19,108 research outputs found

    Self-disclosure and privacy calculus on social networking sites: the role of culture

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    Social Networking Sites (SNSs) have become extremely popular around the world. They rely on user-generated content to offer engaging experience to its members. Cultural differences may inïŹ‚uence the motivation of users to create and share content on SNS. This study adopts the privacy calculus perspective to examine the role of culture in individual self-disclosure decisions. The authors use structural equation modeling and multi-group analysis to investigate this dynamics. The ïŹndings reveal the importance of cultural dimensions of individualism and uncertainty avoidance in the cognitive processes of SNS users

    User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy

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    Recommender systems have become an integral part of many social networks and extract knowledge from a user's personal and sensitive data both explicitly, with the user's knowledge, and implicitly. This trend has created major privacy concerns as users are mostly unaware of what data and how much data is being used and how securely it is used. In this context, several works have been done to address privacy concerns for usage in online social network data and by recommender systems. This paper surveys the main privacy concerns, measurements and privacy-preserving techniques used in large-scale online social networks and recommender systems. It is based on historical works on security, privacy-preserving, statistical modeling, and datasets to provide an overview of the technical difficulties and problems associated with privacy preserving in online social networks.Comment: 26 pages, IET book chapter on big data recommender system

    Social Media in the Dental School Environment, Part B: Curricular Considerations

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    The goal of this article is to describe the broad curricular constructs surrounding teaching and learning about social media in dental education. This analysis takes into account timing, development, and assessment of the knowledge, skills, attitudes, and behaviors needed to effectively use social media tools as a contemporary dentist. Three developmental stages in a student’s path to becoming a competent professional are described: from undergraduate to dental student, from the classroom and preclinical simulation laboratory to the clinical setting, and from dental student to licensed practitioner. Considerations for developing the dental curriculum and suggestions for effective instruction at each stage are offered. In all three stages in the future dentist’s evolution, faculty members need to educate students about appropriate professional uses of social media. Faculty members should provide instruction on the beneficial aspects of this communication medium and help students recognize the potential pitfalls associated with its use. The authors provide guidelines for customizing instruction to complement each stage of development, recognizing that careful timing is not only important for optimal learning but can prevent inappropriate use of social media as students are introduced to novel situations

    Journal of Asian Finance, Economics and Business, v. 4, no. 3

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    Mining social network data for personalisation and privacy concerns: A case study of Facebook’s Beacon

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    This is the post-print version of the final published paper that is available from the link below.The popular success of online social networking sites (SNS) such as Facebook is a hugely tempting resource of data mining for businesses engaged in personalised marketing. The use of personal information, willingly shared between online friends' networks intuitively appears to be a natural extension of current advertising strategies such as word-of-mouth and viral marketing. However, the use of SNS data for personalised marketing has provoked outrage amongst SNS users and radically highlighted the issue of privacy concern. This paper inverts the traditional approach to personalisation by conceptualising the limits of data mining in social networks using privacy concern as the guide. A qualitative investigation of 95 blogs containing 568 comments was collected during the failed launch of Beacon, a third party marketing initiative by Facebook. Thematic analysis resulted in the development of taxonomy of privacy concerns which offers a concrete means for online businesses to better understand SNS business landscape - especially with regard to the limits of the use and acceptance of personalised marketing in social networks

    Modelling Requirements for Content Recommendation Systems

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    This paper addresses the modelling of requirements for a content Recommendation System (RS) for Online Social Networks (OSNs). On OSNs, a user switches roles constantly between content generator and content receiver. The goals and softgoals are different when the user is generating a post, as opposed as replying to a post. In other words, the user is generating instances of different entities, depending on the role she has: a generator generates instances of a "post", while the receiver generates instances of a "reply". Therefore, we believe that when addressing Requirements Engineering (RE) for RS, it is necessary to distinguish these roles clearly. We aim to model an essential dynamic on OSN, namely that when a user creates (posts) content, other users can ignore that content, or themselves start generating new content in reply, or react to the initial posting. This dynamic is key to designing OSNs, because it influences how active users are, and how attractive the OSN is for existing, and to new users. We apply a well-known Goal Oriented RE (GORE) technique, namely i-star, and show that this language fails to capture this dynamic, and thus cannot be used alone to model the problem domain. Hence, in order to represent this dynamic, its relationships to other OSNs' requirements, and to capture all relevant information, we suggest using another modelling language, namely Petri Nets, on top of i-star for the modelling of the problem domain. We use Petri Nets because it is a tool that is used to simulate the dynamic and concurrent activities of a system and can be used by both practitioners and theoreticians.Comment: 28 pages, 7 figure
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