EAGER: Detecting and Tracking Cyber Bullying on the Social Web

EAGER：检测和跟踪社交网络上的网络欺凌

• 批准号: 1144564
• 负责人: Yi Zhang
• 金额: $ 14.73万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1144564&HistoricalAwards=false
• 关键词: EAGER; Detecting; Tracking; Cyber; Bullying

As many children are connected to their peers and spend a significant amount of time on social web sites (Facebook, Twitter, etc.), cyber bullying in social media is becoming a severe problem that can lead to serious social, psychological, and health effects. To alleviate the problem, intervention from adults (teachers, parents, law enforcement, social web site moderators, etc.) is the key. However, many victims do not report bullying to adults, and bullies can use aliases and act anonymously, and thus they are difficult to identify. The goal of this exploratory project is to eliminate or at least reduce these problems by developing an intelligent system to automatically detect and track cyber bullies on the social web.This project explores a solution to cyber bullying based on a combination of machine learning, natural language processing, information filtering, and recommendation and social network modeling techniques. The expected results of the project include: (1) algorithm(s) that can detect cyber bullies and bullying messages automatically; (2) piloting results that suggest what prediction accuracy to expect; (3) a preliminary social web bullying detection prototype system and (4) the first labeled social cyber-bullying data set for testing of the prototype and future research in this direction. The project has high risk, as whether such a system can be developed is an untested idea and the task is challenging, largely due to the diversity of bully behaviors, ambiguity, and the special language used by bullies in social media. Results from this research project are expected to create a foundation for future larger-scale projects investigating the cyber-bullying problem in social media, which will eventually make the social interaction much safer for hundreds of millions of children and beyond. Teaching, training and learning will be promoted directly for the graduate students who serve as research assistants and programmers, and several undergraduates will contribute to the programming. The impact will be strengthened by UCSC's ethnic and cultural diversity, its proximity to Silicon Valley, and the PI's industry collaborations. Results of this research, including data generated, publications, and demo software will be available via the project web site (http://users.soe.ucsc.edu/~yiz/bullying/).

由于许多儿童与同龄人保持联系并在社交网站（Facebook、Twitter 等）上花费大量时间，社交媒体中的网络欺凌正在成为一个严重问题，可能导致严重的社会、心理和健康影响。 为了缓解这个问题，成年人（老师、家长、执法部门、社交网站管理员等）的干预是关键。然而，许多受害者不会向成年人举报欺凌行为，而且欺凌者可以使用化名、匿名行事，因此很难识别。 该探索性项目的目标是通过开发智能系统来自动检测和跟踪社交网络上的网络欺凌行为，从而消除或至少减少这些问题。该项目探索了一种基于机器学习、自然语言相结合的网络欺凌解决方案。处理、信息过滤、推荐和社交网络建模技术。该项目的预期成果包括：（1）能够自动检测网络欺凌和欺凌消息的算法； (2) 试点结果表明预期的预测精度； （3）初步的社交网络欺凌检测原型系统和（4）第一个标记的社交网络欺凌数据集，用于测试原型和该方向的未来研究。该项目具有很高的风险，因为是否可以开发这样的系统是一个未经测试的想法，并且任务具有挑战性，很大程度上是由于欺凌行为的多样性、模糊性以及欺凌者在社交媒体中使用的特殊语言。该研究项目的结果预计将为未来调查社交媒体网络欺凌问题的更大规模项目奠定基础，最终将使数亿儿童及其他群体的社交互动更加安全。教学、培训和学习将直接促进担任研究助理和程序员的研究生，一些本科生将参与编程。 UCSC 的种族和文化多样性、毗邻硅谷以及 PI 的行业合作将增强其影响力。这项研究的结果，包括生成的数据、出版物和演示软件，将通过项目网站 (http://users.soe.ucsc.edu/~yiz/bullying/) 提供。