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      Is writing style predictive of scientific fraud?

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          Abstract

          The problem of detecting scientific fraud using machine learning was recently introduced, with initial, positive results from a model taking into account various general indicators. The results seem to suggest that writing style is predictive of scientific fraud. We revisit these initial experiments, and show that the leave-one-out testing procedure they used likely leads to a slight over-estimate of the predictability, but also that simple models can outperform their proposed model by some margin. We go on to explore more abstract linguistic features, such as linguistic complexity and discourse structure, only to obtain negative results. Upon analyzing our models, we do see some interesting patterns, though: Scientific fraud, for examples, contains less comparison, as well as different types of hedging and ways of presenting logical reasoning.

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            Using syntax to disambiguate explicit discourse connectives in text

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              Author and article information

              Journal
              2017-07-13
              Article
              1707.04095
              ffc43ca9-ec9f-4bb6-b9bf-258f712dbf8d

              http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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              To appear in the Proceedings of the Workshop on Stylistic Variation 2017 (EMNLP), 6 pages
              cs.CL

              Theoretical computer science

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