Characterizing the interactions between politicians and voters in the era of social media.
Keywords: Twitter | Natural Language Processing | Deep Learning | Graph theory
Project coordinator: Stefanie Bailer
CeDA collaborator: Sébastien Boyer
- Characterizing the different flavors of interactions (positive, negative, offensive, etc...) between politicians and the general public on social media.
- Multilingual context dependent word embedding for sentences classification.
- Graph representation of social media interaction.
- Transformer-based Deep Neural Networks: Multilingual BERT or XML-RoBERTa.
- Graph Convolutional Neural Networks.