SaTC: CORE: Medium: Collaborative: A Linguistically-Informed Approach for Measuring and Circumventing Internet Censorship

互联网审查包括对可以在互联网上公开或查看的信息的限制。根据自由之家的年度网络自由报告，世界上一半以上的互联网用户现在生活在互联网受到审查或限制的地方。然而，互联网自由社区的成员缺乏对在何处以及如何实施审查的全面实时认识。实现此类解决方案的挑战包括但不限于覆盖范围、可扩展性、采用和安全性。该项目探索了一种基于语言的方法来衡量和规避互联网审查。该研究通过从语言分析的角度研究审查检测和规避的混合方法，对这个问题采取了新的视角。该团队开发了衡量互联网审查的新模型，研究使用语言技术规避审查的机制，对审查内容进行通信和社交网络测量。主动感知和自然语言处理技术与机器学习和优化相结合，激发了互联网自由的新研究方向，并产生可供公众使用的新的高质量数据和工具。计算机科学、信息安全、网络分析和语言学之间的这种新的同源关系为反审查技术的发展奠定了基础。该研究通过使用语言中可用的信号对审查现象进行建模和分析，为互联网审查、隐私和在线信息检索以及计算社会科学等多个领域做出了贡献。更广泛的贡献包括通过同行评审出版物、专题课程和研讨会广泛传播研究成果。其他好处包括为研究生和本科生研究人员提供解决困难的跨学科问题的高度实践工作的丰富经验。通过计算机科学和语言学方面的研究培训，在招收少数民族学生方面取得了显着成果。

Internet censorship consists of restrictions on what information can be publicized or viewed on the Internet. According to Freedom House's annual Freedom on the Net report, more than half the world's Internet users now live in a place where the Internet is censored or restricted. However, members of the Internet Freedom community lack comprehensive real-time awareness of where and how censorship is being imposed. The challenges to achieving such a solution include but are not limited to coverage, scalability, adoption, and safety. The project explores a linguistically-informed approach for measuring and circumventing Internet censorship.The research takes a new perspective on the problem by investigating a hybrid method for censorship detection and evasion from the lens of linguistic analysis. The team develops new models to measure Internet censorship, investigates mechanisms to circumvent censorship using linguistic techniques, conducts communication and social network measurements of censored content. Active Sensing and natural language processing techniques, in conjunction with machine learning and optimization, invigorates new research directions in Internet Freedom and produces new high quality data and tools available for public use. This new allogamy between computer science, information security, network analysis and linguistics provides the foundation for evolution of anti-censorship technologies. The research contributes to a number of fields including Internet censorship, privacy and online information retrieval, as well as computational social science by modeling and analyzing the phenomenon of censorship using the signal available in language. The broader contribution includes wide dissemination of the research results via peer-reviewed publications, special topic courses and workshops. Additional benefits include providing graduate and undergraduate researchers with significant experience of highly practical work on a difficult interdisciplinary problem. Significant gains are obtained in recruitment of minority students through research training in computer science and linguistics.