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
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 669–674
- Language:
- URL:
- https://aclanthology.org/E17-2106
- DOI:
- 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)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/E17-2106.pdf