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Addressing self-disclosure in social media: An instructional awareness approach

机译:解决社交媒体中的自我披露:一种教学意识方法

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Nowadays the information flowing across the different Social Network Sites (SNSs) like Facebook is highly diverse and rich in its content. It is precisely the diversity of the users' contributions to SNSs that makes these platforms attractive and interesting to engage with. Nevertheless, there is a high amount of private and sensitive information being disclosed permanently by these users in order to take full advantage of the services offered by such sites. Current privacy-protection approaches (like the one provided by Facebook) allow users to restrict the audience of their contributions and hide particular pieces of information; however, they are still far from being widely adopted and put proactively into practice. For this reason, we propose to analyze and address different aspects of online self-disclosure in Social Media from a pedagogical and self-adaptive perspective. In this work we introduce the architecture of an Instructional Awareness System (IAS) based on the MAPE-K blueprint for autonomic systems, and provide a definition of its feedback mechanism using principles of Constraint-Based Modeling (CBM).
机译:如今,像Facebook之类的不同社交网站(SNS)上流传的信息高度多样化,内容丰富。正是用户对SNS贡献的多样性使这些平台具有吸引力和吸引力。但是,这些用户会永久披露大量私人和敏感信息,以便充分利用此类站点提供的服务。当前的隐私保护方法(如Facebook提供的方法)允许用户限制其贡献的受众并隐藏特定信息;但是,它们仍然没有被广泛采用并积极地付诸实践。因此,我们建议从教学和自适应的角度分析和解决社交媒体中在线自我披露的不同方面。在这项工作中,我们介绍了基于MAPE-K自主系统蓝图的教学意识系统(IAS)的体系结构,并使用基于约束的建模(CBM)原理提供了其反馈机制的定义。

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