28:null 29:["$","title",null,{"children":"Research networks | Vishal Devireddy | Observable"}] 2e:T4e8,md` Dataset: [Semantic Scholar Open Research Corpus](http://s2-public-api-prod.us-west-2.elasticbeanstalk.com/corpus/)

Example JSON record


{
  "id": "4cd223df721b722b1c40689caa52932a41fcc223",
  "title": "Knowledge-rich, computer-assisted composition of Chinese couplets",
  "paperAbstract": "Recent research effort in poem composition has focused on the use of
   automatic language generation...",
  "entities": [
  ],
  "fieldsOfStudy": [
      "Computer Science"
  ],
  "s2Url": "https://semanticscholar.org/paper/4cd223df721b722b1c40689caa52932a41fcc223",
  "pdfUrls": [
    "https://doi.org/10.1093/llc/fqu052"
  ],
  "s2PdfUrl": "",
  "authors": [
    {
      "name": "John Lee",
      "ids": [
        "3362353"
      ]
    },
    "..."
  ],
  "inCitations": [
    "c789e333fdbb963883a0b5c96c648bf36b8cd242"
  ],
  "outCitations": [
    "abe213ed63c426a089bdf4329597137751dbb3a0",
    "..."
  ],
  "year": 2016,
  "venue": "DSH",
  "journalName": "DSH",
  "journalVolume": "31",
  "journalPages": "152-163",
  "sources": [
    "DBLP"
  ],
  "doi": "10.1093/llc/fqu052",
  "doiUrl": "https://doi.org/10.1093/llc/fqu052",
  "pmid": "",
  "magId": "2050850752"
}

`2f:T471,get_node_links_from = ( author_names, [minYear, maxYear], [minCitations, maxCitations] ) => { let [papers, authors] = get_papers_from( author_names, [minYear, maxYear], [minCitations, maxCitations] ); let nodes = []; for (let [key, val] of authors) { nodes.push({ id: key, // numPapers: val numPapers: author_to_papers[key].length }); } let links = []; for (let i = 0; i < nodes.length; i++) { let papers_i = author_to_papers[nodes[i].id]; for (let j = i + 1; j < nodes.length; j++) { let papers_j = author_to_papers[nodes[j].id]; let num_intersect = papers_i.filter( (v) => paper_to_authors[v].year >= minYear && paper_to_authors[v].year <= maxYear && paper_to_authors[v].numCitations >= minCitations && paper_to_authors[v].numCitations <= maxCitations && papers_j.includes(v) ).length; if (num_intersect) { links.push({ source: nodes[i].id, target: nodes[j].id, numPapers: num_intersect }); } } } return { nodes, links }; }30:T1797,chart = { const width = 600; const height = 400; // set of the "clicked" nodes to show, does not contain neighbors of clicked nodes let clicked_people = new Set(initial_people); const svg = d3 .create("svg") .attr("viewBox", [-width / 2, -height / 2, width, height]); // Allow zoom/panning const g = svg.append("g").attr("class", "everything"); // encompassing group d3 .zoom() .scaleExtent([1 / 4, 4]) .on("zoom", (evt) => g.attr("transform", evt.transform))(svg); const tooltip = svg .append("text") .attr("class", "tooltip") .attr("x", 0) .attr("y", 0); let link = g.append("g").attr("class", "lines").selectAll("line"); let node = g.append("g").attr("class", "nodes").selectAll("circle"); let simulation = d3 .forceSimulation() .force( "link", d3 .forceLink() .id((d) => d.id) .distance(10) ) .force("charge", d3.forceManyBody().strength(-80).distanceMax(150)) .force( "collision", d3.forceCollide().radius((d) => Math.sqrt(d.numPapers)) ) // .force("center", d3.forceCenter(0, 0).strength(0.02)) .force("x", d3.forceX().strength(0.02)) .force("y", d3.forceY().strength(0.02)) .velocityDecay(0.7) .alphaDecay(0.03) .on("tick", () => { link .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("cx", (d) => d.x).attr("cy", (d) => d.y); }); invalidation.then(() => simulation.stop()); function update( [minNode, maxNode], [minEdge, maxEdge], [minYear, maxYear], [minCitations, maxCitations] ) { let { nodes, links } = get_node_links_from( clicked_people, [minYear, maxYear], [minCitations, maxCitations] ); // Make a shallow copy to protect against mutation, while // recycling old nodes to preserve position and velocity. const old = new Map(node.data().map((d) => [d.id, d])); const nodeSet = new Set( nodes .filter((d) => d.numPapers >= minNode && d.numPapers <= maxNode) .map((d) => d.id) ); nodes = nodes .filter((d) => nodeSet.has(d.id)) .map((d) => Object.assign(old.get(d.id) || {}, d)); links = links .filter( (d) => d.numPapers >= minEdge && d.numPapers <= maxEdge && nodeSet.has(d.source) && nodeSet.has(d.target) ) .map((d) => Object.assign({}, d)); // When an author node is clicked, toggle showing its neighbors and update function click(evt, d) { if (evt.defaultPrevented) return; if (clicked_people.size > 1 && clicked_people.has(d.id)) { clicked_people.delete(d.id); } else { clicked_people.add(d.id); } update( [minNode, maxNode], [minEdge, maxEdge], [minYear, maxYear], [minCitations, maxCitations] ); } // When an author node is hovered over, highlight neighbors and edges function hoverOn(_evt, d) { link.classed( "highlight", (e) => e.source.id === d.id || e.target.id === d.id ); const neighbors = get_neighbors_of(d.id, [minYear, maxYear]); node.classed("neighbor", (e) => neighbors.has(e.id)); tooltip .text(`${d.id} (${d.numPapers})`) .transition() .duration(200) .style("opacity", 1); } // Author node is unhovered, unhighlight all edges and nodes function hoverOut(_evt, _d) { link.classed("highlight", false); node.classed("neighbor", false); tooltip.transition().duration(500).style("opacity", 0); } function hoverMove(evt, _d) { let [x, y] = d3.pointer(evt); tooltip.attr("transform", `translate(${x},${y})`); } node = node .data(nodes, (d) => d.id) .join( (enter) => enter // animate fading in, growing circle .append("circle") .classed("clicked", (d) => clicked_people.has(d.id)) .attr("x", (Math.random() - 0.5) * width) .attr("y", (Math.random() - 0.5) * height) .attr("r", 1) .style("opacity", 0.5) .transition() .duration(800) .attr("r", (d) => Math.sqrt(d.numPapers)) .style("opacity", 1) .selection(), (update_) => update_ .attr("x", (Math.random() - 0.5) * width) .attr("y", (Math.random() - 0.5) * height) .classed("clicked", (d) => clicked_people.has(d.id)) .attr("r", (d) => Math.sqrt(d.numPapers)), (exit) => exit // animate fading out, shrinking circle .classed("exit", true) .classed("neighbor", false) .transition() .duration(900) .style("opacity", 0) .attr("r", 0) .remove() ); node .on("click", click) .on("mouseover", hoverOn) .on("mouseout", hoverOut) .on("mousemove", hoverMove) .call(drag(simulation)); link = link.data(links).join( (enter) => enter .append("line") .style("stroke-opacity", 0) .transition() .duration(800) .style("stroke-opacity", (d) => Math.min(1, d.numPapers / 10)) .selection(), (update_) => update_, (exit) => exit .classed("exit", true) .classed("highlight", false) .transition() .duration(800) .style("stroke", "#fff") .style("opacity", 0) .remove() ); // Add titles // node.append("title").text((d) => `${d.id} (${d.numPapers})`); link .append("title") .text((d) => `${d.source} - ${d.target} (${d.numPapers})`); simulation.nodes(nodes); simulation.force("link").links(links); simulation.alpha(1).restart(); } return Object.assign(svg.node(), { update }); }31:[{"id":"adce229b0e28b8db664a164a4ca52e8e0fa25533566318d26fb6b0644b4adaf0db19e924668bfc19073d83365734cb757c5ae0f64a346d83bc6ac89902b0b1bf","href":"https://static.observableusercontent.com/files/adce229b0e28b8db664a164a4ca52e8e0fa25533566318d26fb6b0644b4adaf0db19e924668bfc19073d83365734cb757c5ae0f64a346d83bc6ac89902b0b1bf","name":"author_to_papers.json","type":"application/json","lastModified":1620341125837.384,"size":1913257},{"id":"75e3daf7e6d60486ade22243a640c96c47cf03e5e20ac7972aa03560689e9bd6ef2efe15268d1f9bce1a53202b9734fa0a105102534f477aef7f040a7758978e","href":"https://static.observableusercontent.com/files/75e3daf7e6d60486ade22243a640c96c47cf03e5e20ac7972aa03560689e9bd6ef2efe15268d1f9bce1a53202b9734fa0a105102534f477aef7f040a7758978e","name":"paper_to_authors.json","type":"application/json","lastModified":1620341126983.527,"size":2695366}] 2c:{"id":"a37de35812ac214e","slug":"research-networks","title":"Research networks","thumbnail":"011bd7de186523c794cf46087184f53aa3eefc6df9dc244bff6a1bfea36bd69d","access_level":"public","create_time":"$D2021-05-06T22:11:24.656Z","update_time":"$D2022-03-18T21:27:29.770Z","view_time":null,"first_public_time":"$D2021-05-08T00:16:25.723Z","has_unpublished_edits":null,"fork":true,"stars":10,"starred":false,"owner":{"type":"team","id":"4faa5ef65e8626e3","login":"twotau","name":"Vishal Devireddy","avatar_url":"https://avatars-next.observableusercontent.com/d4540fdfb5c12e38a1b2c778dd7ce9c992532db90c82cdb5f835e957006a239e","tier":"starter_2024"},"version":1124,"publish_version":1124,"role":null,"authored":false,"authors":[{"type":"individual","id":"c44e1ea68a45c7a2","login":"twotau","name":"Vishal Devireddy","avatar_url":"https://avatars-next.observableusercontent.com/d4540fdfb5c12e38a1b2c778dd7ce9c992532db90c82cdb5f835e957006a239e","tier":null}],"members":[{"type":"individual","id":"c44e1ea68a45c7a2","login":"twotau","name":"Vishal Devireddy","avatar_url":"https://avatars-next.observableusercontent.com/d4540fdfb5c12e38a1b2c778dd7ce9c992532db90c82cdb5f835e957006a239e","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":6,"collection":null,"type":"notebook","body":{"title":"Research networks","cells":[{"id":0,"value":"md`# Research networks`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"$2e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":177,"value":"get_papers_from = (\n author_names,\n [minYear, maxYear],\n [minCitations, maxCitations]\n) => {\n let papers = new Set();\n let authors = new Map();\n\n for (let author of author_names) {\n for (let paperId of author_to_papers[author]) {\n const p = paper_to_authors[paperId];\n if (\n !papers.has(paperId) &&\n p.year >= minYear &&\n p.year <= maxYear &&\n p.numCitations >= minCitations &&\n p.numCitations <= maxCitations\n ) {\n papers.add(paperId);\n\n for (let a of p.authors) {\n let val = authors.get(a) || 0;\n authors.set(a, val + 1);\n }\n }\n }\n }\n\n return [papers, authors];\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":404,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":726,"value":"get_neighbors_of = (author_name, [minYear, maxYear]) => {\n let neighbors = new Set();\n for (let paperId of author_to_papers[author_name]) {\n const p = paper_to_authors[paperId];\n if (p.year >= minYear && p.year <= maxYear) {\n for (let a of p.authors) {\n neighbors.add(a);\n }\n }\n }\n return neighbors;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":416,"value":"get_node_links_from([\"Kenji Inoue\", \"Tatsuo Arai\"], [1970, 2021], [0, 1000])","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":857,"value":"get_random_authors = (n = 1) => {\n let a = Object.keys(author_to_papers);\n let res = new Set();\n while (res.size < n) res.add(a[Math.floor(Math.random() * a.length)]);\n return res;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":342,"value":"md`\nThis network shows authors and their collaborators (people they write papers with).\nLarger circles represent authors that wrote more papers in the conference.\nThe opacity of the link scales with how many papers the two authors wrote together.\nThe graph is zoomable and pannable.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":945,"value":"md`\nClick on a node to expand its neighbors to show connected authors. \nThese are the authors that the network is initialized with:\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":868,"value":"// initial_people = get_random_authors(10)\ninitial_people = [\"Eugenio Guglielmelli\", \"Tatsuo Arai\"]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":959,"value":"md`\n**Filters** \n\n- Right now, we're only showing authors with **${nodeFilter[0]} to ${nodeFilter[1]}** papers in this conference. \n- We also only show edges where both authors collaborated on **${edgeFilter[0]} to ${edgeFilter[1]}** papers in this conference. \n- We only consider papers written between **${yearFilter[0]} to ${yearFilter[1]}** and with **${citationFilter[0]} to ${citationFilter[1]}** citations (from any conference).\n\nNote: all filters are an inclusive range. Author filter and paper citations have a high max because of outliers (prolific authors or super important papers).\n\nNote: the node sizes are based on total papers in this conference, including some that don't meet the filters.\n\nIf the edge filter or citation filter is high, then we end up with a lot of separate components and unconnected vertices.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":467,"value":"viewof nodeFilter = {\n const ps = Object.values(author_to_papers).map((p) => p.length);\n const minMaxPapersTotal = [Math.min(...ps), Math.max(...ps)];\n\n return rangeSlider({\n min: minMaxPapersTotal[0],\n max: minMaxPapersTotal[1],\n value: this ? this.value : minMaxPapersTotal, // Default value\n precision: 0,\n color: \"#ca2881\",\n title: \"Author filter (number of papers)\"\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":446,"value":"viewof edgeFilter = rangeSlider({\n min: 1,\n max: 20,\n value: this ? this.value : [0, 10], // Default value\n precision: 0,\n color: \"#47e26f\",\n title: \"Edge filter (number of collaborated papers)\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":963,"value":"viewof yearFilter = {\n const years = Object.values(paper_to_authors).map((p) => p.year);\n const minMaxYearsTotal = [Math.min(...years), Math.max(...years)];\n\n return rangeSlider({\n min: minMaxYearsTotal[0],\n max: minMaxYearsTotal[1],\n value: this ? this.value : [2000, 2020], // Default value\n precision: 0,\n color: \"#5151d3\",\n title: \"Paper publication year\"\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":983,"value":"viewof citationFilter = {\n const cits = Object.values(paper_to_authors).map((p) => p.numCitations);\n const minMaxCitationsTotal = [Math.min(...cits), Math.max(...cits)];\n\n return rangeSlider({\n min: minMaxCitationsTotal[0],\n max: minMaxCitationsTotal[1],\n value: this ? this.value : [1, minMaxCitationsTotal[1]], // Default value\n precision: 0,\n color: \"#24AADB\",\n title: \"Paper citations\"\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":211,"value":"$30","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":917,"value":"chart.update(nodeFilter, edgeFilter, yearFilter, citationFilter)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":558,"value":"html``","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":22,"value":"md`\n## Appendix\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":23,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":448,"value":"import { rangeSlider } from \"@mootari/range-slider\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":381,"value":"author_to_papers = await FileAttachment(\"author_to_papers.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":383,"value":"paper_to_authors = await FileAttachment(\"paper_to_authors.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":51,"value":"drag = (simulation) => {\n function dragstarted(event, d) {\n if (!event.active) simulation.alphaTarget(0.2).restart();\n d.fx = d.x;\n d.fy = d.y;\n }\n\n function dragged(event, d) {\n d.fx = event.x;\n d.fy = event.y;\n }\n\n function dragended(event, d) {\n if (!event.active) simulation.alphaTarget(0);\n d.fx = null;\n d.fy = null;\n }\n\n return d3\n .drag()\n .on(\"start\", dragstarted)\n .on(\"drag\", dragged)\n .on(\"end\", dragended);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W31","stdlib":"1","titling":"auto"}} 2d:"$2c:body"