TwitterSentix
Analyzing Twitter Sentiments with Deep Learning
Created on 19th November 2023
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TwitterSentix
Analyzing Twitter Sentiments with Deep Learning
The problem TwitterSentix solves
The sentiment analysis of tweets project solves the challenge of efficiently understanding and analyzing public sentiment on Twitter. It offers real-time insights into opinions on diverse topics, aids in brand reputation management, supports crisis monitoring, facilitates cost-effective market research, analyzes political opinions, and evaluates the effectiveness of social media campaigns.
Challenges we ran into
- Dealing with imbalanced sentiment data was a significant challenge. The dataset contained a disproportionate number of positive and negative sentiments, leading to biased model predictions.
- Training a deep learning model, particularly an LSTM network, demanded substantial computational resources. We faced limitations, including long training times and potential memory issues.
- Integrating the sentiment analysis model into the frontend seamlessly presented challenges. Coordinating data flow and ensuring real-time updates without compromising user experience required careful consideration.
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