also proposes a framework for eWOM influence on product consumption. Design/methodology/approach Data were collected through an electronic questionnaire with a total of 524 valid responses. A partial least square methodology was used to approach the data analysis. Findings The findings indicate that both homophily and social identity have an influence on eWOM effect. Additionally, homophily shows influence on social identity being an important value to the total influence. It is also confirmed how eWOM has direct influence on music consumption. Practical implications Social information of consumers becomes more relevant than ever, as the results contribute to highlight its importance as a message adoption influencer and product consumption driver. Originality/value This study contributes to social communication theory by identifying homophily and social identity as valuable assets during eWOM generation. The research brings a new angle to social identity theory in the social network environment and influences eWOM adoption in music streaming consumption.

LATE MODERN ANXIETY AND DIGITAL JIHADIST ALTERNATIVE IN ANNA ERELLE’S IN THE SKIN OF A JIHADIST AND TIMUR BEKMAMBETOV’S PROFILE

For almost a decade, ISIS has held the status of the West’s radical other, its symbolic and real challenge to the western idea of modernity becoming ever more prominent and threatening with a growing accessibility of online propaganda content and recruitment via social media platforms in a largely unregulated social networking environment. In that context, the paper discusses Anna Erelle’s book In the Skin of a Jihadist and its film adaptation Profile as two distinct but complementary visions of the West and its other. My argument is that Timur Bekmambetov’s adaptation, as a Baumanesque critical reading of the West’s late modernity, is supplemental to the original text and its liberal views of jihadist otherness. Profile thus views the West and ISIS as two universalist visions of the world so that by facing the dangerous alterity on the computer screen, the West should not only see the morally inferior enemy to be exposed, transformed or eventually defeated but the reflection of its own late modern failures, disappointments and frustrations.

An Improved Laplacian Gravity Centrality-Based Consensus Method for Social Network Group Decision-Making with Incomplete ELICIT Information

With the advancement of information technology, social media has become increasingly prevalent. The complex networks of social relationships among decision-makers (DMs) have given rise to the problem of social network group decision-making (SNGDM), which has garnered considerable attention in recent years. However, most existing consensus-reaching methods in SNGDM only consider local network information when determining the influence of DMs within the social network. This approach fails to adequately reflect the crucial role of key DMs in regulating information propagation during the consensus-reaching process. Additionally, the partial absence of linguistic evaluations in the decision-making problems also poses obstacles to identifying the optimal alternative. Therefore, this paper proposes an improved Laplacian gravity centrality-based consensus method that can effectively handle incomplete decision information in social network environments. First, the extended comparative linguistic expressions with symbolic translation (ELICIT) are utilized to describe DMs’ linguistic evaluations and construct the incomplete decision matrix. Second, the improved Laplacian gravity centrality (ILGC) is proposed to quantify the influence of DMs in the social network by considering local and global topological structures. Based on the ILGC measure, we develop a trust-driven consensus-reaching model to enhance group consensus, which can better simulate opinion interactions in real-world situations. Lastly, we apply the proposed method to a smart city evaluation problem. The results show that our method can more reasonably handle incomplete linguistic evaluations, more comprehensively capture the influence of DMs, and more effectively improve group consensus.

Deep Learning Multimodal Methods to Detect Fake News

Fake news, characterized by false information disseminated intentionally with malicious intent, has become a critical societal issue. Its impact spans political, economic, and social domains, fueled by the rapid proliferation of digital communication channels, particularly social media. To combat this menace, researchers have turned to automated mechanisms for detection, leveraging machine learning algorithms and curated datasets. In this exploratory research, the landscape of machine learning algorithms is employed in identifying fake news. Notably, the research focus on algorithms such as the Bidirectional Encoder Representations from Transformers (BERT) and Convolutional Neural Network (CNN) respectively. However, most of these studies rely on controlled datasets lacking real-time information from social networks—the very platforms where disinformation thrives. The findings underscore the need for research in social network environments, where fake news spreads most prolifically. Additionally, future investigations should extend beyond political news, considering hybrid methods that combine NLP and deep learning techniques. This study serves as a valuable resource for researchers, practitioners, and policymakers seeking insights into the evolving landscape of the ability to combat fake news effectively.

La evolución prospectiva de las redes sociales desde la perspectiva de la neurofenomenología

The purpose of the present article is to identify neurophenomenological aspects that influence the future development of social networks and to develop a corresponding concept of regulatory policy. The following methods are used in the article: collection and analysis of information, modeling of a conditional social network, systematization and separation of neurophenomenological factors, determination of functional dependencies, development of analytical conclusions and proposals. It was established that instigators and a favorable environment of social networks form prerequisites for the spread of negative information campaigns (conditional attacks). At the same time, it is mathematically proven that with minimal development of resistance to information attacks among users of social media platforms, the potential for stabilizing the information environment of social networks and promoting sustainable advancement of natural society was determined. Based on the research results, it was determined that fostering critical thinking skills, maintaining information stability, and practicing sound personal digital hygiene among users are key factors in upholding the overall stability of social networks. Additionally, these practices promote sustainable development of a psychologically healthy community. Additional investigations are focused on elaborating the notion of regulatory policy to facilitate the prospective advancement of social networks.

Crowdsourcing as an Element of Strategic-Operational Intelligence. How NATO Used it and Changed the Game

The article focuses on the concept of crowdsourcing in the social networking environment as a new phenomenon involving civilians in the intelligence process, enabling the use of their intelligence potential during armed conflict. Crowdsourcing of the civilian population is introduced by the example of NATO intervention during the first civil war in Libya. The article presents its use during the intelligence process at the strategic-operational level of command and control of the armed forces. It establishes its possible definition as a collection method of the intelligence process, and as a collection method which is disjunctively separable from similar intelligence collection methods.

New consensus reaching process with minimum adjustment and feedback mechanism for large-scale group decision making problems under social trust networks

Large-scale group decision making problems in social networks environment have become an important research topic in decision making science. In this paper, we propose a new consensus reaching process with minimum adjustment and feedback mechanism considering public opinions for large-scale group decision making problems under social trust networks. The trust propagation operator based on Archimedean t-norm is used to calculate incomplete trust values first. The fast unfolding algorithm is used to divide experts into subgroups. The opinion evolution model is presented to calculate experts’ weights based on dynamic trust values and expert influence. Public opinions are used to determine consensus thresholds of attributes. A dual-path adjustment model is developed for group consensus in social network. Divide experts’ evaluation values into three different types: ‘conflict behavior’, ‘tolerant behavior’, ‘trust behavior’. Minimum cost adjustment models have been developed considering adjustment directions for the ‘conflict behavior’ and interactive path is activated for the ‘tolerant behavior’. The drugs selection from E-commerce platform for therapy of influenza at home is used to illustrate the new method and comparisons have also been conducted.

A Study on the Endogenous Dynamics of Rural Tourism Green Development in Yunnan Under the Background of Carbon Peaking and Carbon Neutrality

Yunnan Province has abundant rural tourism resources, however, the vigorous development of rural tourism in Yunnan is accompanied by ecological safety risks. Severe tourism pollution restricts the sustainable development of rural tourism in Yunnan. 'Greening' has become the main way for the sustainable development of rural tourism in Yunnan under the background of 'dual carbon'. Based on the 'dual carbon' background and combining the perspectives of 'driving factors for green development' and 'green behavior', this paper deeply analyzes the current situation of 'greening' in rural tourism communities in Yunnan during the process of rural tourism development. Combined with the social network relationships of rural tourism green development communities in Yunnan, the original model is modified. On the basis of social exchange theory and group dynamics, a relationship model between social network environment and participation behavior mechanism is formed. Through this model, the endogenous driving force of rural tourism community residents to participate in green development is explored, and methods and paths to motivate the driving force for green development are sought. Ultimately, it achieves that residents can participate, are willing to participate, and have the ability to participate in all aspects of the green development of rural tourism in Yunnan, promoting the sustainable development of rural tourism and communities in Yunnan.

Research on English Reading Motivation and Its Influencing Factors in Social Network Environment

Abstract Reading plays a pivotal role in English language acquisition, with the motivation for reading critically influencing both readers’ attitudes and students’ competencies. This study develops an English reading model predicated on a social network-enabled reading mechanism and investigates the impact of English reading motivation through the lens of social network embedding. The research focuses on English readers’ reading motivation, employing five scales: structural embeddedness, relational embeddedness, reading goals, reading interest, and reading motivation. Data were analyzed using factor analysis and structural equation modeling to elucidate the influence mechanism of English reading motivation from the perspective of social network embeddedness. The results indicate that the path coefficients for the impact of structural and relational embedding within social networks on English reading goals are statistically significant at the 0.05 level, with values of 0.152 and 0.133, respectively. Furthermore, the path coefficient linking English reading goals to English reading interest is 0.335, and the coefficient from reading interest to reading motivation is 0.542, both of which are significant at the 0.001 level. The findings suggest that engaging in English reading activities through social networks can substantially boost readers’ interest in reading, thereby facilitating the achievement of their reading goals.

The Main Mechanisms and Characteristics of the Impart of Social Network on Consumer Behavior

Based on the contemporary social network environment, this paper discusses the practical significance of its impact on consumer behavior, and influencers as the main component of social network, this paper mainly take the mega-influencers and small influencers as the research object, through the analysis of the characteristics and application of the small-world network social network model to the micro-influencers, it is concluded that the influence of the mega- influencers on consumer decision-making is very important, but micro-influencers also play a subtle role in consumer behavior, which can be perceived as inseparable. At the same time, the application of small-world network model in economic management is a relatively new research field, which brings new ideas for economic management research and provides an effective technical tool. For example, this paper studies a new model of marketing through small-world network community, and innovates marketing strategy from two aspects of dominance and suggestion according to the different characteristics of mega-influencers and micro-influencers.

Be A Part or Be Apart? The Consumer Utility and Social Networks: An Application of Agent-Based Modeling

<p>本文探討社會網絡對消費者效用的影響，以代理人基模擬消費者於不同網絡型態的互動，重構Jager（2000）的模型並使用二維的效用函數。決策時間代表涉入程度，刻畫所有消費情境。模擬不同型態的社會網絡、密度、認知類型、總人數對個別消費效用的影響。並將效用函數拆解成個人與社會部份以捕捉影響主因。結果表明，任何社會網絡中，網絡愈疏散，消費者所獲得的效用愈高，原因為社會部份的效用稀釋減少；社群影響力下降，非純粹個人效用提升。檢視市場參與人數與社會網絡密度對消費者效用的影響後發現，若消費者身處適切的社會網絡，消費者效用提升。意即，較多的消費者於較疏散的網絡或較少的消費者於較密集的網絡，這二種社群環境對新進廠商相對有利，既存廠商優勢不明顯。</p> <p> </p><p>This study aims to examine the effect of social networks on consumer utility. An agent-based model was employed to simulate the interaction among consumers in different social network types. Jager’s (2000) agent-based model was reconstructed, and a two-dimensional utility function was introduced, considering decision-making time (product involvement) and incorporating all types of consumption scenarios. The goal was to simulate the impact of different types of social networks, social network densities, consumer cognitive types, and the total number of consumers on individual consumer utility. The utility function was decomposed into individual and social components to identify the primary factors influencing consumer utility. Research results indicate that in any social network, as the network becomes more dispersed, consumer utility increases. The reason for this is that the decline in social influence causes the social aspect of utility to be diluted and reduced, rather than a pure increase in individual utility. After examining the impact of the number of market participants and the density of social networks on consumer utility, it was found that if consumers are in an appropriate social network, consumer utility increases. This refers to situations where there are more consumers in a dispersed network or fewer consumers in a dense network. In these two types of social network environments, it is relatively advantageous for new entrants, but this advantage is not as evident for existing vendors.</p> <p> </p>

Effect of three-stage cascade of opinion dynamics models in coupled networks

Information technology has contributed to the spread of public opinion across multiple coupled networks, and the scope of information spread has expanded. Owing to the impact of personal subjective cognition, information attenuation occurs during the process of opinion transmission in social networks, particularly in multi-layer social networks. In this paper, we construct a three-stage cascade opinion dynamics model, based on the Hegselmann–Krause (HK) model, to analyze the effect of information dissemination attenuation on group decision behavior in coupled social networks. This model considers three-stage cascade information transmission and two competitive opinion leader subgroups in two different social network environments, and can describe a public opinion dissemination environment more closely. The results show that the combination of the network structure and the level of trust of the public can effectively guide the spread of public opinion, which provides valuable insights into the role of social media in shaping public opinion and its impact on various fields. These findings can be useful for advertisers and policymakers to control public opinion and reach a consensus in group decision-making.