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2023 SEMEVAL SemEval 2023

NLP-LISAC at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation

Abstract

AbstractThis paper presents our system and findings for SemEval 2023 Task 9 Tweet Intimacy Analysis. The main objective of this task was to predict the intimacy of tweets in 10 languages. Our submitted model (ranked 28/45) consists of a transformer-based approach with data augmentation via machine translation.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Abdessamad Benlahbib , Hamza Alami , Achraf Boumhidi , Omar Benslimane

Topics

Machine Learning > Core Methods > Regression Machine Learning > Application Areas > Data Augmentation Natural Language Processing > Generation > Language Modeling Machine Learning > Learning Types > Transfer Learning Natural Language Processing > Applications > Sentiment Analysis Deep Learning > Techniques > Transfer Learning

Keywords

transfer learning sentiment analysis machine translation multilingual nlp data augmentation text regression transformer-based approach tweet intimacy analysis
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