Stock market analysis using sentiment analysis

Author Reg. ID: TIJER_150803

Published Paper Id: TIJER2403015

Published In: Volume 11 Issue 3, March-2024

Abstract: One of the major problem on twitter is hateful tweets that can be analyzed and can be removed from Twitter in accordance with twitter policies. The Algorithms Exploration explores Unison models and feature extractors. Different learning models are compared, including convolutional and recurrent neural networks. Human decision-making is heavily influenced by emotions. Affective computing takes this fact into account with the intention of adapting decision support to an individual's emotional state. Deep learning can improve performance, but as this study shows, the unique properties of this task include: bidirectional processing, dropout layers as regularization techniques, weighted loss functions, Requires recurrent neural network adaptation. In this case, the network is first trained for another goal, in this case sentiment analysis, and then the output layer is adapted to the emotion detection task.

Keywords: Sentiment Analysis, Cyberbullying, Emotion, Emotion Recognition, Unison model, Feature extractor, Convolutional NeuralNetwork(CNNs), Recurrent Neural Network(RNNs).

Downloads: 00034

Page No: a88-a98

Country: Pune, Maharashtra , India

Research Area: Science and Technology

Published Paper URL: https://tijer.org/TIJER/viewpaperforall?paper=TIJER2403015

Published Paper PDF: https://tijer.org/TIJER/papers/TIJER2403015

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