EAGER: Exploring Children's Use of Online Social Networks Using the KidGab Network

这项提议将支持使用KidGab研究儿童使用社交网络的原因以及他们如何相互影响。KidGab是一个由研究团队管理的社交网络，专为青春期前的女童子军设计。尽管青少年经常使用社交网络，但人们对他们(与成年人相比)在网上的行为或这如何影响他们的幸福感知之甚少，因为大多数流行的社交网络在被发现时会关闭青少年的账户，而为青少年量身定做的网络在用户可以做什么和可供研究的数据方面都受到了严格的限制。在他们与德克萨斯州女童军委员会现有工作的基础上，研究小组将为KidGab开发新的功能和活动，并与新的委员会一起举办外联研讨会。这将使该团队能够研究儿童对不同的招募和激励(游戏化)策略的反应，特别是观察成人与同伴创建的内容以及协作活动与个人活动在鼓励继续使用方面的相对价值。通过观察儿童如何在以视觉为重点的活动中创造和采用彼此的绘画，该团队还将开发新的方法来研究创造力、一致性和在社交网络中的影响力。除了在这些具体问题上取得进展外，该团队的长期研究目标是建立一个足够大的网络和数据集，以便他们和其他研究人员都可以进行未来的研究和分析。更广泛地说，该团队将创建有用的在线内容和设计指南，为青少年建立社交网络，支持身份发展和个人联系等积极结果，同时减少过度分享和网络欺凌等不良结果。该团队的初步工作表明，定期发布新内容对于保持参与度至关重要；因此，该提案的第一个主要组成部分是开发方法，让网络中的儿童生成和分享内容，如个性测验和图像，网络成员可以使用虚拟货币购买并在他们的个人资料中展示这些内容。这将允许团队(1)比较成人创建的内容与同伴创建的内容的吸收情况及其对鼓励长期参与的影响，(2)检查儿童在生成儿童创建的内容库时更喜欢生成和消费的内容类型，以及(3)研究关于身份创建和探索的更大问题。第二个主要组成部分是开展以素描为基础的活动，向参与者提供一项创造性任务，并使他们的工作通过网络可见，以便其他参与者可以在自己的工作中采纳其中的想法。该团队将手动编码为给定任务生成的草图的关键特征，并使用链接分析算法(如PageRank和Hubs and Authority算法)研究它们的传播，将参与者作为中心或权威的程度解释为他们受到他人影响或影响的可能性。通过观察各种特定的任务和指导行为的变化，以及参与者的特征，该团队将深入了解青少年社交网络中影响的关键驱动因素。此外，手动注释的草图将为计算机视觉和用于草图分析的机器学习算法提供训练数据。该团队将通过与地理上已参与该网络的人附近的各个童子军委员会举行的活动来部署这些内容创建机制；这样的战略将最好地利用该团队与附近委员会的现有关系，同时增加招募密集子网络的机会，以鼓励长期保留。

This proposal will support research into why children use social networks and how they influence each other using KidGab, a social network managed by the research team and designed for pre-teen Girl Scouts. Although pre-teens regularly use social networks, relatively little is known about how they (versus adults) behave online or how this affects their well-being because most popular social networks close pre-teens' accounts when detected, while purpose-built networks for pre-teens are heavily restricted in terms of both what users can do and what data is available for study. Building on their existing work with Girl Scout councils in Texas, the research team will develop new features and activities for KidGab and conduct outreach workshops with new councils. This will allow the team to study how children respond to different recruitment and motivating ('gamification') strategies, in particular, looking at the relative value of adult- versus peer-created content and collaborative versus individual activities in encouraging continued use. Through looking at how children create and adopt each other's drawings in visually-focused activities, the team will also develop novel methods for studying creativity, conformity, and influence in social networks. In addition to making progress on these specific questions, the team's long-term research goal is to build a large enough network and dataset that both they and other researchers can conduct future studies and analyses. More broadly, the team will create useful online content and design guidance for building social networks for pre-teens that support positive outcomes such as identity development and personal connection while reducing bad outcomes such as oversharing and cyberbullying.Preliminary work by the team shows that the regular release of new content is critical to retaining participation; thus, the first main component of the proposal is to develop ways for children in the network to generate and share content such as personality quizzes, and images that network members can use virtual currency to buy and display on their profiles. This will allow the team to (1) compare the uptake of adult-created versus peer-created content and their effects on encouraging long-term participation, (2) examine the kinds of content children prefer to generate and consume while generating a library of child-created content, and (3) study larger questions about identity creation and exploration. The second main component is to develop sketching-based activities in which participants are given a creativity task and their work is made visible through the network so that other participants can adopt ideas from it in their own work. The team will manually code key features of sketches generated for a given task and study their propagation using link-analysis algorithms such as PageRank and the Hubs and Authorities Algorithm, interpreting the degree to which a participant is a hub or authority as the likelihood that they are influenced by or influence others. By looking at a variety of specific tasks and variations in instructions that prime behaviors, as well as characteristics of participants, the team will develop insights into key drivers of influence in pre-teens' social networks. Further, the manually annotated sketches will provide training data for computer vision and machine learning algorithms for sketch analysis. The team will deploy these content creation mechanisms through events held with individual Scout councils geographically near those who have already participated in the network; such a strategy will best leverage the team's existing relationships with nearby councils while increasing the chance of recruiting dense sub-networks to encourage long-term retention.