Getting Started with Neo4j and Gephi Tool

Neo4j delivers the lightning-fast read and write performance you need, while still protecting your data integrity. It is the only enterprise-strength graph database that combines native graph storage, scalable architecture optimized for speed, and ACID compliance to ensure the predictability of relationship-based queries.

Let Start the demo,

I am using the neo4j browser from its official website. You can check here. Also, you can download it from that website.

For demo purposes, I have used Movies Datasets which are by default available in the neo4j tool. After selecting the dataset I have performed various queries.

Here is the list of movies released in the 1990s:

By using different query we can find the appropriate information like how many labels are there.

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Gephi is a tool for data analysts and scientists keen to explore and understand graphs. … The goal is to help data analysts to make hypotheses, intuitively discover patterns, isolate structure singularities or faults during data sourcing.

You can download gephi tool form here.

In this demo, I have chosen simple lesmiserables.gml dataset and performed some basic gephi operations on it. So let’s get started.

Here import your dataset.

Below is how all the nodes and edges are displayed l after the load of the dataset.

Now we can represent the data in various layouts. In the left pane choose the layout option and choose the layout of your choice and click on Run. In the below image I have chosen the ForceAtlas layout which displays the data in the following form.

Next, we can differentiate the nodes based on various rankings like their In-Degree, Out-Degree, or Degree and show them in different colors. For this in the left pane on the top side choose Nodes->Ranking there choose the ranking like in the below image In-Degree is chosen, where red color nodes have lower in-degree compared to white and Dark grey node has highest in-degree rankings.

Average degree report you see when you click on the run button in the above image.

Thank you :)