I-Corps: Exploring the Commercialization Potential of ChatCoder

I-Corps：探索 ChatCoder 的商业化潜力

• 批准号: 1456172
• 负责人: April Edwards
• 金额: $ 5万
• 依托单位: Ursinus College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1456172&HistoricalAwards=false
• 关键词: Corps; Exploring; Commercialization; Potential; ChatCoder

Current parental control software does not provide parents and kids with the one tool they desperately want and need ? a method for halting cyber-aggression in progress, rather than reporting the event after it occurs. Although most cyberbullying and cyber-predation acts occur over an extended period of time, current programs can only detect acts based on keywords in text; they don?t offer tools to actually stop the abuse and they don?t capture context. Concern about cyberbullying and cyber-predation among parents and authorities has led to a booming parental control software market and to the passage of anti-cyberbullying laws in many states. The proposed innovation offers better recognition of cyber-abuse and as well as response capabilities; thereby providing a more dynamic, interactive, and empowering resource for youths and their parents.The team has developed machine learning algorithms that are able to detect approximately 80% of cyberbullying communication, and 84% of predatory conversation. These algorithms were developed using data that was collected and labeled for research purposes. The algorithms need to be adapted for real-time communication, as well as continuously updated as additional data become available. The theoretical model for victim response is in development. The model identifies the type, context and severity of bullying or predation, along with categories of potential responses from which victims can choose. The team has completed the proof-of-concept and is ready to move forward with the development of a software prototype.

当前的家长控制软件无法为家长和孩子提供他们迫切想要和需要的一种工具？一种阻止正在进行的网络攻击的方法，而不是在事件发生后报告事件。尽管大多数网络欺凌和网络掠夺行为发生在很长一段时间内，但当前的程序只能根据文本中的关键字检测行为；他们不提供真正阻止滥用的工具，也不捕获上下文。家长和当局对网络欺凌和网络掠夺的担忧导致家长控制软件市场蓬勃发展，并导致许多州通过了反网络欺凌法律。拟议的创新可以更好地识别网络滥用以及响应能力；从而为青少年及其父母提供更具活力、互动性更强的资源。该团队开发了机器学习算法，能够检测大约 80% 的网络欺凌通信和 84% 的掠夺性对话。这些算法是使用为研究目的收集和标记的数据开发的。这些算法需要适应实时通信，并随着额外数据的可用而不断更新。受害者反应的理论模型正在开发中。该模型确定了欺凌或掠夺的类型、背景和严重性，以及受害者可以选择的潜在反应类别。该团队已经完成了概念验证，并准备继续开发软件原型。