  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.
