LIN-IN - LinkedIn Insights

Analyse your LinkedIn connections and messages with some simple data science.

Caution: this is a quick and dirty simple toy project. No warranty!

Features

Upload your LinkedIn data export to receive information about:

• Overview of all your connections
• Companies and positions of your connections
• How your profile developed over time
• A graph of your company network
• A graph of positions within your network
• Overview of all your messages

Lin-In.mp4

Run Locally

Clone the project

  git clone https://github.com/benthecoder/linkedin-visualizer.git

Go to the project directory

  cd lin-in

Using Docker

Build an Image

docker build -t lin-in:0.0.1 .

Run the Image

docker run -p 8501:8501 lin-in:0.0.1

The app is now live on http://localhost:8501/

Using Conda

Create Conda environment

  conda create --name env_name python=3.12.1

Activate the environment

  conda activate env_name

Install requirements

  pip install -r requirements.txt

Run streamlit

  streamlit run app.py

Using Poetry

first make sure you have python 3.12.1

  poetry install

  poetry run streamlit run app.py

Credits

This is an extended fork of Linkedin Visualizer, adding several new functions, extensions, dependency updates (python 12+) and further cleaning. Other sources used:

• Linkedin Analysis
• Linkedin Network Visualization
• Plotly Docs