Social Network Interactions Research Articles

How does consumer-to-consumer community interaction affect brand trust?

This article seeks to study how the extensive usage of social networking sites (SNSs) and interaction in consumer-to-consumer (C2C) communities influence brand trust. Social networking sites have impacted internet commerce in a technologically advanced era; it connects global users. Social media ads have changed our thinking; new market trends are reshaping the business industry. This study empirically investigates a model based on media richness theory and social capital theory. Using data collected from users who conducted transactions on these sites, a theoretical model was developed to analyze the inspirations behind trust. The results show that Instagram’s media-rich platform enhances social capital and a sense of virtual community between its members, affecting trust. Instagram usage intensity does not immediately affect brand trust, but it has an indirect effect; community trust also positively influences brand trust. This study defines the role of a sense of virtual community (SOVC) and social capital (SC) in C2C communities only. This study delivers insights to managers on how to increase brand trust via SNSs. Prior studies on social commerce do not apply to C2C communities on social media platforms, especially Instagram. This study presents a novel standpoint of social capital and media richness structures as precursors of brand trust in C2C communities.

Social networks, heterogeneity, and adoption of technologies: Evidence from India

This study examines the role of caste-based affiliations in the smallholders’ social network interactions for adoption choices. In particular, whether lower-caste, namely Scheduled Castes/Scheduled Tribes, farmers rely more on social networks for information than their counterparts. We further explore whether social network effects are more pronounced when farmers interact within their caste than otherwise. Finally, the study tests whether the effects (intra-caste and inter-caste) vary by caste—SC/ST versus non-SC/ST farmers. The study uses a survey of 478 mustard farmers in Rajasthan, India. Econometric concerns related to unobserved heterogeneity are addressed by employing specifications with village fixed effects and a series of robustness tests. Simultaneity concerns are addressed by analyzing the social network effects in a dynamic adoption framework. Results show that the adoption choices regarding hybrid mustard seeds are more pronounced for the lower-caste farmers than for their counterparts. Findings reveal that social network effects are significant in intra-caste but not in the case of inter-caste. Finally, the result shows that the likelihood of accepting advice in technology adoption is higher when SC/ST farmers interact with non-SC/ST network members than when non-SC/ST farmers interact with SC/ST network members.

Retraction Note: Innovation and improvement of visual communication design of mobile app based on social network interaction interface design

Retraction Note: Innovation and improvement of visual communication design of mobile app based on social network interaction interface design

A theory of infrastructural rhetoric

This article theorizes infrastructures and their components as rhetorical objects for analysis and persuasive use. Though the term infrastructure has been applied broadly to several studies in the social sciences, writing, technical communication, and technology studies, infrastructures have yet to be systematically theorized as an active persuasive consideration for those engaging in communicative practice. This article makes a case for a taxonomic theoretical understanding and conceptualization of infrastructure that may lead to new methodological developments in future research. This theory builds from theories of infrastructures as relational networks of social interaction around objects. The article aims to assist the persuasive endeavors of those engaged in communicative practice in infrastructural settings.

Relationships between changing communication networks and changing perceptions of psychological safety in a team science setting: Analysis with actor-oriented social network models.

A growing evidence base suggests that complex healthcare problems are optimally tackled through cross-disciplinary collaboration that draws upon the expertise of diverse researchers. Yet, the influences and processes underlying effective teamwork among independent researchers are not well-understood, making it difficult to fully optimize the collaborative process. To address this gap in knowledge, we used the annual NIH mHealth Training Institutes as a testbed to develop stochastic actor-oriented models that explore the communicative interactions and psychological changes of its disciplinarily and geographically diverse participants. The models help investigate social influence and social selection effects to understand whether and how social network interactions influence perceptions of team psychological safety during the institute and how they may sway communications between participants. We found a degree of social selection effects: in particular years, scholars were likely to choose to communicate with those who had more dissimilar levels of psychological safety. We found evidence of social influence, in particular, from scholars with lower psychological safety levels and from scholars with reciprocated communications, although the sizes and directions of the social influences somewhat varied across years. The current study demonstrated the utility of stochastic actor-oriented models in understanding the team science process which can inform team science initiatives. The study results can contribute to theory-building about team science which acknowledges the importance of social influence and selection.

Land Use Identification through Social Network Interaction

The Internet generates large volumes of data at a high rate, in particular, posts on social networks. Although social network data have numerous semantic adulterations and are not intended to be a source of geo-spatial information, in the text of posts we find pieces of important information about how people relate to their environment, which can be used to identify interesting aspects of how human beings interact with portions of land based on their activities. This research proposes a methodology for the identification of land uses using Natural Language Processing (NLP) from the contents of the popular social network Twitter. It will be approached by identifying keywords with linguistic patterns from the text, and the geographical coordinates associated with the publication. Context-specific innovations are introduced to deal with data across South America and, in particular, in the city of Arequipa, Peru. The objective is to identify the five main land uses: residential, commercial, institutional-governmental, industrial-offices and unbuilt land. Within the framework of urban planning and sustainable urban management, the methodology contributes to the optimization of the identification techniques applied for the updating of land use cadastres, since the results achieved an accuracy of about 90%, which motivates its application in the real context. In addition, it would allow the identification of land use categories at a more detailed level, in situations such as a complex/mixed distribution building based on the amount of data collected. Finally, the methodology makes land use information available in a more up-to-date fashion and, above all, avoids the high economic cost of the non-automatic production of land use maps for cities, mostly in developing countries.

How Do Non-Agricultural Employment and Regional Selection Affect Farmers' Domestic Sewage Discharge Behavior? Empirical Evidence from Rural China.

In many countries, along with rising rural labor transfer, the problem of rural domestic sewage discharge is becoming increasingly serious due to labor shortages in the villages. It is urgent to solve the environment pollution and health problems of residents which is caused by the massive discharge of domestic sewage in rural areas. Based on the survey data collected from Nanjing Agricultural University in 2020, this paper employs the ordered probit model and the CMP method, to empirically test the impact of non-agricultural employment and regional choice on farmers’ domestic sewage discharge behavior and the moderating effect of environmental cognition and the social network. The results show that: (1) There is a significantly positive correlation between non-agricultural employment and farmers’ sewage treatment behavior. (2) Environmental cognition significantly improves the participation of urban non-agricultural employment farmers in sewage treatment, and the social network has a significant role in promoting the adoption of sewage treatment behavior of local non-agricultural employment farmers. (3) Further heterogeneity analysis results show that the inhibitory effect of urban non-agricultural employment on random sewage discharge is more pronounced than that of local non-agricultural employment. Therefore, in order to effectively solve the problem of rural domestic sewage discharge, it is necessary to actively guide the sewage discharge behavior of non-agricultural employment households, strengthen the social network interaction within the village, and increase the publicity for sewage discharge knowledge.

Uso de redes sociales para la prevención del abuso de sustancias durante la cuarentena por COVID-19

Introduction: the COVID-19 pandemic has increased exposure to stressors, which can lead to an increase in drug use as a coping mechanism. Due to the confinement, social networks represent an important means for dissemination of clear, reliable information on ways to prevent drug abuse, and the consequences of said abuse in the general population and among those most vulnerable to acquiring the virus and developing the most serious symptomatology of COVID-19. Objective: to disseminate scientific evidence-based information on alcohol, tobacco and drug use in the context of the COVID-19 contingency in Mexico. Method: we developed messages accompanied by images through the analysis of information on drug use and COVID-19 from a government institution. The messages were disseminated on two social networks to promote healthy behaviors, to increase the knowledge about risks associated to COVID-19 and drug use, and to encourage reflection. Results: the messages reached a total of 851,622 people and had up to 35,819 interactions on Facebook and Twitter. Discussion and conclusions: knowing the interactions in social networks allows to strategically incorporate specific information for different populations at risk. Having information from an institutional social network is a tool to prevent the dissemination of false or inaccurate information.

Who should i talk to? - informal workplace learning among teachers in police education

ABSTRACT Previous research has shown that teachers’ informal learning in social networks is of great importance for their professional development. Participation in social networks is often characterised by knowledge exchange between employees with the aim of dealing with work-related challenges or improving the work practice. In this study, attention was focused on teachers at a Swedish police education unit and their participation in work-related social networks. The findings were based on two data collections, logbooks of social networking interactions and follow-up interviews with 23 teachers. The purpose was to explore who they talked to, for what purpose and what means of communication they used, and the analysis included mapping of their interactions in social networks and a qualitative analysis of their narratives. Overall, the study shows that the teachers’ participation in social networks was extensive and valuable for their professional development as teachers. Furthermore, the analysis shows that the teachers’ interactions in social networks are usually intentional and based on knowledge needs related to pedagogical aspects of teaching, that the composition of course content and teaching teams can affect teachers’ readiness to participate in several different networks and that the type of knowledge need affects which means of communication are used.

Incentive strategy models of household waste separation based on cost uncertainties: A perspective of social networks

Waste management has become a serious problem in China, with households generating an increasing amount of waste. To tackle this problem, many city administrations have implemented regulations on household waste separation and are stepping up efforts to improve awareness. Moreover, the existence of individual interactions in social networks makes the cost of raising awareness highly uncertain. Therefore, this paper aims to describe the individual interactions based on dynamics of opinion spread method and build the incentive strategy model that is extended to three robust incentive strategy models based on various uncertain sets by robust optimization: Box-SO Model, Ellipsoid-SO Model and Box-Ellipsoid-SO Model. The simulation results indicated that a higher uncertain level parameter or a lower interaction threshold leads to lower public awareness, in which the Ellipsoid-SO Model has the best robustness with sacrificing 7.96% of the total awareness value, but the Box-Ellipsoid-SO Model loses 24.24%. Meanwhile, cost constraint has a direct effect on public awareness, and people with a high frequency of social interactions are key to improving public awareness of household waste separation. Additionally, the results have several management implications that are conducive to improving public awareness and behavior of household waste separation in social networks: (1) The fundamental premise of improving public waste separation behavior is to stimulate awareness; (2) Small-scale activities are more efficient than large-scale activities in improving pro-environment opinion; (3) Given the existence of opinion leaders, propaganda for residents should be pertinently targeted. • Social interactions of awareness on household waste separation are studied. • Incentive models with cost uncertainties are proposed to improve awareness. • Awareness values of robust models are lower than basic model due to uncertainty. • Ellipsoid-SO Model has best robustness with losing 7.96% of the total awareness. • Small-scale activities are more efficient to improve public awareness.

The Emergence of Interorganizational Networks: A Pluralistic Perspective

Despite the recent attention of management scholars towards the pluralistic and multilevel nature of interorganizational relationships and networks, we still have a limited account of the initial moment of network emergence and its impact on subsequent network evolution. I seek to shed some light on this point through a reinterpretation of a classic model of network formation to investigate the emergence of an interorganizational network from a pluralistic point of view: the existence of an underlying network of social interactions influences the genesis of a business network. Results of the model indicate that an underlying social level of interaction can play an enabling but also a detrimental role, in terms of architectures, dynamics and performance of the business network. Positive social exchanges favor multiplexity, while previous negative connections impede it, making it more difficult to obtain inclusive architectures. Social relationships mediate environmental conditions, and influence trajectories of network evolution in both a serendipitous and a path-dependent way, posing challenges to the governance of the network. The impact of social relationships on business ones is particularly relevant in terms of the interorganizational network performance, which is complexly shaped by both the density of the social ties and their strength, with a complementary effect at the network level but a substitutive effect at the ego level.

Analyzing the extremization of opinions in a general framework of bounded confidence and repulsion

In the bounded confidence framework, agents’ opinions evolve as a result of interactions with other agents having similar opinions. Thus, consensus or fragmentation of opinions can be reached, but not extremization (the evolution of opinions towards an extreme value). In contrast, when repulsion mechanisms are at work, agents with distant opinions interact and repel each other, leading to extremization. This work proposes a general opinion dynamics framework of bounded confidence and repulsion, which includes social network interactions and agent-independent time-varying rationality. We extensively analyze the performance of our model to show that the degree of extremization among a population can be controlled by the repulsion rule, and social networks promote extreme opinions. Agent-based rationality and time-varying adaptation also bear a strong impact on opinion dynamics. The high accuracy of our model is determined in a real-world social network well referenced in the literature, the Zachary Karate Club (with a known ground truth). Finally, we use our model to analyze the extremization of opinions in a real-world scenario, in Spain: a marketing action for the Netflix series “Narcos”.

Role of Law and Judiciary in Social Transformation in India: A Need for a Changing Society

Any deviation from the accepted or established way of life is referred to as social transformation. The phrase ‘social change’ describes alterations to society as a whole. According to Maclver, society is a "network of social interactions." These social interactions alter as a result of social change. Law and social transformation are two very different ideas that place a strong emphasis on social problem studies, changes in those problems, and their resolution through judicial and legislative processes. Following the 1950 implementation of the Indian Constitution, India became a "Republic" and a country with a federal system. Multiculturalism is more evident than it used to be in this country, which has several states segregated according to language and culture. The Constitution set the stage for the ‘Rule of Law,’ effective government, and multiculturalism, yet reflected the will of the populace. According to the adage “Law Changes Society,” society must adapt to the law's requirements. When an anomaly occurs, it is taken before the judiciary, which then applies the principle of the rule of law to alter the current practice of law. Law has historically been seen as a vehicle for enacting social change. Through a vibrant judicial system and innovative jurisprudence that actively put both historical and contemporary wrongs to right, legal justice has gradually paved the path for social justice. While there are many tools available for bringing about change and transformation in our society for the law, none of them can be regarded as the most efficient and secure technique for the transition, as this article seeks to highlight.

The use of video essays and podcasts to enhance creativity and critical thinking in engineering

The current demands of the labor market demand a new compendium of skills from engineering graduates. To develop skills at a more complex level, this study analyzed the use of second-generation Video Essays and Podcasts to improve soft skills. The characteristics of students belonging to Generation Z as digital natives were considered and digital platforms were adapted for interaction in social networks to enhance critical thinking and creativity (Criticality). Active learning experiences in different engineering programs were analyzed using the 4-group Solomon methodology with a quantitative design and different assessment instruments were used for Pre-Tests and Post-Tests, including various fluency and originality tests, as well as answering articulation ability tests. and modified VALUE rubrics from the Association of American Colleges and Universities (AAC&U). Our results clearly suggest that the use of these two tools substantially improves understanding of scientific concepts in engineering subjects, a greater ability to develop increasingly in-demand skill sets, and a greater awareness of creative thinking competence.

Modeling Information Diffusion With Sequential Interactive Hypergraphs

In online social networks, numerous users generate and distribute tremendous content simultaneously, and how information spreads in online society has attracted critical attention. Recent studies introduce deep learning to help mine the complex diffusion pattern and forecast the diffusion trend. However, there are two limitations of the state-of-art methods. On the one hand, existing models only focus on the internal influence within the diffusion flow but ignore the external influence from the dissemination of other contents. On the other hand, the dynamics of user interest are barely considered, while the changes of user preference for contents also have a considerable impact on future diffusion. To address these issues, we introduce the hypergraph structure and a sequential framework to model complex interactions in social networks. Then, we propose dual-channel hypergraph neural networks to tackle the diffusion prediction problem, denoted by HyperINF. Specifically, in the user channel, we build sequential user interactive hypergraphs and learn the dynamic user representation, and in the diffusion channel, we construct a diffusion interactive graph to capture the cross-diffusion relation. At last, we consider the social relation to help make the prediction. Experimental results on three datasets suggest the effectiveness and practicability of the proposed framework.

Using Minecraft as an educational tool for supporting collaboration as a 21st century skill

Collaboration is an important 21st century skill, and there is an increasing interest in computer-supported collaborative learning (CSCL) in teaching and learning practices regarding the necessary knowledge and skills for 21st century learners. However, solutions are still lacking concerning how to enable learners to collaborate when working with a specific subject. This study developed and tested a learning design using Minecraft as an educational tool in math classes in higher education over a 2-year period. The research questions are: 1) How can Minecraft be used as an educational tool for learning subject-specific skills, and what are the implications for the development of 21st century skills? 2) How can social network analysis (SNA) and interaction analysis (IA) be used as a research methodology for analyzing the use of Minecraft as an educational tool for learning subject-specific skills? Data was analyzed using a mixed-methods approach, in which both a quantitative perspective through SNA and a qualitative perspective through IA were employed. Findings of the study: 1) suggested that using Minecraft for learning a subject-specific skill triggered collaborative learning processes, 2) facilitated the development of 21st century skills in math classes, and 3) combining SNA and IA as a research methodology for analyzing the use of Minecraft for learning subject-specific skills. These findings serve as a stepping stone for teachers and researchers to create learning designs that use a digital educational tool to facilitate collaborative learning and advance the literature on CSCL and educational practice.

Fair Competition for Business in the Field of Information and Communication Technologies in the Era of "Postcontemporary Society" Economy

This article examines the fairness of business competition in the field of information and communication technologies. In the era of "postcontemporary society" economy, the dominant factor of development is the use of information. The share of business in the field of information and communication technologies in the economy is constantly growing. For businesses, its integration into the Internet, which has become an important market for the sale and promotion of goods and services, is becoming increasingly important. Various digital innovations, social networks, mobile applications, information and communication technologies have become commonplace in today's society, which affects the need to study their impact on business. Technology transfer is the basis of innovative activities of small businesses and a means of their sustainable development, a guarantee of profit and social impact. It is noted that in order to win in the competition, personal brand and trademarks, strategic management and balanced business plans are of special importance. A characteristic feature of leading high-tech companies is the use of digital platforms through which they provide their services. Digital platforms are used for interaction in social networks, use of search and payment systems, exchange of information materials. The need for high start-up costs leads to the difficulty of entering this market and the concentration of large amounts of data in the hands of a small number of players, which carries the threat of monopolization in the market of digital platforms.

Exchange networks of the Early Bronze Age Gulf: The imported ceramics from Kalba 4 (United Arab Emirates)

AbstractImported ceramics from Early Bronze Age contexts in southeast Arabia illustrate a complex multidirectional network of material and social interactions at this time. Significant socioeconomic changes that occurred in the Hafit (3200–2800 B.C.) and Umm an‐Nar (2800–2000 B.C.) periods have been linked to external demand for copper, which is argued to have stimulated a change in subsistence patterns. Similarly, disruption to long‐distance exchange networks by external factors has been cited as driving change at the end of the Umm an‐Nar period. Archaeological evidence from the region suggests a shift in the direction of exchange from Mesopotamia to the Indus occurred around the middle of the third millennium B.C. However, a recent analysis of Mesopotamian historical sources has highlighted the scale of state‐organised textile production for export to the lower Gulf in the later third millennium B.C. The site of Kalba 4 has a stratified sequence of occupation deposits dating from the Umm an‐Nar and Iron Age (1300–300 B.C.). In this study, a typological analysis of imported ceramics is used to locate the Kalba in the chronological framework of the region and discuss the changing networks of long‐distance exchange that were operating. The imported pottery at Kalba 4 indicates that the inhabitants of the site were exchanging goods with a range of polities, including southern Mesopotamia, the Indus Valley (Meluhha), southeast Iran (Marhashi) and Bahrain (Dilmun). A significant quantity of Late Akkadian ceramics at the site suggests it became an important location for Mesopotamian trade at this time.

Accounting information quality detection method of listed companies based on mobile social network interaction model

The existing quality of accounting information detection methods have large errors and cannot meet the needs of listed companies. Therefore, this paper presents a study on the accounting information quality detection methods of listed companies based on the mobile social network interaction model. The interactive model to obtain accounting information of listed companies based on mobile social network, select accounting information quality detection index, construct the accounting information quality detection index system; Determine the weight of accounting information quality detection index by hierarchical analysis method; construct a panel model based on detection index weight to realize the quality detection of accounting information of listed companies. The experimental results show that the accounting information quality detection error of this method is 0.10%–0.31%. It reduces detection error, improves detection accuracy, has good application performance, and is suitable for the promotion and application of accounting information quality detection.

Epidemics on multilayer simplicial complexes

Simplicial complexes describe the simple fact that in social networks a link can connect more than two individuals. As we show here, this has far-reaching consequences for epidemic spreading, in particular in the context of a multilayer network model, where one layer is a virtual social network and the other one is a physical contact network. The social network layer is responsible for the transmission of information via pairwise or higher order 2-simplex interactions among individuals, while the physical layer is responsible for the epidemic spreading. We use the microscopic Markov chain approach to derive the probability transition equations and to determine epidemic outbreak thresholds. We further support these results with Monte Carlo simulations, which are in good agreement, thus confirming the analytical tractability of the proposed model. We find that information transmission rates are frequently low when actual disease transmission rates in the physical network are low or medium, and we show that this can be mitigated effectively by introducing 2-simplex interactions in the social network. The relative ease of introducing higher-order interactions in virtual social networks means that this could be exploited to inhibit epidemic outbreaks.