44:["$","title",null,{"children":"Politics on Bluesky | Smoked Haddock | Observable"}] 4c:T419,const updated = new Date(data.timestamp); const nextUpdate = new Date(updated.getTime() + 30 * 60 * 1000); const fmt = d3.timeFormat("%b %-d, %-I:%M %p"); display(html`

This notebook explores what people are posting about Climate, US, and UK politics on Bluesky. Recent posts are distilled into a network of frequently mentioned terms: larger circles are mentioned more, and thicker links mean two terms appear together in more posts. Click a term to see the posts that mention it, or click a link to see posts that mention both of its terms.

How fresh is the data? The datasets are regenerated by a background worker every 30 minutes, and the CDN cache is flushed after each run, so reloading the page picks up the latest snapshot. The current ${channel} snapshot was generated at ${fmt(updated)}; the next one is expected around ${fmt(nextUpdate)}.

`);4d:T1599,const graph = (() => { const {network} = summary; const keep = new Set(network.nodes.filter((d) => d.data.count >= minMentions).map((d) => d.data.id)); const links = network.edges .filter((d) => keep.has(d.data.source) && keep.has(d.data.target) && d.data.count >= minLink) .map((d) => ({source: d.data.source, target: d.data.target, count: d.data.count})); const connected = new Set(links.flatMap((d) => [d.source, d.target])); const nodes = network.nodes .filter((d) => connected.has(d.data.id)) .map((d) => ({id: d.data.id, count: d.data.count})); return {nodes, links}; })(); const neighbors = new Map(graph.nodes.map((d) => [d.id, new Set([d.id])])); for (const l of graph.links) { neighbors.get(l.source).add(l.target); neighbors.get(l.target).add(l.source); } const width = 900, height = 600; const radius = d3.scaleSqrt(d3.extent(graph.nodes, (d) => d.count), [5, 30]); const strokeWidth = d3.scaleSqrt(d3.extent(graph.links, (d) => d.count), [0.5, 8]); const color = d3.scaleSequentialLog(d3.extent(graph.nodes, (d) => Math.max(1, d.count)), d3.interpolateBlues); const simulation = d3.forceSimulation(graph.nodes) .force("link", d3.forceLink(graph.links).id((d) => d.id).distance(90).strength(0.4)) .force("charge", d3.forceManyBody().strength(-300)) .force("center", d3.forceCenter(0, 0)) .force("collide", d3.forceCollide((d) => radius(d.count) + 4)); const svgEl = d3.create("svg") .attr("viewBox", [-width / 2, -height / 2, width, height]) .attr("width", width) .attr("style", "max-width: 100%; height: auto; font: 12px sans-serif;"); svgEl.append("rect").attr("x", -width / 2).attr("y", -height / 2).attr("width", width).attr("height", height) .attr("fill", "transparent").on("click", () => select(null)); svgEl.append("text").attr("x", -width / 2 + 10).attr("y", -height / 2 + 22).attr("pointer-events", "none") .attr("style", "font-size: 18px; font-weight: bold").text(`What people are saying: "${channel}" word network`); svgEl.append("text").attr("x", -width / 2 + 10).attr("y", -height / 2 + 40).attr("fill", "#666").attr("pointer-events", "none") .text(`${graph.nodes.length} terms, ${graph.links.length} links · size = mentions, width = co-occurrences · click a term or a link to filter posts · ${data.timestamp}`); const link = svgEl.append("g").attr("stroke", "#999").attr("stroke-opacity", 0.5) .selectAll("line").data(graph.links).join("line") .attr("stroke-width", (d) => strokeWidth(d.count)) .attr("pointer-events", "none"); // Wider invisible lines to make thin edges easy to click const linkHit = svgEl.append("g").attr("stroke", "transparent") .selectAll("line").data(graph.links).join("line") .attr("stroke-width", (d) => Math.max(12, strokeWidth(d.count) + 6)) .attr("cursor", "pointer") .on("click", (event, d) => { event.stopPropagation(); toggle([d.source.id, d.target.id]); }); linkHit.append("title").text((d) => `${d.source.id} – ${d.target.id}: ${d.count} co-occurrences`); const node = svgEl.append("g").selectAll("g").data(graph.nodes).join("g") .attr("cursor", "pointer") .on("click", (event, d) => { event.stopPropagation(); toggle([d.id]); }) .call(d3.drag() .clickDistance(4) .on("start", (event) => { if (!event.active) simulation.alphaTarget(0.3).restart(); event.subject.fx = event.subject.x; event.subject.fy = event.subject.y; }) .on("drag", (event) => { event.subject.fx = event.x; event.subject.fy = event.y; }) .on("end", (event) => { if (!event.active) simulation.alphaTarget(0); event.subject.fx = null; event.subject.fy = null; })); node.append("circle").attr("r", (d) => radius(d.count)).attr("fill", (d) => color(Math.max(1, d.count))) .attr("stroke", "#fff").attr("stroke-width", 1.5); node.append("text").text((d) => d.id).attr("text-anchor", "middle").attr("dy", "0.35em") .attr("fill", (d) => d.count > 60 ? "white" : "#222").attr("pointer-events", "none") .attr("font-size", (d) => Math.max(9, Math.min(16, radius(d.count) * 0.6))); node.append("title").text((d) => `${d.id}: ${d.count} mentions`); // Selection is an array of terms (1 for a node, 2 for a link) or null function highlight(ids) { const sel = ids ? new Set(ids) : null; const single = ids && ids.length === 1 ? ids[0] : null; const near = !ids ? null : single ? neighbors.get(single) : sel; const active = (d) => !ids ? false : single ? (d.source.id === single || d.target.id === single) : (sel.has(d.source.id) && sel.has(d.target.id)); node.attr("opacity", (d) => !near || near.has(d.id) ? 1 : 0.15); node.select("circle").attr("stroke", (d) => sel?.has(d.id) ? "#e4572e" : "#fff").attr("stroke-width", (d) => sel?.has(d.id) ? 4 : 1.5); link.attr("stroke", (d) => active(d) ? "#e4572e" : "#999") .attr("stroke-opacity", (d) => !ids ? 0.5 : active(d) ? 0.9 : 0.05); } const chartNode = svgEl.node(); chartNode.value = null; function toggle(ids) { const cur = chartNode.value; const same = cur && cur.length === ids.length && ids.every((id) => cur.includes(id)); select(same ? null : ids); } function select(ids) { chartNode.value = ids; highlight(ids); chartNode.dispatchEvent(new Event("input", {bubbles: true})); } simulation.on("tick", () => { for (const sel of [link, linkHit]) sel.attr("x1", (d) => d.source.x).attr("y1", (d) => d.source.y).attr("x2", (d) => d.target.x).attr("y2", (d) => d.target.y); node.attr("transform", (d) => `translate(${d.x},${d.y})`); }); invalidation.then(() => simulation.stop()); const selectedTerms = view(chartNode);4e:T485,const matchingPosts = (() => { const terms = selectedTerms ?? []; const res = terms.map((t) => new RegExp(`\\b${_.escapeRegExp(t)}\\b`, "i")); return summary.sentences .map((s) => { const [, did, rkey] = s.post.uri.match(/^at:\/\/([^/]+)\/[^/]+\/([^/]+)$/) ?? []; return { createdAt: s.post.record.createdAt, text: s.post.record.text, url: did ? `https://bsky.app/profile/${did}/post/${rkey}` : null }; }) .filter((d) => res.every((re) => re.test(d.text))); })(); const label = selectedTerms ? selectedTerms.map((t) => `“${t}”`).join(" + ") : null; display(html`

${label ? `Posts mentioning ${label}` : "All posts"} (${matchingPosts.length} of ${summary.sentences.length})

`); display(Inputs.table(matchingPosts, { columns: ["createdAt", "text", "url"], header: {createdAt: "Time", text: "Post", url: "Link"}, format: { createdAt: (d) => d3.timeFormat("%H:%M:%S")(new Date(d)), url: (d) => d ? html`open ↗` : "" }, width: {createdAt: 70, url: 70}, rows: 12 }));4f:[] 48:{"id":"7367181996e44dc1","slug":"us-politics-on-bluesky","title":"Politics on Bluesky","thumbnail":"6461d21b916d2c5bb3f281741a44edd119a08c9f1f083f02e95e1467631a0bd0","access_level":"public","create_time":"$D2026-10-29T17:10:18.491Z","update_time":"$D2026-10-30T09:02:16.405Z","view_time":null,"first_public_time":"$D2026-10-29T17:28:40.261Z","has_unpublished_edits":null,"fork":false,"stars":1,"starred":false,"owner":{"type":"team","id":"e7154098d804ccd3","login":"mycroft","name":"Smoked Haddock","avatar_url":"https://avatars-next.observableusercontent.com/0de24321ffaf4363ff2bdd86f04762092b5e049101dfafce274db05f65c8d923","tier":"pro_2026","bio":"Pattern radar for symbol streams","followed_by_you":false,"follows_you":false},"version":45,"publish_version":45,"role":null,"authored":false,"authors":[{"type":"individual","id":"37a2ff115a9312f2","login":"mycroft","name":"Smoked Haddock","avatar_url":"https://avatars-next.observableusercontent.com/0de24321ffaf4363ff2bdd86f04762092b5e049101dfafce274db05f65c8d923","tier":null,"bio":"Pattern radar for symbol streams","followed_by_you":false,"follows_you":false}],"members":[{"type":"team","id":"e7154098d804ccd3","login":"mycroft","name":"Smoked Haddock","avatar_url":"https://avatars-next.observableusercontent.com/0de24321ffaf4363ff2bdd86f04762092b5e049101dfafce274db05f65c8d923","tier":"pro_2026","role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Politics on Bluesky","cells":[{"id":1,"value":"# Politics on Bluesky","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"$4c","pinned":false,"hidden":true,"mode":"js","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2,"value":"const example = await d3.json(\"https://mycroft-pull.b-cdn.net/radar/uspol.json\", {proxy: true});\ndisplay(Array.isArray(example) ? 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