Document Type
Conference Proceeding
Publication Date
1-1-2019
Journal / Book Title
Proceedings of the Annual Hawaii International Conference on System Sciences
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.
Montclair State University Digital Commons Citation
Leberknight, Christopher S. and Feldman, Anna, "Leveraging NLP and social network analytic techniques to detect censored Keywords: System design and experiments" (2019). Department of Computer Science Faculty Scholarship and Creative Works. 678.
https://digitalcommons.montclair.edu/compusci-facpubs/678
Rights
CC BY-NC-ND 4.0