Abstract
This papers presents a platform for monitoring press narratives with respect to several social challenges, including gender equality, migrations and minority languages. As narratives are encoded in natural language, we have to use natural processing techniques to automate their analysis. Thus, crawled news are processed by means of several NLP modules, including named entity recognition, keyword extraction,document classification for social challenge detection, and sentiment analysis. A Flask powered interface provides data visualization for a user-based analysis of the data. This paper presents the architecture of the system and describes in detail its different components. Evaluation is provided for the modules related to extraction and classification of information regarding social challenges.- Anthology ID:
- 2021.ltedi-1.6
- Volume:
- Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion
- Month:
- April
- Year:
- 2021
- Address:
- Kyiv
- Editors:
- Bharathi Raja Chakravarthi, John P. McCrae, Manel Zarrouk, Kalika Bali, Paul Buitelaar
- Venue:
- LTEDI
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 46–50
- Language:
- URL:
- https://aclanthology.org/2021.ltedi-1.6
- DOI:
- Cite (ACL):
- Iñaki San Vicente, Xabier Saralegi, and Nerea Zubia. 2021. GEPSA, a tool for monitoring social challenges in digital press. In Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, pages 46–50, Kyiv. Association for Computational Linguistics.
- Cite (Informal):
- GEPSA, a tool for monitoring social challenges in digital press (San Vicente et al., LTEDI 2021)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2021.ltedi-1.6.pdf