Short Text Authorship Attribution via Sequence Kernels, Markov Chains and Author Unmasking: An Investigation

@inproceedings{Sanderson2006ShortTA,
  title={Short Text Authorship Attribution via Sequence Kernels, Markov Chains and Author Unmasking: An Investigation},
  author={Conrad Sanderson and Simon G{\"u}nter},
  booktitle={EMNLP},
  year={2006}
}
We present an investigation of recently proposed character and word sequence kernels for the task of authorship attribution based on relatively short texts. Performance is compared with two corresponding probabilistic approaches based on Markov chains. Several configurations of the sequence kernels are studied on a relatively large dataset (50 authors), where each author covered several topics. Utilising Moffat smoothing, the two probabilistic approaches obtain similar performance, which in… CONTINUE READING
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Information theory helps historians

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