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The purpose of this project is to identify main topics in personal Twitter timelines

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bertini36/profiler

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Build Status Requirements Status Coverage Status License: MIT

bertini36/profiler 📖

Installation   •  Commands   •  Algorithm settings   •  Post

Profiler tries to identify main topics in personal Twitter timelines using LDA topic models algorithm in a easy way for simple exploratory purposes

⚙️ Environment Setup

🐳 Required tools

  1. Install Docker and Docker Compose
  2. Clone this project: git clone https://github.com/bertini36/profiler
  3. Move to the project folder: profiler

🚀 Usage

  1. Install all the dependencies and bring up the project with Docker executing: make build
  2. cp .env-sample .env
  3. Add your Twitter keys at .env
  4. If you require it, customize some algorithm technical configs at src/settings.py
  5. Run an inference: make run timelines=pablocasado_ topics=3
  6. HTML outputs will be generated at output folder. Open them with your navigator

📈 Results screenshot


— Built with ❤️ from Mallorca —

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The purpose of this project is to identify main topics in personal Twitter timelines

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