This is a graph of Peertube instances following each other. There are 942 nodes and 10067 edges.

Eigenvector centrality

On Peertube, an instance X can follow an instance Y to let its users see all the videos posted on Y. This graph is a directed graph.

Color and size of nodes depends on how big their Eigenvector centrality is. Nodes which have 0 centrality are blue and small, nodes with bigger centrality are big and red.

What centrality represents? Instances which are not followed by anyone have 0 centrality. Instances (A) with a lot of followers (B) have bigger centrality. If those followers (B) themselves have followers ©, it means centrality of A will be even higher.

Does it mean anything in context of Peertube? I’m not sure. Considering chain of three instances: (A) <- (B) <- ©, when (A) posts a video, does it appear in ©? Probably not. But if it was so, then centrality would’ve mean this: Videos posted on instances with high centrality spread across entire network, while videos posted on instances with 0 centrality are not visible anywhere else.

Here are top 10 instances and their centrality:

How to repeat this graph visualization

  1. Download latest Peertube instances.csv and interactions.csv files here: https://www.kaggle.com/datasets/marcdamie/fediverse-graph-dataset-reduced
  2. Import them to Gephi;
  3. Apply Giant Component filter to remove nodes which are not connected to biggest network;
  4. Apply ForceAtlas 2 layout;
  5. Run Eigenvector centrality Statistics (directed). It will add a new column to nodes table;
  6. Apply Nodes - Color - Ranking - Eigenvector centrality;
  7. Apply Nodes - Size - Ranking - Eigenvector centrality;
  8. Configure Preview and export.

Gephi

P.S. On colorful image used as thumbnail of this post nodes are colored by Modularity (community detection).

  • TacoEvent@lemmy.zipEnglish
    4·
    2 months ago

    This is really cool. I feel like people tend to want to gather some sort of critical insight from these graph visualizations but I just enjoy taking in the shape of this data.

    Any particular explanation for the topmost featured graph?

    • podbrushkin@mander.xyzOPEnglish
      4·
      2 months ago

      Not really, I don’t see no well-defined communities (except for those little green guys at the bottom). If there were real clusters, they would’ve been visible by mere placement of nodes, without the need for coloring them. Originally, it was communities which I hoped to discover. Well, to the left there are several groups of yellow nodes - when I was inspecting them closely, I’ve noticed they are grouped not because they’re connected to each other, but because they follow and they are followed by same set of nodes. That was the reason they “gravitated” to each other.

  • plantteacher@mander.xyzEnglish
    2·
    26 days ago

    I LOVE that you show people how it’s done. I wish more posts included the reproduction steps.

    Gephi is not in the official Debians repos (bummer!). Installing tarballs creates a maintenance burden for Debian upgrades. So I wonder what Gephi does considering it seems to use graphviz. Graphviz is in the official Debian repos, but nothing I have made with graphviz looks like your art. So would you say Gephi is an essential extra layer to get your effects?

    • podbrushkin@mander.xyzOPEnglish
      2·
      23 days ago

      Why do you think Gephi is using Graphviz? I think it does not. In graphviz there is no Giant Component filter and no centrality statistics, which are part of graph theory. Gephi is closer to graph theory than graphviz is. Graphviz does have some good node placement algorithms, but in general these apps have different scope. Graphviz is a no go for this purpose.

      Gephi, NetworkX or iGraph - pick single one of these and it will be a single tool you need to repeat steps in the post and achieve similar result. But latter two are programming libraries. Managing to get and launch Gephi probably worth the hassle.

      • plantteacher@mander.xyzEnglish
        1·
        10 days ago

        Why do you think Gephi is using Graphviz?

        I don’t get on here often so now I have forgotten what gave me that impression.

        Gephi, NetworkX or iGraph

        Thanks for the tip! Debian officially has a r-cran-igraph pkg, so perhaps I should start by tinkering with that.

  • Meldrik@lemmy.wtfEnglish
    2·
    2 months ago

    This looks really awesome. If an instance is following a lot of other instances, that will make it small and blue on the chart, yes? That’s why I can’t find my instance? 😅

    • podbrushkin@mander.xyzOPEnglish
      3·
      2 months ago

      No, outgoing follows don’t affect color or size, only incoming (how many instances follow you and if they’re important or not). What’s the name of your instance? I will take a look later. Or you can try finding PeerTube instances.csv file on Kaggle (link in the post) and try checking yourself if your instance is in the dataset. To download a file account is needed, but you can search through specific column by clicking on header.