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Found 4 papers, 1 papers with code
Emotions are Universal: Learning Sentiment Based Representations of Resource-Poor Languages using Siamese Networks
Machine learning approaches in sentiment analysis principally rely on the abundance of resources.
Contrastive Learning of Emoji-based Representations for Resource-Poor Languages
The model learns the representations of resource-poor and resource-rich language in a common emoji space by using a similarity metric based on the emojis present in sentences from both languages.
Sentiment Analysis of Code-Mixed Languages leveraging Resource Rich Languages
Code-mixed data is an important challenge of natural language processing because its characteristics completely vary from the traditional structures of standard languages.
Neural Network Architecture for Credibility Assessment of Textual Claims
CREDO consists of different modules for capturing various features responsible for the credibility of an article.
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