Context Of Social Networks Research Articles

Group-Oriented Task Allocation for Crowdsourcing in Social Networks

Previous crowdsourcing studies often adopted the individual-oriented approach that outsources a task to an individual worker or team formation-based approach that outsources a task to an artificially formed team of workers. Nowadays, workers are often naturally organized into groups through social networks. To address such common issue of grouped workers in real crowdsourcing systems, this article explores a novel crowdsourcing paradigm in which the task allocation targets are naturally existing worker groups but not individual workers or artificially formed teams as before. Because a natural group might not possess all required skills and needs to coordinate with other groups in the social network contexts for performing a complex task, a concept of contextual crowdsourcing value is presented to measure a group's capacity to complete a task by coordinating with its contextual groups, which determines the priority that the group is assigned the task; then, the task allocation algorithms, including the allocations of groups and the workers actually participating in executing the task, are designed. The experiments on a real-world dataset show that our presented group-oriented approach can nearly always achieve better synergy performance, consistency performance, conflict performance, adaptability, and effectiveness on reducing costs, as compared with previous benchmark individual-oriented and team formation approaches.

Antecedents and Outcomes of Information Privacy Concerns in the Saudi Arabia Social Networking Context

Online information privacy has become a developing social worry that may hinder individuals' social site associations. The motivation behind this investigation is to dissect the effect of an err toward privacy and the social presence of a website on a person's privacy concerns about the website. Data were collected from 650 respondents in Saudi Arabia. The findings indicate a significance influence of informativness, social presence, utility of website, perceived severity, and self-efficacy on website-specific privacy concerns. Furthermore, privacy concerns have a significant influence on behavioural intentions. This study also extends the information privacy literature through the analysis of the drivers and outcomes of online privacy concerns in the social network context.

Adaptation of community-based distribution of family planning services to context-specific social networks: a case of marriage counsellors in Lusaka district, Zambia

BackgroundThe significant contribution of community-based distribution (CBD) of family planning services and contraceptives to the uptake of contraceptives in hard-to-reach communities has resulted in the scaling-up of this approach in many Sub-Saharan countries. However, contextual factors need to be taken into consideration. For example, social network influence (e.g. spouse/partner, in-laws, and parents) on fertility decisions in many African and Asian societies is inevitable because of the social organisational structures. Hence the need to adapt CBD strategies to the social network context of a given society.MethodsData collection involved structured interviews from August 2018 to March 2019. Randomly selected respondents (n = 149) were recruited from four purposively selected health facilities in Lusaka district, Zambia. Respondents were screened for age (> 15 yrs.) and marital status. A mix of categorical and qualitative data was generated. The Statistical Package for Social Sciences (SPSS®24) was used to carry out descriptive analysis and tests of association (Fisher’s exact) while Nvivo®12 was used to analyse the qualitative data using a deductive thematic approach.ResultsThe results indicate that pre-marriage counselling (pre-MC) influences key elements of the husband-wife relationship (p > 0.005), namely; sexual relationship, inter-personal communication, assignation of roles and responsibilities, leadership and authority. These elements of the husband-wife relationship also affect how spouses/partners interact when making fertility decisions. More importantly, the majority (86%) of the respondents indicated having a continuing relationship with their marriage counsellors because of the need to consult them on marital issues.ConclusionMarriage counsellors, though hardly reported in fertility studies, are important ‘constituents’ of the social network in the Zambian society. This is because marriage counsellors are trusted sources of information about marital issues and often consulted about family planning but perceived not to have the correct information about modern contraceptives. In this context, pre-MC offers a readily available, sustainable and culturally appropriate platform for disseminating accurate information about modern contraceptives provided in a private and personal manner. Therefore, the CBD strategy in Zambia can harness marriage counsellors by recruiting and training them as community agents.

Redes sociales y la adicción al like de la generación z

Psicólogos y expertos del mundo de la tecnología vienen advirtiendo, desde hace tiempo, que el uso frecuente y continuado de las redes sociales puede resultar en una adicción, lo que, a su vez, podría derivar en ansiedad, dependencia emocional, pérdida de motivación, falta de autocontrol e irritabilidad. Un estudio realizado por la Chicago Booth School of Business (2012) señalaba que las redes sociales tienen una capacidad de adicción mayor incluso que la del tabaco porque, entre otros motivos, acceder a estas plataformas resulta sencillo y, además, gratuito. Con el presente estudio, planteamos como objetivo principal analizar la importancia e impacto que supone el like en la generación Z, así como estudiar el contexto social de las redes sociales e investigar si el like afecta a esta generación y de qué manera. Para la elaboración de esta investigación se ha realizado, por un lado, una revisión bibliográfica sobre las redes sociales y el uso que los jóvenes hacen de ellas, identificando cuáles son sus favoritas, cuánto tiempo le dedican y las implicaciones que estas tienen sobre el cerebro humano. Por otro lado, se ha realizado un estudio de campo que se ha llevado a cabo en España a una muestra de 500 jóvenes de 18 a 26 años (los correspondientes a la generación Z), con el objetivo de conocer el uso que hacen de las redes sociales y analizar el impacto que tienen los likes sobre ellos. Entre las conclusiones principales destacamos un uso de redes sociales de más de tres horas diarias, siendo Instagram y WhatsApp las redes favoritas por esta generación. Si bien algunos miembros de este grupo social afirman sentirse inseguros, enfadados e incluso tristes si no reciben la respuesta esperada (traducida en likes o comentarios pospublicación) no modifican ni adaptan el tipo de contenido que comparten públicamente en base al número de likes que puedan conseguir. Finalmente, a pesar de que dicen no darle demasiada importancia a la retroalimentación recibida, suelen activar sus notificaciones en las redes sociales para estar a la última de posibles interacciones.

Social Networking of Quasi-Species Consortia drive Virolution via Persistence.

The emergence of cooperative quasi-species consortia (QS-C) thinking from the more accepted quasispecies equations of Manfred Eigen, provides a conceptual foundation from which concerted action of RNA agents can now be understood. As group membership becomes a basic criteria for the emergence of living systems, we also start to understand why the history and context of social RNA networks become crucial for survival and function. History and context of social RNA networks also lead to the emergence of a natural genetic code. Indeed, this QS-C thinking can also provide us with a transition point between the chemical world of RNA replicators and the living world of RNA agents that actively differentiate self from non-self and generate group identity with membership roles. Importantly the social force of a consortia to solve complex, multilevel problems also depend on using opposing and minority functions. The consortial action of social networks of RNA stem-loops subsequently lead to the evolution of cellular organisms representing a tree of life.

Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts

As a forward-looking reliability-management engineering technique, failure mode and effect analysis (FMEA) has been widely utilized to improve the reliability of products, processes, systems, and services. In practice, multiple responsible parties for FMEA implementation have different backgrounds, knowledge levels, and opinions. Integrating consensus into FMEA has some notable merits: the connections between FMEA participants can be strengthened, and a collective solution with a high degree of acceptability to the FMEA problem can be yielded. Meanwhile, the social network relationship among FMEA participants should be an essential element in FMEA because the participants’ opinions are subject to influence by each other and likely to evolve due to their social network interactions. Thus, this study first proposes a social network consensus model with minimum adjustment distance to assist FMEA participants in attaining a consensus, in which participants utilize a linguistic distribution assessment approach to represent their opinions. Second, an opinion evolution-based social network consensus model with minimum adjustment distance is further presented by considering the phenomenon of opinion evolution. Finally, some theoretical analyses, a case study, and a detailed comparative analysis are presented to verify the validity of the proposed FMEA approach.

The strength of weak bots

Some fear that social bots, automated accounts on online social networks, propagate falsehoods that can harm public opinion formation and democratic decision-making. Empirical research, however, resulted in puzzling findings. On the one hand, the content emitted by bots tends to spread very quickly in the networks. On the other hand, it turned out that bots’ ability to contact human users tends to be very limited. Here we analyze an agent-based model of social influence in networks explaining this inconsistency. We show that bots may be successful in spreading falsehoods not despite their limited direct impact on human users, but because of this limitation. Our model suggests that bots with limited direct impact on humans may be more and not less effective in spreading their views in the social network, because their direct contacts keep exerting influence on users that the bot does not reach directly. Highly active and well-connected bots, in contrast, may have a strong impact on their direct contacts, but these contacts grow too dissimilar from their network neighbors to further spread the bot’s content. To demonstrate this effect, we included bots in Axelrod’s seminal model of the dissemination of cultures and conducted simulation experiments demonstrating the strength of weak bots. A series of sensitivity analyses show that the finding is robust, in particular when the model is tailored to the context of online social networks. We discuss implications for future empirical research and developers of approaches to detect bots and misinformation.

Network culture and the aesthetics of dissension

This article addresses the complex relationship between digital activism and Internet art, from the initial proposals in the 1990s up to the present day. The analysis focuses on those projects that have most impacted the convergence of net art and “net-activism” during this period, with a particular emphasis on the relationship between artistic practice and hacktivism. Likewise, phenomena such as virtual sit-ins, DDOS-based strategies and several others that have emerged in the new context of social networks and participatory online platforms (memes, flash mobs, etc.) are analysed, in order to reflect on the new practices of social media art and their potential for specific critical action.

Social Capital in the Context of Fitness for Purpose Do Engineering Students in Africa Possesses the Right Capital

Social capital is important as it becomes an imperative as key indices for development and growth of students who opt for engineering education. Engineering educators have important role to play in motivating engineering students with untapped potentials to possess the right capital by creating productive teaching platforms. This paper explored the relationship of social capital on engineering education in addition to students possessing the right capital in their respective course of study. This paper argued that engineering educators should develop students’ social capital within the context of social networks and norms by promoting knowledge-based social capital and its productivity among engineering students. This paper was guided by Social Capital Theory, which lay emphases on the views that student learning should be centred on education invested on human capital and social capital. Specifically, we explore engineering students having the right capital in their study and social capital is a quality criterion that enhances students in possessing the right capital towards EE in Africa. Thus, to address the social capital gaps in engineering education, it suggested that engineering educational curriculum as well as staff development and capacity building should be designed in developing engineering student to possess the right capital in their field of study. A number of educational-oriented recommendations for social capital in engineering education investment were made.

Individual Characteristics, Social Networks and Investor Sentiment

Individual investors are always inevitably in the social network context, and their socialization varies greatly with their respective environment and social background. But at the same time, people will naturally communicate and share information to make up for their lack of information and experience. Investor sentiment will not only be affected by individual characteristics, but also be influenced by social networks, showing convergence during the interaction process. This paper collects individual investor characteristics, social networks, and sentiment state utilizing a network questionnaire, constructs the comprehensive indexes of investor sentiment and social networks, and analyzes the socialized influencing factors and diffusion mechanism of investor sentiment.The empirical results based on the online questionnaire survey data show that: Firstly, the individual characteristics of investors will affect their sentimental state. There is a positive promotion effect of variables such as the education and income, investment experience, household asset size, and stock investment ratio; the CCP membership of investors shows a significant negative effect, and age has an inverted U-shaped effect on their sentiment. Secondly, social network relationships have an inverted U-shaped effect on investor sentiment. Investors with very weak or strong social network relationships have a more peaceful sentimental state. Thirdly, group sentiment within the network will promote individual sentiment, causing investor sentiment to spread within the social network. But sentiment diffusion has significant differences among different types of investors, and the sentiment is more likely to spread among investors with low academic qualifications, not-CCP members, short investment years, and weak social networks. Finally, from the perspective of diffusion channels, the sentiment is mainly diffused in the network based on social interaction mechanisms, information mechanisms, and funding mechanisms. Among them, the social interaction and the breadth of information sources have an inhibitory effect on sentiment diffusion. The wider the source of funds and the higher the cost of funds, the lower the probability of sentiment spreading.These conclusions expand the research scope of investor sentiment in the context of social networks, and help to deeply understand how the sentiment spreads under the influence of individual characteristics and social networks. Also, these conclusions may enlighten stock market regulators to educate individual investors and suppress irrational investment behavior.

The problem and promise of scale in multilayer animal socialnetworks.

Scale remains a foundational concept in ecology. Spatial scale, for instance, has become a central consideration in the way we understand landscape ecology and animal space use. Meanwhile, scale-dependent social processes can range from fine-scale interactions to co-occurrence and overlapping home ranges. Furthermore, sociality can vary within and across seasons. Multilayer networks promise the explicit integration of the social, spatial, and temporal contexts. Given the complex interplay of sociality and animal space use in heterogeneous landscapes, there remains an important gap in our understanding of the influence of scale on animal social networks. Using an empirical case study, we discuss ways of considering social, spatial, and temporal scale in the context of multilayer caribou social networks. Effective integration of social and spatial processes, including biologically meaningful scales, within the context of animal social networks is an emerging area of research. We incorporate perspectives that link the social environment to spatial processes across scales in a multilayer context.

Suicidal ideation among North Korean refugees in South Korea: Exploring the influence of social network characteristics by gender.

Rates of death by suicide among North Korean refugees are three times higher than those among their host-country counterparts in South Korea. However, social and cultural factors predicting suicidality among North Korean refugees are not well known. Thus, we explored how social networks affect suicidal ideation in a sample of 405 North Korean refugees in South Korea using egocentric network data. Network diversity (number of different types of ties) was a protective factor for suicidal ideation among women. Having a help-providing and trustworthy church-based tie was a protective factor for women, whereas it was a risk factor for men. It is likely that women connected to people in diverse social contexts received more support to effectively deal with adversities. Because South Korean churches provide tailored worship services and financial aid to North Korean refugees, women might receive emotional comfort from church-based ties whom they can trust and receive help from, whereas men might become distressed about being financially dependent on others, which contradicts cultural expectations of a man's traditional role. Our findings have implications for mental health practitioners serving vulnerable populations, and highlight the importance of understanding the cultural context of social networks and gender in suicide research.

A joint feedback strategy for consensus in large-scale group decision making under social network

Nowadays, large-scale group decision making (LSGDM) has become a hot topic and brought new challenges for the decision makers. This article proposes a framework of joint feedback strategy to help large-scale group decision makers to reach an agreement by combing social network context and feedback behavior. Firstly, the social network of large-scale group decision makers is explored to study the trust relationship, and it is used to assign weights associated to decision makers. And the recommendation advice can be generated by trust relationship using as reliable resource to aggregate group opinions to a collective one. Secondly, the recommendation advice is embedded to the feedback mechanism in LSGDM, and a joint feedback strategy is proposed based on harmony degree to help the multiple non-consensus decision makers modify their preferences to improve the efficiency of consensus achievement. In detail, this article builds two optimization models with the aim of maximum harmony degree: (1) one is with consistent feedback behaviour; (2) the other is with different feedback behaviour. At last, a numerical and a comparison analysis are provided to show the validity of joint feedback strategy with different feedback behaviors.

Network Estimation via Graphon With Node Features

Estimating the probabilities of linkages in a network has gained increasing interest in recent years. One popular model for network analysis is the exchangeable graph model (ExGM) characterized by a two-dimensional function known as a graphon. Estimating an underlying graphon becomes the key of such analysis. Several nonparametric estimation methods have been proposed, and some are provably consistent. However, if certain useful features of the nodes (e.g., age and schools in social network context) are available, none of these methods was designed to incorporate this source of information to help with the estimation. This paper develops a consistent graphon estimation method that integrates the information from both the adjacency matrix itself and node features. We show that properly leveraging the features can improve the estimation. A cross-validation method is proposed to automatically select the tuning parameter of the method.

A trust-similarity analysis-based clustering method for large-scale group decision-making under a social network

Large-scale group decision-making (LSGDM) under a social network context has attracted much attention in the field of decision science. The clustering of individual opinions and the handling of trust relationships are the main research topics. Opinion similarity and trust relationship are considered to be two important measurement attributes for implementing clustering. Traditional clustering methods often use a single attribute to divide the original group without requiring a combination of the above two attributes. However, these two attributes play different roles in the clustering process, insofar as opinion similarity is used to measure the level of difference among individual opinions, whereas the trust relationship represents the trustworthiness of decision makers. This paper develops a trust-similarity analysis (TSA)-based clustering method to manage the clustering operation in LSGDM events under a social network context. First, the trust-similarity matrix is established to collectively describe the decision information. Second, all measurement attribute values are mapped to a trust-similarity plot from which the joint threshold can be calculated. Finally, a TSA-based clustering method is proposed that considers the attributes of opinion similarity and trust relationship and that allocates their importance to achieve specific clustering objectives. The numerical experiment and comparative analysis reveal the feasibility and advantages of the proposed method.

Knowledge sharing in social networks: considering the role of political skill and trust

PurposeThe purpose of this paper is to bring a more individual focus to social networks in theorizing the social process of knowledge sharing.Design/methodology/approachThe theoretical model proposes that political skill will shape an individual's social network. Further, political skill within a network will influence the degree of complex knowledge sharing, which likely happens through the mechanism of affective- and cognitive-based trust.FindingsTheoretical implications and future research directions are discussed.Originality/valueKnowledge sharing is an inherently social process and as such occurs within the context of social networks in an organization. However, research to date has not fully explored the details of how and why complex knowledge sharing happens within a social network. Generally, theory on social networks has focused on structural qualities of a network, rather than the individual characteristics of the members of that network. This paper brings a more individual focus to social networks in theorizing the social process of knowledge sharing.

The dilemma of social commerce

PurposeDue to customers' extensive avoidance behavior, social commerce may be less successful than anticipated. This study investigates the underlying mechanism and antecedents that influence customers' avoidance of peer-generated advertisements.Design/methodology/approachBased on the general framework of avoidance behavior, we propose a theoretical model for the context of a mobile social network, with tie strength as the user-related factor and violation of shared language, advertisement relevance and information overload as contextual variables. Using survey data collected from 334 customers on WeChat, we empirically examine the research model and hypotheses.FindingsTie strength and advertisement relevance are negatively associated with avoidance behavior, whereas information overload and violation of shared language have significantly positive effects. Furthermore, tie strength weakens the negative relationship between violation of shared language and avoidance behavior but strengthens the positive relationship between advertisement relevance and avoidance behavior.Originality/valueThe findings extend understanding of advertisement avoidance behavior and can guide practitioners' improvement of advertising efficiency in mobile social networks.

Successful futures, successful curriculum: What can Wales learn from international curriculum reforms?

The proposed Curriculum for Wales 2022 presents a bold new vision for curriculum, teaching and learning. Together with its focus on four key purposes, it affords substantially more flexibility and autonomy to teachers and schools, positions learners as central to curriculum decision making, promotes active forms of pedagogy and twenty‐first‐century skills and reduces specification of curriculum content. Like other ‘new curriculum’ examples around the world, it brings with it a complex set of interacting curricular elements, with challenges including curriculum design capability and the agency required of those working with the curriculum. In this article, we discuss challenges and opportunities for this curriculum reform in light of international curriculum experience. In particular, we highlight the need for attention to the accountability, professional learning and social network context necessary for the realization of national curriculum aspirations in Wales.

Impact of Trust Aspects and Value Co-Creation as Mediation on Purchase Intention in Social Networking Context

Social Media Communication through Social Networking has become developing marketing issue of increasing popularity. This article investigates Word-of-Mouth communication through Social Networking Sites guided by the socialization framework with Purchase Intention as outcomes and Value Co-creation, Trust as antecedents. 508 participants who engaged in Word- of-Mouth communication about products through Social Networking Sites are surveyed. It confirms that the trust and Value Co-creation influences Purchase Intention positively. Electronic Word-of-Mouth communication impacts Purchase Intention directly and indirectly by reinforcing Value Co-creation with Trust. The model is used to study the main objective of determining the factors of consumer purchase intention through Word-of-Mouth communication in Social Networking Sites. These findings have significance managerial and theoretical implications.

Numerical Interval Opinion Dynamics in Social Networks: Stable State and Consensus

When people express their opinions, they often cannot provide exact opinions but express uncertain opinions, such as numerical interval opinions. Moreover, due to the differences in the cultural background and character of agents, people who encounter numerical interval opinions often show different uncertainty tolerances. By taking different numerical interval opinions and different uncertainty tolerances into account, in this article, we propose a numerical interval opinion dynamics model to investigate the process of forming collective opinions in a group of interaction agents under an uncertain and social network context. We propose the theoretical analysis and algorithms to identify the stable agents whose opinions will be becoming stable and the oscillation agents whose opinions will always be fluctuating in the opinion evolution process. Furthermore, we study the conditions under which a consensus opinion can be built among the stable agents and estimate the opinion ranges of the oscillation agents. Finally, numerical examples and analysis are used to show the feasibility and effectiveness of the proposed theories and algorithms.