You can find the slides of our speakers below:
• Alexis Dutot, Linkfluence
At Linkfluence, we analyze millions of social media posts per day in more than 60 languages. This represents thousands of noisy user-generated documents per second passing through our internal enrichment pipeline. This volume combined with the real-time constraint prevents us from using cross lingual BERT-like models.
In this talk we will focus on multilingual sentiment analysis and emotion detection tasks based on social media data. Only a few annotated corpora tackle these tasks and the vast majority of them is dedicated to the English language. We will see how we fully exploit the potential of emojis as a universal expression of sentiment and emotion in order to build accurate sentiment analysis and emotion detection “real-time” deep learning systems in several languages using solely English annotated corpora.
• Benoît Lebreton, Sacha Samama and Tom Stringer, Quantmetry
Melusine is an open source library developed by Quantmetry and MAIF. The talk focuses on technical issues raised by Melusine’s open source implementation, as well as underlying neural models and algorithms that are being leveraged.