使用集体健康意识推荐算法和教育虚拟伴侣来消除社交媒体威胁
Challenging Social Media Threats using Collective Well-being Aware Recommendation Algorithms and an Educational Virtual Companion
摘要：
社交媒体已经成为我们生活中不可或缺的一部分，将我们的互联能力扩展到新的水平。关于其积极影响有很多话要说。然而，另一方面，近年来社交媒体的一些严重负面影响一再被强调，指出了对社会及其更弱势成员，如青少年的各种威胁。因此，我们提出了一个理论框架的基础上自适应的“社交媒体虚拟伴侣”的教育和支持整个社区，青少年学生，在社交媒体环境中进行互动，以实现理想的条件，定义在一个社区的具体和参与性的集体福祉（CWB）的设计措施。本指南将自动处理与专家干预和指导相结合。虚拟伴侣将由推荐系统（CWB-RS）提供支持，该系统将优化CWB指标，而不是参与度或平台利润，目前这在很大程度上驱动推荐系统，从而忽略任何社会附带影响。我们重点关注教育管理的专家和教育工作者伴侣的社交媒体社区。它们发挥着五个关键作用：（a）在以课堂为基础的教育活动中使用该指南;（b）指导CWB的定义;（c）提供学习策略、目标和活动的层次结构，以支持和包含基于层次强化学习的CWB-RS的自适应排序算法;（d）充当社区成员之间直接冲突的调解人;最后，（e）监测和解决超出智能代理的能力和控制的道德和教育问题。的同伴的组件和研究的教育和心理学的基本原则的性能的初步结果。
英文摘要：
Social media have become an integral part of our lives, expanding our interlinking capabilities to new levels. There is plenty to be said about their positive effects. On the other hand, however, some serious negative implications of social media have been repeatedly highlighted in recent years, pointing at various threats to society and its more vulnerable members, such as teenagers. We thus propose a theoretical framework based on an adaptive "Social Media Virtual Companion" for educating and supporting an entire community, teenage students, to interact in social media environments in order to achieve desirable conditions, defined in terms of a community-specific and participatory designed measure of Collective Well-Being (CWB). This Companion combines automatic processing with expert intervention and guidance. The virtual Companion will be powered by a Recommender System (CWB-RS) that will optimize a CWB metric instead of engagement or platform profit, which currently largely drives recommender systems thereby disregarding any societal collateral effect.We put an emphasis on experts and educators in the educationally managed social media community of the Companion. They play five key roles: (a) use the Companion in classroom-based educational activities; (b) guide the definition of the CWB; (c) provide a hierarchical structure of learning strategies, objectives and activities that will support and contain the adaptive sequencing algorithms of the CWB-RS based on hierarchical reinforcement learning; (d) act as moderators of direct conflicts between the members of the community; and, finally, (e) monitor and address ethical and educational issues that are beyond the intelligent agent's competence and control. Preliminary results on the performance of the Companion's components and studies of the educational and psychological underlying principles are presented.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
