Collaborative Research: HCC: Small: Understanding Online-to-Offline Sexual Violence through Data Donation from Users
合作研究:HCC:小型:通过用户捐赠的数据了解线上线下性暴力
基本信息
- 批准号:2211897
- 负责人:
- 金额:$ 19.69万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-10-01 至 2026-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
This project will improve our understanding of online-to-offline sexual violence by exploring how computer-mediated communication shapes consent exchange practices, or the ways in which individuals give and perceive to receive consent to sexual activity. Sexual violence is a serious public health problem in the United States: every 68 seconds an American is sexually assaulted. Online-to-offline sexual violence refers to nonconsensual sexual acts that occur via the combination of computer-mediated and face-to-face communication. The ways in which Americans discover and interact with potential sexual partners are increasingly computer-mediated, however we have little understanding of how computer-mediated communication influences perceptions of appropriate sexual behavior, which may predispose individuals to becoming perpetrators or victims of sexual harm without their realization. The knowledge produced through this project will benefit public health and constitute crucial advances in multiple intersecting fields such as human computer interaction, nursing, and psychology via informing entirely new solutions to online-to-offline sexual violence that are truly preventative and do not rely on conscious intent by the perpetrator to cause harm, or recognition by victims that harm is occurring. The research uses a mixed methods, longitudinal approach to studying online-to-offline sexual activity through online dating, a well known context for sexual violence. A framework of online-to-offline sexual violence through the lens of computer-mediated consent will be developed by creating, curating, and analyzing a dataset of user behavior examples during online dating. This will comprise instances of online daters' behavior across online and offline interaction as it relates to sexual activity such as consent practices, as well as the impacts of such behavior on key psychological constructs. Data collection will be made more scalable and privacy-preserving with a data donation app embodying best practices for sexual experience reporting. The research plan involves user-centered design, implementation, and evaluation of the data donation app, followed by multiple cohorts of longitudinal data collection with online daters through use of the data donation app and recurrent interviews about their online dating and associated sexual experiences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
这个项目将通过探索计算机中介沟通如何塑造同意交换做法,或个人给予和感知接受性活动的同意的方式,来提高我们对线上到线下性暴力的理解。性暴力在美国是一个严重的公共卫生问题:每68秒就有一名美国人遭到性侵。线上到线下的性暴力是指通过网络媒介和面对面交流相结合而发生的非双方自愿的性行为。美国人发现并与潜在的性伴侣互动的方式越来越多地是通过电脑来实现的,然而,我们对电脑传播如何影响人们对适当性行为的看法知之甚少,这可能会使个人在不知不觉中成为性伤害的实施者或受害者。通过该项目产生的知识将有益于公共健康,并通过告知线上到线下的性暴力的全新解决方案,真正具有预防性,并构成多个交叉领域的关键进步,如人机交互、护理和心理学,而不依赖于犯罪者造成伤害的有意意图,或受害者对伤害正在发生的认识。这项研究使用了一种混合的方法,纵向的方法来研究线上到线下通过在线约会的性行为,这是众所周知的性暴力的背景。通过创建、管理和分析在线约会期间用户行为实例的数据集,将开发一个通过网络中介同意的镜头在线到线下性暴力的框架。这将包括在线交友者在线上和线下互动中的行为实例,因为它与性行为有关,例如同意做法,以及这种行为对关键心理结构的影响。数据收集将变得更具可扩展性和隐私保护,因为数据捐赠应用程序体现了性体验报告的最佳做法。该研究计划涉及以用户为中心的数据捐赠应用程序的设计、实施和评估,然后通过使用数据捐赠应用程序对在线约会对象进行多个队列的纵向数据收集,并定期采访他们的在线约会和相关的性经历。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
AttCAT: Explaining Transformers via Attentive Class Activation Tokens
- DOI:
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Yao Qiang;Deng Pan;Chengyin Li;X. Li;Rhongho Jang;D. Zhu
- 通讯作者:Yao Qiang;Deng Pan;Chengyin Li;X. Li;Rhongho Jang;D. Zhu
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Dongxiao Zhu其他文献
"It's Not What We Were Trying to Get At, but I Think Maybe It Should Be": Learning How to Do Trauma-Informed Design with a Data Donation Platform for Online Dating Sexual Violence
“这不是我们想要达到的目标,但我认为也许应该如此”:学习如何利用在线约会性暴力的数据捐赠平台进行创伤知情设计
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Wenqi Zheng;Emma Walquist;Isha Datey;Xiangyu Zhou;Kelly Berishaj;Melissa Mcdonald;Michele Parkhill;Dongxiao Zhu;Douglas Zytko - 通讯作者:
Douglas Zytko
MFABA: A More Faithful and Accelerated Boundary-based Attribution Method for Deep Neural Networks
MFABA:一种更忠实、更加速的深度神经网络基于边界的归因方法
- DOI:
10.48550/arxiv.2312.13630 - 发表时间:
2023 - 期刊:
- 影响因子:3.4
- 作者:
Zhiyu Zhu;Huaming Chen;Jiayu Zhang;Xinyi Wang;Zhibo Jin;Minhui Xue;Dongxiao Zhu;Kim - 通讯作者:
Kim
Towards Trauma-Informed Data Donation of Sexual Experience in Online Dating to Improve Sexual Risk Detection AI
致力于在线约会中性经历的创伤知情数据捐赠,以改进性风险检测人工智能
- DOI:
10.1145/3586182.3616689 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Wenqi Zheng;Emma Walquist;Isha Datey;Xiangyu Zhou;Kelly Berishaj;Melissa Mcdonald;Michele Parkhill;Dongxiao Zhu;Douglas Zytko - 通讯作者:
Douglas Zytko
Benchmark and Neural Architecture for Conversational Entity Retrieval from a Knowledge Graph
从知识图进行会话实体检索的基准和神经架构
- DOI:
10.1145/3589334.3645676 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Mona Zamiri;Yao Qiang;Fedor Nikolaev;Dongxiao Zhu;Alexander Kotov - 通讯作者:
Alexander Kotov
Mechanical evolution of metastatic cancer cells in three-dimensional microenvironment
三维微环境中转移癌细胞的机械演化
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Karlin Hilai;Daniil Grubich;Marcus Akrawi;Hui Zhu;Razanne Zaghloul;Chenjun Shi;Man Do;Dongxiao Zhu;Jitao Zhang - 通讯作者:
Jitao Zhang
Dongxiao Zhu的其他文献
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{{ truncateString('Dongxiao Zhu', 18)}}的其他基金
NSF Convergence Accelerator Track H: Leveraging Human-Centered AI Microtransit to Ameliorate Spatiotemporal Mismatch between Housing and Employment for Persons with Disabilities
NSF 融合加速器轨道 H:利用以人为本的人工智能微交通改善残疾人住房和就业之间的时空不匹配
- 批准号:
2235225 - 财政年份:2022
- 资助金额:
$ 19.69万 - 项目类别:
Standard Grant
SCC-CIVIC-PG Track A: Leveraging AI-assist Microtransit to Ameliorate Spatiotemporal Mismatch between Housing and Employment
SCC-CIVIC-PG Track A:利用人工智能辅助微交通改善住房和就业之间的时空错配
- 批准号:
2043611 - 财政年份:2021
- 资助金额:
$ 19.69万 - 项目类别:
Standard Grant
EAGER: A Novel Algorithmic Framework for Discovering Subnetworks from Big Biological Data
EAGER:一种从生物大数据中发现子网络的新颖算法框架
- 批准号:
1451316 - 财政年份:2014
- 资助金额:
$ 19.69万 - 项目类别:
Standard Grant
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Research on Quantum Field Theory without a Lagrangian Description
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Cell Research (细胞研究)
- 批准号:30824808
- 批准年份:2008
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- 批准号:10774081
- 批准年份:2007
- 资助金额:45.0 万元
- 项目类别:面上项目
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