Unleashed is a Streamlit-powered web app that performs in-depth sentiment analysis and competitive benchmarking of consumer electronics products using customer reviews. Designed for tech enthusiasts, product analysts, and businesses, it transforms raw feedback into actionable insights.
🌐 Live Demo: Click to try the app 📸 Screenshots: See below
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⭕ Overview - Snapshot
Concise overview featuring random examples, word clouds and sentiment counts -
📊 Detailed Sentiment Analysis - The Deep Dive
Deep insights into the data providing a detailed analysis. -
🆚 Competitor Comparison - Competitive Landscape
Compare product sentiment across competing brands in real time. -
🧠 NLP Operations - NLPfication
Instantly receive tokenized, lemmatized, POS, and NER forms of text. -
📈 Analyze Text - Analysis Hub
Analyze text sentiment in real-time or via CSV upload
| Overview | Detailed Analysis | Competitive Analysis | NLP Operations | Analyze Text |
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Run the following commands one by one in your Terminal
# Clone the repo
git clone https://github.com/prachikohlii/Unleashed-Sentiment-Analysis-For-Consumer-Electronics.git
cd Unleashed-Sentiment-Analysis-For-Consumer-Electronics
# Run the app
streamlit run 1_Welcome_Aboard.pyWe use en_core_web_sm for NLP tasks. If needed, download it manually:
python -m spacy download en_core_web_smstreamlit>=1.32
numpy>=1.24,<2.0
pandas>=2.0
matplotlib>=3.7
seaborn
plotly
plotly.express
wordcloud
nltk
spacy>=3.7.2
https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl
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Pull requests and feedback are welcome! For major changes, open an issue first to discuss what you’d like to change.
📧 Reach out on LinkedIn or drop a ⭐ if you like the project!
Check out Project PPT for more info.