Six degrees of Kevin Bacon : a webinar on graph visualization (and movies)

Watch the video record on-line at


In the 1960’s a scientist called Milgram unveiled the underlying social networks in human societies with a few simple letters. Today it seems networks are everywhere but without tools and techniques to explore them, they remain mysterious. In a coming webinar, we’ll demonstrate how to use Linkurious to find information in the “Hollywood graph” and why Kevin Bacon is the center of the known Universe.

Six degrees of Kevin Bacon

Milgram’s experiments are linked to the small-world phenomenon.  Through a series of experiences, Milgram and other researchers proved that human societies have a short average path between different people. How short? There is a theory called Six degrees of separation according to which everyone and everything is six or fewer steps away, by way of introduction, from any other person in the world. It means that through friends of friends you are connected to everyone on the planet, from Justin Bieber to the most remote villages in the Amazonia. On virtual social networks, it’s quite true : on Facebook the average number of acquaintances between two users is 4,74. So it’s not hard to imagine that in little networks like the world of Hollywood, everyone knows everyone. Movie buffs have actually invented a game around that called Six degrees of Kevin Bacon. The rules are simple : you have to find the connections between an actor and Kevin Bacon via the people they both have played with. The person who finds the shortest path wins!

How to explore graphs

Graph exploration is not just a trivia game though. Financial transaction, logistics systems or telecommunication networks are all real-world example of graphs. Finding abnormal transactions and uncovering the people they involve, dispatching trucks in an efficient way or improving the reliability of a phone network are all problems that involve understanding graphs. But when you don’t have the tools, networks can become mazes.

On Thursday September 05 @ 08:00 PDT / 17:00 CEST, we’ll present a webinar on the exploration of graphs. Make sure to register for the webinar if you have a Neo4j database and want to better understand the data you store or if you’re looking for new ways to explore the underlying networks in your data.

We’ll use the graph of Hollywood actors (and actresses) to show how to use Linkurious to explore Neo4j databases and find valuable insights. Here are some of the topics we’ll discuss :

– how to see the connections of a single node;

– how to explore a graph starting from a local view;

– how to filter and refine your canvas to make it clearer;

– how to run advanced queries;

Here is a short video that gives you a preview of what we’ll be talking about :

Linkurious – Play the Kevin Bacon game from Linkurious on Vimeo.

If there are questions you want to ask or problems you’d like us to talk about, we welcome your feedback. Please share it in the comments section or via the contact page. We’ll either tackle them during the webinar or we’ll get back to you.


Talking about graph visualization in London (27/02)

We will be in London on the 27th to talk about graph visualization.

We will explain why visualization is key to understanding graphs and present some of the options people can use to do so. Of course, we will also talk about Linkurious and why we think it solve some of the common problems with visualization solutions.

Registration is free, you just have to signup here. The event starts at 18:30.

If you are interested by graph and living in London, we would love to see you and talk. Come join us!

We are looking for interesting graph or network datasets : please help us!

We are building a tool to help people understand and visualize graph data. This means that we are always on the lookout for new datasets we can bring the power of graph visualization to. In the coming months we will be participating in conferences, meeting people and writing stuff on this blog. We want to use these opportunities to share interesting stories about the world we live in and we need you for that.

There is something you are curious about? You think there are graph data out there that would be fun to visualize? You want to learn and explore the connections between things? Visualize a particular network? Please share your ideas with us.

We are looking for highly connected data that can be modeled as nodes and links. The easier it is to import it in Neo4j the better.

Currently we are using database in our demo. There are a few other interesting datasets including some that are already prepared for Neo4j (here).  Stanford has a nice collection of large datasets too. If you are curious, you can learn about it here.

You can help us with your suggestions about the data and the stories graph visualization can be used for. If you have ideas you want to share with us you can contact us on twitter (@Linkurious), via mail (contact {at} or just leave a comment below.

We are looking forward hearing from you.

Our first Neo4j meetup : visualizing graphs with Linkurious and Gephi

Hello everyone,

Thursday we were invited by Neo4j France to participate in their monthly meetup. Thank you Cédric for that opportunity. It was a lot of fun.

The meetup was dedicated to the visualization of graphs. Neo4j offers a solution to store and access vast amount of data in graph form. To access and explore this data, it is sometimes easier to visualize it. There are multiple solutions to do that.

Sébastien Heymann presented Gephi, an open-source project he co-founded. Gephi is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs. It runs on Windows, Linux and Mac OS X. It is free and with over 100k downloads for the latest version, Gephi is becoming a standard in network visualization. If you haven’t tried it yet, you definitely should.

The good news for Neo4j users is that they can use Gephi with their data. It’s as simple as downloading a plugin. With that plugin you can load your Neo4j database in Gephi and start exploring it.

What’s even better is that you can use that plugin to export data to a Neo4j format. Gephi is compatible with a lot of formats and comes with tools to sort and clean you data. This means that you can get you data inside Gephi, use it for analysis and export your work to Neo4j. If you want to learn more about it, you can watch that tutorial.

Why would you want to export your data to Neo4j? Because then you can search it with Linkurious! Jean Villedieu presented some of the advantages of that approach. First of all, Linkurious is really simple. We want to make the exploration of graph data a seamless experience. This means that to get a graph of what you are interested in, you just have to type in a search bar. You get access to one or more nodes. You can choose to see what they are linked to. This give you a first graph : it is small and focused on what you searched in the first place. This means that it is easier for you to understand it.

From there, you can start exploring. Just choose the nodes you are interested in and click to expand your graph with the nodes they are linked to.

At any point in time, you can remove nodes, see proprieties and customize your graph.

You can access the Linkurious presentation slides here. Be warned, it’s in French 🙂

We had a lot of fun presenting a live demo of Linkurious and interacting with the great people that were attending. It was really interesting to get feedback on our work and a glimpse at the business needs of graph visualization. We will be working on making Linkurious better and we are looking forward to other opportunities to meet with potential users.


Meetup on graph visualization : join us the 24/01 in Paris

Neo4j, the leading graph database software, will be organizing a meetup on the visualization of graphs. It’s free, if you want to come you just have to register here.

Graph databases are a new way to store and access data by representing it as nodes and connections. It is particularly useful to use highly connected data as social networks, recommendation engines, music discovery or anti-fraud systems do. Graph databases give data scientists exciting opportunities.

We will be presenting Linkurious for the first time and how it can be used to visualize and navigate Neo4j databases.

Sébastien Heymann, the Linkurious CEO, will be also presenting Gephi, an open-source project on graph visualization that he co-founded. Gephi is particularly useful to run network analysis on large graphs. Sébastien will be explaining how to combine Neo4j and Gephi and demonstrating some of the benefits of this approach.

The meetup is open to everyone and registration is free : we hope to see you here!

Linkurious vous aide à visualiser vos graphes de données

Nous sommes ravis d’annoncer le lancement de Linkurious, un outil de visualisation des graphes simple et intuitif qui est maintenant disponible en béta.

L’utilisation des bases de données de graphes est en train de révolutionner la manière dont on stocke et interagit avec les données. Dans un monde hyperconnecté, les graphes permettent d’accéder de manière quasi instantannée à des données complexes et à leurs relations. Recommandation, réseau social, gestion de contenu : Amazon, Linkedin ou Adobe font partie des entreprises qui se servent des graphes pour construire des services innovants et performants.

Les graphes sont partout et nous voulons aider les entreprises à les utiliser. Pour cela, Linkurious propose un outil qui permet de :

  • visualiser le contenu de votre base de données de graphes avec une interface simple, accessible sur un naviguateur internet;
  • simplifier vos recherche avec un moteur de recherche intuitif;
  • se concentrer sur les données qui vous intéressent à l’intérieur de l’ensemble d’un graphe.

La première version de Linkurious est compatible avec la base de données de graphes neo4j. Il suffit de s’inscrire pour commencer à explorer vos données ! Vous n’avez pas de bases de données neo4j mais vous voulez tester Linkurious ? Pas de problèmes : connectez vous et visualiser une partie de la base IMDb. Nous espérons dans les prochains proposer d’autres sources de données (être prévenu du développement de Linkurious).

Vous pouvez utiliser Linkurious en béta pendant les prochains mois. Contactez-nous à si vous voulez en savoir plus.