Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.16071 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913402457161728 |
|---|---|
| author | Gómez-Rodríguez, Carlos Imran, Muhammad Vilares, David Solera, Elena Kellert, Olga |
| author_facet | Gómez-Rodríguez, Carlos Imran, Muhammad Vilares, David Solera, Elena Kellert, Olga |
| contents | Sentiment analysis is a key technology for companies and institutions to gauge public opinion on products, services or events. However, for large-scale sentiment analysis to be accessible to entities with modest computational resources, it needs to be performed in a resource-efficient way. While some efficient sentiment analysis systems exist, they tend to apply shallow heuristics, which do not take into account syntactic phenomena that can radically change sentiment. Conversely, alternatives that take syntax into account are computationally expensive. The SALSA project, funded by the European Research Council under a Proof-of-Concept Grant, aims to leverage recently-developed fast syntactic parsing techniques to build sentiment analysis systems that are lightweight and efficient, while still providing accuracy and explainability through the explicit use of syntax. We intend our approaches to be the backbone of a working product of interest for SMEs to use in production. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_16071 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Dancing in the syntax forest: fast, accurate and explainable sentiment analysis with SALSA Gómez-Rodríguez, Carlos Imran, Muhammad Vilares, David Solera, Elena Kellert, Olga Computation and Language 68T50 I.2.7 Sentiment analysis is a key technology for companies and institutions to gauge public opinion on products, services or events. However, for large-scale sentiment analysis to be accessible to entities with modest computational resources, it needs to be performed in a resource-efficient way. While some efficient sentiment analysis systems exist, they tend to apply shallow heuristics, which do not take into account syntactic phenomena that can radically change sentiment. Conversely, alternatives that take syntax into account are computationally expensive. The SALSA project, funded by the European Research Council under a Proof-of-Concept Grant, aims to leverage recently-developed fast syntactic parsing techniques to build sentiment analysis systems that are lightweight and efficient, while still providing accuracy and explainability through the explicit use of syntax. We intend our approaches to be the backbone of a working product of interest for SMEs to use in production. |
| title | Dancing in the syntax forest: fast, accurate and explainable sentiment analysis with SALSA |
| topic | Computation and Language 68T50 I.2.7 |
| url | https://arxiv.org/abs/2406.16071 |