@inproceedings{3424abed4e4f46fdab5e0408185e41e5,
title = "Leveraging NLP and social network analytic techniques to detect censored Keywords: System design and experiments",
abstract = "Internet regulation in the form of online censorship and Internet shutdowns have been increasing over recent years. This paper presents a natural language processing (NLP) application for performing cross country probing that conceals the exact location of the originating request. A detailed discussion of the application aims to stimulate further investigation into new methods for measuring and quantifying Internet censorship practices around the world. In addition, results from two experiments involving search engine queries of banned keywords demonstrates censorship practices vary across different search engines. These results suggest opportunities for developing circumvention technologies that enable open and free access to information.",
author = "Christopher Leberknight and Anna Feldman",
note = "Funding Information: The work is supported by the National Science Foundation under Grant No.: 1704113, Division of Computer and Networked Systems, Secure & Trustworthy Cyberspace (SaTC). Publisher Copyright: {\textcopyright} 2019 IEEE Computer Society. All rights reserved.; null ; Conference date: 08-01-2019 Through 11-01-2019",
year = "2019",
language = "English",
series = "Proceedings of the Annual Hawaii International Conference on System Sciences",
publisher = "IEEE Computer Society",
pages = "2872--2879",
editor = "Bui, {Tung X.}",
booktitle = "Proceedings of the 52nd Annual Hawaii International Conference on System Sciences, HICSS 2019",
}