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Recode-Hive / machine-learning-repos

A curated list of awesome machine learning frameworks, libraries and software (by language). I
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💡[Feature]: Sentiment analysis of twitter using deep learning (LSTM) . #550

Open Shantnu-singh opened 6 days ago

Shantnu-singh commented 6 days ago

Is there an existing issue for this?

Feature Description

Sentiment analysis using deep learning, particularly with Long Short-Term Memory (LSTM) networks, involves analyzing textual data from Twitter to determine the emotional tone behind the tweets. LSTMs are a type of recurrent neural network (RNN) they are well-suited for understanding the context and nuances in tweet texts to accurately classify sentiments as positive, negative, or neutral.

Use Case

This can be utilized by businesses and organizations to monitor public opinion and brand perception in real-time. For example, a company can analyze tweets mentioning their products or services to keep track of customer satisfaction and identify potential areas for improvement. Additionally, during events or marketing campaigns, sentiment analysis can help track the immediate reactions and adjust strategies accordingly.

Benefits

improved accuracy in sentiment classification due to the model's ability to understand context and manage long term dependencies in text. This leads to more reliable insights into public opinion, allowing businesses to make informed decisions, enhance customer engagement, and quickly respond to negative sentiments to response to potential PR crises.

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Priority

High

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github-actions[bot] commented 6 days ago

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