EAGER: Detecting and Tracking Cyber Bullying on the Social Web

由于许多儿童与同龄人建立联系，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的问题，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（教师、家长、执法人员、社交网站版主等）的干预。是关键然而，许多受害者不会向成年人报告欺凌事件，欺凌者可以使用别名并匿名行事，因此很难识别。 这个探索性项目的目标是通过开发一个智能系统来自动检测和跟踪社交网络上的网络欺凌行为，消除或至少减少这些问题。该项目探索基于机器学习、自然语言处理、信息过滤、推荐和社交网络建模技术相结合的网络欺凌解决方案。该项目的预期结果包括：（1）可以自动检测网络欺凌和欺凌信息的算法;（2）表明预测准确性的试验结果;（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，用于测试原型和未来的研究。该项目具有很高的风险，因为是否可以开发这样一个系统是一个未经测试的想法，任务是具有挑战性的，主要是由于欺凌行为的多样性，模糊性，以及欺凌者在社交媒体上使用的特殊语言。该研究项目的结果预计将为未来调查社交媒体中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人的社交互动更加安全。教学，培训和学习将直接促进研究生谁担任研究助理和程序员，和几个本科生将有助于编程。UCSC的种族和文化多样性，其靠近硅谷以及PI的行业合作将加强其影响。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/bullyiz/bullying/）提供。

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/).