Tweet Text
Tweet text analysis focuses on understanding the content and context of tweets for various applications, ranging from sentiment analysis and fake news detection to predicting user engagement and classifying topics. Current research heavily utilizes deep learning models, particularly transformer-based architectures like BERT and its variants, along with other techniques such as graph neural networks and LSTMs, to analyze textual and multimodal data (including images and emojis). This field is significant for its potential to improve social media monitoring, enhance public health surveillance (e.g., tracking disease outbreaks), and facilitate more nuanced understanding of online political discourse and public opinion.
Papers
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