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Twitter Sentiment Analysis
My cutting-edge Twitter Sentiment Analysis Web-App leverages the power of Neural Networks to provide real-time sentiment analysis of live tweets fetched via the Twitter API. By incorporating advanced deep learning techniques, my app enables users to gain unparalleled insights into public sentiments and emotions related to any topic of interest.
At the core of my app is a meticulously crafted Neural Network model that has been trained on a vast collection of ~1.6 million tweets. The model's architecture uses Convolutional layer along with a LSTM layer. This design enables the model to effectively learn and extract patterns from the textual data, capturing the subtle nuances and context of each tweet. The impressive 80% accuracy attained during training showcases the model's proficiency in sentiment classification.
With my app, users can enjoy real-time sentiment analysis on live tweets fetched via the Twitter API. The model rapidly processes each tweet, assigning accurate sentiment scores that reflect the emotions and opinions expressed by the Twitter community. This real-time functionality ensures that users receive up-to-date sentiment insights on their chosen topics, facilitating timely and data-driven decision-making.