https://github.com/seyha1007/amazon-reviews-analysis
🧐 This project analyzes Amazon Fine Food Reviews to investigate whether negative reviews are more emotionally intense and lexically repetitive than positive ones. Using R, we apply sentiment analysis and lexical diversity metrics to uncover patterns in consumer review language.
https://github.com/seyha1007/amazon-reviews-analysis
acp amazon-reviews bert data-analytics glove jupyter-notebook lstm-sentiment-analysis machine-learning nltk random-forest scikit-learn sentiment-classification sentimental-analysis support-vector-machine
Last synced: about 2 months ago
JSON representation
🧐 This project analyzes Amazon Fine Food Reviews to investigate whether negative reviews are more emotionally intense and lexically repetitive than positive ones. Using R, we apply sentiment analysis and lexical diversity metrics to uncover patterns in consumer review language.
- Host: GitHub
- URL: https://github.com/seyha1007/amazon-reviews-analysis
- Owner: Seyha1007
- License: mit
- Created: 2025-04-13T03:12:25.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-04-14T20:00:58.000Z (about 1 year ago)
- Last Synced: 2025-04-14T20:23:14.409Z (about 1 year ago)
- Topics: acp, amazon-reviews, bert, data-analytics, glove, jupyter-notebook, lstm-sentiment-analysis, machine-learning, nltk, random-forest, scikit-learn, sentiment-classification, sentimental-analysis, support-vector-machine
- Language: R
- Size: 193 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0