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exporter.ts
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exporter.ts
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import { MultiDirectedGraph } from "graphology";
import forceAtlas2 from "./graphology-layout-forceatlas2/index.js";
import circular from "graphology-layout/circular";
import * as fs from "fs";
import louvain from "graphology-communities-louvain";
interface Edge {
source: string;
target: string;
weight: number;
}
interface Node {
did: string;
handle: string;
}
interface IndexNode {
key: number;
did: string;
label: string;
}
interface Cluster {
label?: string;
idx: string;
dbIndex?: number;
x?: number;
y?: number;
color?: string;
prio?: number;
size: number;
representative?: string;
positions: { x: number; y: number }[];
}
interface ClusterRepPrio {
label: string;
prio: number;
dbIndex: number;
}
const clusterRepresentatives: Map<string, ClusterRepPrio> = new Map();
clusterRepresentatives.set("yui.bsky.social", {
label: "Japanese Language Cluster",
prio: 5,
dbIndex: 500,
});
clusterRepresentatives.set("shahbazi.bsky.social", {
label: "Persian Language Cluster",
prio: 5,
dbIndex: 504,
});
clusterRepresentatives.set("ritzdays.net", {
label: "Korean Language Cluster",
prio: 5,
dbIndex: 506,
});
clusterRepresentatives.set("livialamblet.com", {
label: "Brasil Supercluster",
prio: 5,
dbIndex: 502,
});
clusterRepresentatives.set("hoax.bsky.social", {
label: "Brasilian Swiftie Subcluster",
prio: 4,
dbIndex: 516,
});
clusterRepresentatives.set("vedat.bsky.social", {
label: "Turkish Language Minicluster",
prio: 4,
dbIndex: 515,
});
clusterRepresentatives.set("awhurst.bsky.social", {
label: "Web3",
prio: 4,
dbIndex: 510,
});
// clusterRepresentatives.set("wesbos.com", {
// label: "Front-end Developers",
// prio: 3,
// });
clusterRepresentatives.set("pfrazee.com", {
label: "BSky English Language Metacluster",
prio: 5,
dbIndex: 501,
});
clusterRepresentatives.set("nori.gay", {
label: "Hellthread Metacluster",
prio: 4,
dbIndex: 505,
});
clusterRepresentatives.set("andy.wrestlejoy.com", {
label: "Wrestling Subcluster",
prio: 3,
dbIndex: 508,
});
clusterRepresentatives.set("johnmichiemusic.com", {
label: "Musician Subcluster",
prio: 3,
dbIndex: 509,
});
// clusterRepresentatives.set(
// "deepfates.com.deepfates.com.deepfates.com.deepfates.com.deepfates.com",
// {
// label: "TPOT",
// prio: 4,
// dbIndex: 507,
// }
// );
clusterRepresentatives.set("estrogenempress.gay", {
label: "Trans + Queer Shitposters",
prio: 4,
dbIndex: 503,
});
// clusterRepresentatives.set("itguyry.com", "BIPOC in Tech");
clusterRepresentatives.set("yap.zone", {
label: "Furries",
prio: 3,
dbIndex: 511,
});
clusterRepresentatives.set("maureenbug.bsky.social", {
label: "Squid Cluster",
prio: 3,
dbIndex: 512,
});
clusterRepresentatives.set("mathan.dev", {
label: "Ukrainian Cluster",
prio: 3,
dbIndex: 518,
});
clusterRepresentatives.set("swamilee.xyz", {
label: "Italian Cluster",
prio: 3,
dbIndex: 519,
});
clusterRepresentatives.set("muffinchips.bsky.social", {
label: "Gay Himbo Cluster",
prio: 3,
dbIndex: 520,
});
clusterRepresentatives.set("jonasnuts.bsky.social", {
label: "Portugal Cluster",
prio: 3,
dbIndex: 521,
});
clusterRepresentatives.set("alicekeeler.com", {
label: "Education Cluster",
prio: 2,
dbIndex: 522,
});
let filteredHandles = ["mattyglesias.bsky.social", "berduck.deepfates.com"];
// log logs a message with a timestamp in human-readale format
function log(msg: string) {
console.log(`${new Date().toLocaleString()}: ${msg}`);
}
async function fetchGraph() {
log("Loading graph...");
const data = fs.readFileSync("graph.tsv", "utf8");
const lines = data.split("\n").filter((line) => line.trim() !== "");
const nodesMap: Map<string, Node> = new Map();
const edges: Edge[] = [];
log("Fetching opted out authors...");
const optedOutAuthorsResp = await fetch(
"https://bsky-search.jazco.io/opted_out_authors"
);
const optedOutAuthorsJSON = await optedOutAuthorsResp.json();
filteredHandles = filteredHandles.concat(
optedOutAuthorsJSON.authors.map((author: any) => author.handle)
);
log(`Filtered handle count ${filteredHandles.length}`);
log("Parsing graph file...");
lines.forEach((line, _) => {
const [source, sourceHandle, target, targetHandle, weight] =
line.split("\t");
if (
filteredHandles.includes(sourceHandle) ||
filteredHandles.includes(targetHandle)
) {
return;
}
const parsedWeight = parseFloat(weight);
if (source !== target && parsedWeight > 2) {
const sourceNode = { did: source, handle: sourceHandle };
if (!nodesMap.has(source) && source !== "" && sourceHandle !== "") {
nodesMap.set(source, sourceNode);
} else if (source === "" || sourceHandle === "") {
return;
}
const targetNode = { did: target, handle: targetHandle };
if (!nodesMap.has(target) && target !== "" && targetHandle !== "") {
nodesMap.set(target, targetNode);
} else if (target === "" || targetHandle === "") {
return;
}
edges.push({
source,
target,
weight: parsedWeight,
});
}
});
// Sort the nodes by did so that the order is consistent
const nodes: Node[] = Array.from(nodesMap.values()).sort((a, b) => {
if (a.did < b.did) {
return -1;
} else if (a.did > b.did) {
return 1;
} else {
return 0;
}
});
log("Done parsing graph response");
return { edges: edges, nodes };
}
// If "enriched" is set, leave DIDs in the node data
log("Starting exporter...");
fetchGraph().then((graphData: { edges: Edge[]; nodes: Node[] }) => {
const { edges, nodes } = graphData;
// Create the graph
const graph = new MultiDirectedGraph();
const totalEdges = edges.length;
const totalNodes = nodes.length;
const indexNodes: Map<string, IndexNode> = new Map();
log("Adding nodes...");
for (let i = 0; i < totalNodes; i++) {
if (i % 1000 === 0) {
log(`Adding node ${i} of ${totalNodes - 1}`);
}
const node = nodes[i];
const indexNode = {
key: i,
did: node.did,
label: node.handle,
};
const graphNode = {
key: i,
label: node.handle,
did: node.did,
};
graph.addNode(i, graphNode);
indexNodes.set(node.did, indexNode);
}
log("Done adding nodes");
// Create a map of edges for quick reverse lookups
const edgeMap: Map<string, Edge> = new Map();
for (let i = 0; i < totalEdges; i++) {
const edge = edges[i];
edgeMap.set(`${edge.source}-${edge.target}`, edge);
}
// First, find the minimum and maximum weights in the graph
let minWeight = Infinity;
let maxWeight = -Infinity;
let totalWeight = 0;
for (let i = 0; i < totalEdges; i++) {
const edge = edges[i];
minWeight = Math.min(minWeight, edge.weight);
maxWeight = Math.max(maxWeight, edge.weight);
totalWeight += edge.weight;
}
const logMinWeight = Math.log(minWeight);
const logMaxWeight = Math.log(maxWeight);
const minEdgeSize = 0.2;
const maxEdgeSize = 4;
log("Adding edges...");
// Then, set the size of each edge based on its weight relative to the min and max weights
for (let i = 0; i < totalEdges; i++) {
if (i % 1000 === 0) {
log(`Adding edge ${i} of ${totalEdges - 1}`);
}
const edge = edges[i];
let weight = edge.weight;
const partnerEdge = edgeMap.get(`${edge.target}-${edge.source}`);
if (partnerEdge !== undefined) {
const bothEdgeWeight = edge.weight + partnerEdge.weight;
const mutualityFactor =
(edge.weight / bothEdgeWeight) * (partnerEdge.weight / bothEdgeWeight);
weight =
mutualityFactor * bothEdgeWeight * (1 + Math.log(bothEdgeWeight));
}
// Calculate the size based on the logarithm of the edge weight relative to the range of weights
const size =
minEdgeSize +
((Math.log(weight) - logMinWeight) / (logMaxWeight - logMinWeight)) *
(maxEdgeSize - minEdgeSize);
graph.addEdge(
indexNodes.get(edge.source)?.key,
indexNodes.get(edge.target)?.key,
{
ogWeight: edge.weight,
weight: parseFloat(weight.toFixed(2)),
size: parseFloat(size.toFixed(2)),
}
);
}
log("Filtering edges...");
// Reduce all edges to the top 10 outbound edges for each node
graph.forEachNode((node, attrs) => {
const edges = graph.outEdges(node);
const sortedEdges = edges.sort((a, b) => {
return (
graph.getEdgeAttribute(b, "weight") -
graph.getEdgeAttribute(a, "weight")
);
});
const topEdges = sortedEdges.slice(0, 10);
const topEdgeSet = new Set(topEdges);
edges.forEach((edge) => {
if (!topEdgeSet.has(edge)) {
graph.dropEdge(edge);
}
});
});
log(`Graph has ${graph.order} nodes and ${graph.size} edges.`);
log("Done adding edges");
const degrees = graph.nodes().map((node) => graph.degree(node));
const minDegree = degrees.reduce((a, b) => Math.min(a, b));
const maxDegree = degrees.reduce((a, b) => Math.max(a, b));
const skyBluePalette = [
"#009ACD", // DeepSkyBlue3
"#5B9BD5", // CornflowerBlue
"#7EC0EE", // SkyBlue2
"#87CEFA", // LightSkyBlue1
"#4A708B", // SkyBlue4
"#1E90FF", // DodgerBlue
"#00BFFF", // DeepSkyBlue
"#3CB371", // MediumSeaGreen
"#FF7F50", // Coral
"#FF4500", // OrangeRed
];
const minSize = 1.5,
maxSize = 15;
log("Assigning attributes...");
graph.forEachNode((node) => {
const degree = graph.inDegreeWithoutSelfLoops(node);
// Set the size based on the degree of the node relative to the min and max degrees
let newNodeSize =
minSize +
Math.sqrt((degree - minDegree) / (maxDegree - minDegree)) *
(maxSize - minSize);
// Calculate the radius of the circle based on the size
let radius = newNodeSize / 2;
// Calculate the area of the circle based on the radius
let area = Math.PI * radius * radius;
// Round to 2 decimal places to conserve bits in the exported graph
newNodeSize = parseFloat(newNodeSize.toFixed(2));
area = parseFloat(area.toFixed(2));
graph.setNodeAttribute(node, "size", newNodeSize);
graph.setNodeAttribute(node, "area", area);
// Set a random color
graph.setNodeAttribute(
node,
"color",
skyBluePalette[Math.floor(Math.random() * 10)]
);
});
// Log total number of nodes, edges, and graph weight
log(
`Users: ${graph.order.toLocaleString()} Connections: ${graph.size.toLocaleString()} Interactions: ${totalWeight.toLocaleString()}`
);
log("Assigning layout...");
circular.assign(graph);
const settings = forceAtlas2.inferSettings(graph);
const iterationCount = 600;
log(`Running ${iterationCount} Force Atlas simulations...`);
forceAtlas2.assign(graph, { settings, iterations: iterationCount });
log("Done running Force Atlas");
log("Assigning community partitions...");
// To directly assign communities as a node attribute
louvain.assign(graph, {
resolution: 1.18,
});
log("Done assigning community partitions");
// initialize clusters from graph data
const communityClusters: { [key: string]: Cluster } = {};
graph.forEachNode((_, atts) => {
const idx = atts.community;
// If this node is in a community that hasn't been seen yet, create a new cluster
if (!communityClusters[idx]) {
communityClusters[idx] = {
idx: idx,
positions: [],
size: 1,
};
} else {
// Otherwise, increment the size of the cluster
communityClusters[idx].size++;
}
const repClusterPrio = clusterRepresentatives.get(atts.label);
// If this node is the representative of its cluster, set the cluster representative
if (repClusterPrio !== undefined) {
// If the cluster already has a representative, check if this rep's cluster has a higher priority
const currentPrio = communityClusters[idx].prio;
if (currentPrio === undefined || repClusterPrio.prio > currentPrio) {
communityClusters[idx].representative = atts.label;
communityClusters[idx].prio = repClusterPrio.prio;
communityClusters[idx].label = repClusterPrio.label;
communityClusters[idx].dbIndex = repClusterPrio.dbIndex;
}
}
});
// Drop any clusters with fewer than 50 members, remove the cluster assignment from any nodes in those clusters
for (const community in communityClusters) {
if (communityClusters[community].size < 50) {
graph.updateEachNodeAttributes((_, atts) => {
if (atts.community === community) {
delete atts.community;
}
return atts;
});
delete communityClusters[community];
}
}
log("Truncating node position assignments...");
// Reduce precision on node x and y coordinates to conserve bits in the exported graph
graph.updateEachNodeAttributes((_, attrs) => {
attrs.x = parseFloat(attrs.x.toFixed(2));
attrs.y = parseFloat(attrs.y.toFixed(2));
return attrs;
});
log("Done truncating node position assignments");
graph.forEachNode((_, atts) => {
if (atts.community === undefined || atts.community === null) return;
const cluster = communityClusters[atts.community];
if (cluster === undefined) return;
cluster.positions.push({ x: atts.x, y: atts.y });
});
// Filter positions that are 2 standard deviations away from the mean and compute the barycenter of each cluster
for (const community in communityClusters) {
let x_positions = communityClusters[community].positions.map((p) => p.x);
let y_positions = communityClusters[community].positions.map((p) => p.y);
log(`Processing community ${communityClusters[community].label}...`);
if (x_positions.length === 0 || y_positions.length === 0) {
log(`Skipping community ${communityClusters[community].label}...`);
continue; // Skip this community if it has no positions
}
const mean_x =
x_positions.reduce((acc, x) => acc + x, 0) / x_positions.length;
const mean_y =
y_positions.reduce((acc, y) => acc + y, 0) / y_positions.length;
const std_x = Math.sqrt(
x_positions
.map((x) => Math.pow(x - mean_x, 2))
.reduce((a, b) => a + b, 0) / x_positions.length
);
const std_y = Math.sqrt(
y_positions
.map((y) => Math.pow(y - mean_y, 2))
.reduce((a, b) => a + b, 0) / y_positions.length
);
log(
`Community ${communityClusters[community].label} mean: (${mean_x}, ${mean_y}) std: (${std_x}, ${std_y})`
);
log(
`Community ${communityClusters[community].label} positions: ${communityClusters[community].positions.length}`
);
const filtered_positions = communityClusters[community].positions.filter(
(p) =>
Math.abs(p.x - mean_x) <= 2 * std_x &&
Math.abs(p.y - mean_y) <= 2 * std_y
);
log(
`Community ${communityClusters[community].label} filtered positions: ${filtered_positions.length}`
);
if (filtered_positions.length === 0) {
log(`Skipping community ${communityClusters[community].label}...`);
continue; // Skip this community if there are no positions within 2 standard deviations
}
communityClusters[community].x = parseFloat(
(
filtered_positions.reduce((acc, p) => acc + p.x, 0) /
filtered_positions.length
).toFixed(2)
);
communityClusters[community].y = parseFloat(
(
filtered_positions.reduce((acc, p) => acc + p.y, 0) /
filtered_positions.length
).toFixed(2)
);
log(
`Community ${communityClusters[community].label} barycenter: (${communityClusters[community].x}, ${communityClusters[community].y})`
);
}
// Strip the positions from the cluster objects
for (const community in communityClusters) {
communityClusters[community].positions = [];
}
graph.setAttribute("clusters", communityClusters);
// Reassign cluster indices to match db indices
for (const community in communityClusters) {
const cluster = communityClusters[community];
if (cluster.dbIndex !== undefined) {
// Reassign nodes to the new cluster index
graph.updateEachNodeAttributes((_, atts) => {
if (atts.community === community) {
atts.community = `${cluster.dbIndex}`;
}
return atts;
});
cluster.idx = `${cluster.dbIndex}`;
}
}
log(`Number of clusters: ${Object.keys(communityClusters).length}`);
for (const communityIdx in communityClusters) {
const community = communityClusters[communityIdx];
log(
`Cluster ${
community.label || community.idx
}, size: ${community.size.toLocaleString()}, representative: ${
community.representative || "N/A"
}`
);
}
graph.setAttribute("lastUpdated", new Date().toISOString());
log("Exporting enriched graph...");
let outputPath = "./out/exported_graph_enriched.json";
fs.writeFileSync(outputPath, JSON.stringify(graph.export()));
log("Done exporting enriched graph");
log("Minifying graph...");
// Remove DIDs from nodes if not enriched
graph.updateEachNodeAttributes((_, atts) => {
if (atts.did !== undefined) {
delete atts.did;
}
return atts;
});
log("Done minifying graph");
log("Exporting minified graph...");
outputPath = "./out/exported_graph_minified.json";
fs.writeFileSync(outputPath, JSON.stringify(graph.export()));
log("Done exporting minified graph");
});