GitHub / abhishekjoshi007 / A-Multi-Modal-Transformer-Architecture-Combining-Sentiment-Dynamics-Temporal-Market-Data

Our approach uniquely fuses sentiment dynamics from social media and news sources with temporal market data and macroeconomic indicators to construct dynamic graph representations of interfirm relationships. Further, we employ state-of-the-art GNNs, such as temporal graph convolutions, that adapt to the changing market and significantly enhance it.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abhishekjoshi007%2FA-Multi-Modal-Transformer-Architecture-Combining-Sentiment-Dynamics-Temporal-Market-Data
PURL: pkg:github/abhishekjoshi007/A-Multi-Modal-Transformer-Architecture-Combining-Sentiment-Dynamics-Temporal-Market-Data

Topics: graphneuralnetwork, ieee, multimodal-deep-learning, stock-data, stock-prediction, stock-price-prediction

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