https://github.com/stevillis/glassdoor-reviews-report
A report analyzing sentiment predictions made by a BERTimbau-based model on Glassdoor reviews of IT Companies in Cuiabá.
https://github.com/stevillis/glassdoor-reviews-report
bert bertimbau glassdoor ml nlp pytorch sentiment-analysis
Last synced: 3 months ago
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A report analyzing sentiment predictions made by a BERTimbau-based model on Glassdoor reviews of IT Companies in Cuiabá.
- Host: GitHub
- URL: https://github.com/stevillis/glassdoor-reviews-report
- Owner: stevillis
- Created: 2024-04-23T01:56:31.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2025-01-10T17:23:10.000Z (10 months ago)
- Last Synced: 2025-01-10T18:33:23.913Z (10 months ago)
- Topics: bert, bertimbau, glassdoor, ml, nlp, pytorch, sentiment-analysis
- Language: Jupyter Notebook
- Homepage: https://glassdoor-reviews-report.streamlit.app/
- Size: 3.87 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Glassdoor Reviews Report
This repository contains a sentiment analysis report of Cuiabá IT Companies' reviews in Glassdoor. It also presents a model that leverages BERT-based architecture, specifically BERTimbau, to predict the sentiment of employee reviews.
The live preview can be found at: [Análise de sentimento em avaliações no Glassdoor: Um estudo sobre empresas de Tecnologia da Informação em Cuiabá](https://glassdoor-reviews-report.streamlit.app/).
⚠️ If you find the app in **sleep mode**, please hit the button **"Yes, get this app back up!"**.
## Application Overview
### [📊 Dashboard](./📊Dashboard.py)
The main entry point of the application that provides a comprehensive analysis of Glassdoor reviews for IT companies in Cuiabá. The dashboard includes:
#### 📊 Key Metrics
- Overall sentiment analysis metrics (positive, negative, neutral)
- Distribution of reviews by sentiment
- Analysis by employee role groups
#### 🏆 Company Rankings
- Positive reviews ranking
- Negative reviews ranking
- Detailed company analysis
#### 📊 Advanced Analysis
- Sentiment trends over time
- Rating distribution analysis
- Word cloud visualizations
- Most common words analysis
- N-gram analysis
## Detailed Pages
### [🏠 Análise Geral](./pages/1_🏠_Análise%20geral.py)
A comprehensive analysis of Glassdoor reviews for IT companies in Cuiabá, including:
- **Introduction**: Overview of the project goals and methodology using BERT-based sentiment analysis
- **Ranking Analysis**:
- Top companies with highest positive reviews
- Companies with most negative feedback
- Detailed company performance metrics
- **Temporal Analysis**: Sentiment trends over time
- **Rating Analysis**: Correlation between star ratings and sentiment scores
- **Employee Role Analysis**: Sentiment distribution across different job functions
- **Text Analysis**:
- Word clouds of most frequent terms
- Top 10 most common words
- N-gram analysis for common phrases
- **Conclusion**: Summary of key findings and insights
### [🥇 Ranking geral de avaliações](./pages/2_🥇_Ranking%20geral%20de%20avaliações.py)
Shows the number of reviews and the associated sentiment for each company, ordered by the difference between positive and negative reviews.
### [📉 Avaliações ao longo do tempo](./pages/3_📉_Avaliações%20ao%20longo%20do%20tempo.py)
Presents a sentiment analysis of reviews along the time by company.
### [⭐ Avaliações por quantidade de estrelas](./pages/4_⭐_Avaliações%20por%20quantidade%20de%20estrelas.py)
Examines how reviews correlate with star ratings for a chosen company.
### [🧑💼 Avaliações por grupo de funcionários](./pages/5_🧑💼_Avaliações%20por%20grupo%20de%20funcionários.py)
Shows reviews categorized by different employee groups for a specific company.
### [☁️ Nuvem de Palavras por empresa](./pages/6_☁️_Nuvem_de_Palavras_por_empresa.py)
Shows Word Cloud by company.
### [📊 Top 10 palavras mais usadas](./pages/7_📊_Top%2010%20palavras%20mais%20usadas.py)
Shows Top 10 frequent words by company.
### [🔠 NGrams](./pages/8_🔠_NGrams.py)
Shows N-Grams by company.
### [🧠 Treinamento do Modelo](./pages/9_🧠_Treinamento%20do%20Modelo.py)
Shows Data Preparation, Model Architecture, Model Training and Model Evaluation.
## How to Run the Application
### Prerequisites
- Python 3.11
1. Clone the repository:
```sh
git clone https://github.com/yourusername/glassdoor-reviews-report.git
cd glassdoor-reviews-report
```
2. Install the required dependencies:
```sh
pip install -r requirements.txt
```
3. Run the Streamlit application:
```sh
streamlit run 📊Dashboard.py
```
4. The application will start and automatically open in your default web browser. If it doesn't, you can access it at `http://localhost:8501`