26,762 research outputs found

    Utility of Parental Mediation Model on Youth’s Problematic Online Gaming

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    The Parental Mediation Model PMM) was initially designed to regulate children’s attitudes towards the traditional media. In the present era, because of prevalent online media there is a need for similar regulative measures. Spending long hours on social media and playing online games increase the risks of exposure to the negative outcomes of online gaming. This paper initially applied the PMM developed by European Kids Online to (i) test the reliability and validity of this model and (ii) identify the effectiveness of this model in controlling problematic online gaming (POG). The data were collected from 592 participants comprising 296 parents and 296 students of four foreign universities, aged 16 to 22 years in Kuala Lumpur (Malaysia). The study found that the modified model of the five-factor PMM (Technical mediation, Monitoring mediation, Restrictive mediation, Active Mediation of Internet Safety, and Active mediation of Internet Use) functions as a predictor for mitigating POG. The findings suggest the existence of a positive relation between ‘monitoring’ and ‘restrictive’ mediation strategies and exposure to POG while Active Mediation of Internet Safety and Active mediation of Internet use were insignificant predictors. Results showed a higher utility of ‘technical’ strategies by the parents led to less POG. The findings of this study do not support the literature suggesting active mediation is more effective for reducing youth’s risky behaviour. Instead, parents need to apply more technical mediations with their children and adolescents’ Internet use to minimize the negative effects of online gaming

    The Importance of Transparency and Willingness to Share Personal Information

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    This study investigates the extent to which individuals are willing to share their sensitive personal information with companies. The study examines whether skepticism can influence willingness to share information. Additionally, it seeks to determine whether transparency can moderate the relationship between skepticism and willingness to share and whether 1) companies perceived motives, 2) individual’s prior privacy violations, 3) individuals’ propensity to take risks, and 4) individuals self-efficacy act as antecedents of skepticism. Partial Least Squares (PLS) regression is used to examine the relationships between all the factors. The findings indicate that skepticism does have a negative impact on willingness to share personal information and that transparency can reduce skepticis

    Exploring service quality among online sharing economy platforms from an online media perspective

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    The sharing economy has become a new socioeconomic activity that allows the co-creation, production, distribution and consumption of goods and services between individuals, driven by Web 2.0 and e-word of mouth. How these online platforms communicate their content is critical. This paper seeks to develop a scale for measuring the perceived quality of websites that offer information about sharing economy services focused on online peer-to-peer accommodation. The resulting model is validated by means of structural equations and is composed of four dimensions (efficiency; reliability, privacy/security; and communication). The influence that perceived quality exerts on satisfaction and loyalty is then explored from an online media perspective. A scale resulting from the combination of these two areas of knowledge (online media and e-service quality) may take advantage of the more beneficial features they have to offer and provide us with as balanced and convergent a model as possible. The results of the study show that all of the initial hypotheses are confirmed except one. Efficiency, reliability and privacy/security positively influence the perceived quality of a collaborative accommodation portal, whereas communication does notFunding: This research was funded by MINISTERIO DE ECONOMÍA, INDUSTRIA Y COMPETITIVIDAD, grant id. TURCOLAB ECO2017-88984-R. Acknowledgments: The authors acknowledge the support of the Catalan Government for the accreditation as Consolidated Research Group TURESCO (2017 SGR 49)

    Executive Summary

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    Children, family and the state : revisiting public and private realms

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    The state is often viewed as part of the impersonal public sphere in opposition to the private family as a locus of warmth and intimacy. In recent years this modernist dichotomy has been challenged by theoretical and institutional trends which have altered the relationship between state and family. This paper explores changes to both elements of the dichotomy that challenge this relationship: a more fragmented family structure and more individualised and networked support for children. It will also examine two new elements that further disrupt any clear mapping between state/family and public/private dichotomies: the third party role of the child in family/state affairs and children's application of virtual technology that locates the private within new cultural and social spaces. The paper concludes by examining the rise of the 'individual child' hitherto hidden within the family/state dichotomy and the implications this has for intergenerational relations at personal and institutional levels

    Consensus-Based Transfer Linear Support Vector Machines for Decentralized Multi-Task Multi-Agent Learning

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    Transfer learning has been developed to improve the performances of different but related tasks in machine learning. However, such processes become less efficient with the increase of the size of training data and the number of tasks. Moreover, privacy can be violated as some tasks may contain sensitive and private data, which are communicated between nodes and tasks. We propose a consensus-based distributed transfer learning framework, where several tasks aim to find the best linear support vector machine (SVM) classifiers in a distributed network. With alternating direction method of multipliers, tasks can achieve better classification accuracies more efficiently and privately, as each node and each task train with their own data, and only decision variables are transferred between different tasks and nodes. Numerical experiments on MNIST datasets show that the knowledge transferred from the source tasks can be used to decrease the risks of the target tasks that lack training data or have unbalanced training labels. We show that the risks of the target tasks in the nodes without the data of the source tasks can also be reduced using the information transferred from the nodes who contain the data of the source tasks. We also show that the target tasks can enter and leave in real-time without rerunning the whole algorithm

    Secure webs and buying intention: the moderating role of usability

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    El presente trabajo ha planteado un modelo conceptual a fin de mostrar como los antecedentes de la intenciĂłn de compra se ven reforzados en contextos de Webs altamente usables. EspecĂ­ficamente, el trabajo analiza en profundidad el rol moderador de la usabilidad en la explicaciĂłn de la conexiĂłn entre seguridad de una Web e intenciĂłn de compra. Entre ambos extremos (seguridad e intenciĂłn de compra), se han incluido diversas variables para explicar mejor su conexiĂłn. Para ello, ha sido diseñada una Web ficticia de ropa dirigida al segmento joven de clase media. A fin de alterar la usabilidad de la Web se han realizado dos tipos de manipulaciones: la velocidad y la facilidad de uso de la Web. Las dos Webs creadas (alta usabilidad y baja usabilidad) fueron visitadas por un total de 170 encuestados que fueron compensados con un USB valorado en 15 euros. Los resultados muestran que la seguridad percibida en la Web acarrea tres interesantes efectos (especialmente para la Web altamente usable): (i) mejora las actitudes agrado, (ii) reduce el nivel de riesgo percibido; (iii) aumenta la confianza. Los dos Ășltimos efectos, a su vez, acaban aumentando la intenciĂłn de compra.. Por Ășltimo, se ha demostrado que la usabilidad, efectivamente, refuerza las relaciones consideradas en el modelo propuesto para explicar la intenciĂłn de compra.A conceptual model has been proposed to show how buying intention antecedents are reinforced in highly usable contexts. Specifically, this paper deeply analyses the moderator role of system variables (usability) on explaining the relationship between Web security and buying intention. Between both extremes (security and buying intention), several relationships have also been stated to better explain this effect. An “ideal” fictitious Website was designed for a non existent clothing company directed at the segment of middle class consumers. In order to alter Web usability, two blocks of changes were made, one concerning Website speed and the other related to ease of use. Our experiment sample consisted of 170 respondents who participated in exchange for a pen-drive (USB) valued at 15 euros. The results show that improving website security has three interesting effects (especially in high usable contexts): (i) it improves pleasure attitudes, (ii) reduces the level of perceived risk and (iii) increases trust. Secondly, it has been found that to increase buying intention, two actions must be taken: (i) to diminish perceived risk and (ii) to improve users’ pleasure attitudes towards the Website. Finally, usability has been found to have a moderating role in all the relationships considered (reinforcing them)

    The Internet of Hackable Things

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    The Internet of Things makes possible to connect each everyday object to the Internet, making computing pervasive like never before. From a security and privacy perspective, this tsunami of connectivity represents a disaster, which makes each object remotely hackable. We claim that, in order to tackle this issue, we need to address a new challenge in security: education

    Sensing Subjective Well-being from Social Media

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    Subjective Well-being(SWB), which refers to how people experience the quality of their lives, is of great use to public policy-makers as well as economic, sociological research, etc. Traditionally, the measurement of SWB relies on time-consuming and costly self-report questionnaires. Nowadays, people are motivated to share their experiences and feelings on social media, so we propose to sense SWB from the vast user generated data on social media. By utilizing 1785 users' social media data with SWB labels, we train machine learning models that are able to "sense" individual SWB from users' social media. Our model, which attains the state-by-art prediction accuracy, can then be used to identify SWB of large population of social media users in time with very low cost.Comment: 12 pages, 1 figures, 2 tables, 10th International Conference, AMT 2014, Warsaw, Poland, August 11-14, 2014. Proceeding
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