Abstract
Language processing architectures are often evaluated in near-to-perfect conditions with respect to processed content. The tools which perform sufficiently well on electronic press, books and other type of non-interactive content may poorly handle littered, colloquial and multilingual textual data which make the majority of communication today. This paper aims at investigating how Polish Twitter data (in a slightly controlled ‘political’ flavour) differs from expectation of linguistic tools and how they could be corrected to be ready for processing by standard language processing chains available for Polish. The setting includes specialised components for spelling correction of tweets as well as hashtag and username decoding.- Anthology ID:
- W17-2215
- Volume:
- Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Beatrice Alex, Stefania Degaetano-Ortlieb, Anna Feldman, Anna Kazantseva, Nils Reiter, Stan Szpakowicz
- Venue:
- LaTeCH
- SIG:
- SIGHUM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 115–125
- Language:
- URL:
- https://aclanthology.org/W17-2215
- DOI:
- 10.18653/v1/W17-2215
- Cite (ACL):
- Maciej Ogrodniczuk and Mateusz Kopeć. 2017. Lexical Correction of Polish Twitter Political Data. In Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 115–125, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Lexical Correction of Polish Twitter Political Data (Ogrodniczuk & Kopeć, LaTeCH 2017)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/W17-2215.pdf