Convolutional Neural Networks for Authorship Attribution of Short Texts

Prasha Shrestha, Sebastian Sierra, Fabio González, Manuel Montes, Paolo Rosso, Thamar Solorio


Abstract
We present a model to perform authorship attribution of tweets using Convolutional Neural Networks (CNNs) over character n-grams. We also present a strategy that improves model interpretability by estimating the importance of input text fragments in the predicted classification. The experimental evaluation shows that text CNNs perform competitively and are able to outperform previous methods.
Anthology ID:
E17-2106
Volume:
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
Month:
April
Year:
2017
Address:
Valencia, Spain
Editors:
Mirella Lapata, Phil Blunsom, Alexander Koller
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
669–674
Language:
URL:
https://aclanthology.org/E17-2106
DOI:
Bibkey:
Cite (ACL):
Prasha Shrestha, Sebastian Sierra, Fabio González, Manuel Montes, Paolo Rosso, and Thamar Solorio. 2017. Convolutional Neural Networks for Authorship Attribution of Short Texts. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 669–674, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Convolutional Neural Networks for Authorship Attribution of Short Texts (Shrestha et al., EACL 2017)
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PDF:
https://aclanthology.org/E17-2106.pdf