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RahemetGisho/fintech-review-analytics

Domaine:

natural language processingsocioeconomic
Créateur:
Rah
Hôte:
Customer review analytics pipeline for Ethiopian mobile banking apps, using NLP, sentiment analysis, thematic extraction, and PostgreSQL to generate actionable business insights from Google Play Store data. # Fintech Review Analytics Customer Experience Analytics for Ethiopian Fintech Applications using Google Play Store Reviews. --- # 📌 Project Overview This project analyzes customer reviews from Ethiopian banking applications on the Google Play Store and transforms raw customer feedback into actionable business insights using: - Web Scraping - Data Preprocessing - Sentiment Analysis - Thematic Analysis - PostgreSQL Database Engineering - Data Visualization & Business Insights The project focuses on three Ethiopian banks: - Commercial Bank of Ethiopia (CBE) - Bank of Abyssinia (BOA) - Dashen Bank --- # 📁 Project Structure ```text fintech-review-analytics/ ├── .github/ │ └── workflows/ │ └── unittests.yml ├── data/ │ ├── raw/ │ ├── processed/ │ └── analyzed/ ├── notebooks/ │ ├── task2_analysis.ipynb │ └── task4_insights.ipynb ├── sql/ │ ├── schema.sql │ └── verification_queries.sql ├── src/ │ ├── scraper.py │ ├── preprocess.py │ ├── sentiment_analysis.py │ ├── theme_analysis.py │ ├── nlp_pipeline.py │ ├── db_connection.py │ └── load_to_postgres.py ├── tests/ ├── requirements.txt └── README.md ``` --- # 🛠️ Technologies Used ## Programming & Data Processing - Python - pandas - NumPy ## Web Scraping - google-play-scraper ## NLP & Machine Learning - Hugging Face Transformers - DistilBERT - NLTK - scikit-learn ## Database Engineering - PostgreSQL - SQLAlchemy - psycopg2 ## Visualization - Matplotlib - Seaborn - WordCloud ## Development Tools - Git & GitHub - Jupyter Notebook - VS Code - GitHub Actions --- # 🗂️ Task 1 — Data Collection & Preprocessing ## 🎯 Objective - Scrape Google Play Store reviews - Clean and preprocess customer feedback - Prepare analysis-ready dataset --- # 📊 Data Collection Reviews were collected using the `google-play-scraper` Python library. ## Target Applications | Bank | App ID | | ------ | ------------------------------ | | CBE | `com.combanketh.mobil …

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