1st Place - Asahi Newspaper NLP Competition 2023

*This is a conceptual illustration generated by AI. It may not accurately represent the actual competition or dataset.
1st Place - Asahi Newspaper NLP Competition 2023
Designed predictive models to identify viral news articles on social media using multimodal tabular data (text, images, metadata). Emsemble 3 models below.
- Fine-tuned RoBERTa, which was pretrained by Asahi Newspaper team, for text embeddings. By combining meta information and texts data, I created new text data such as news.
- deep / shallow LightGBM on engineered features:
- Text (e.g., sentiment, headline length, word extraction)
- Social metadata (shares, comments, etc.)
- Achieved top F1 score: 78.39 out of 16 participants
Tools: Python, RoBERTa (Transformers), LightGBM
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