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Creators/Authors contains: "Peng J. and Leberknight, C."

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  1. ; ; (, Proceedings of The COLING 1st Natural Language Processing for Information Freedom workshop)
    This paper investigates censorship from a linguistic perspective. We collect a corpus of censored and uncensored posts on a number of topics, build a classifier that predicts censorship decisions independent of discussion topics. Our investigation reveals that the strongest linguistic indicator of censored content of our corpus is its readability. 
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    Accepted Manuscript Full Text Available