2e:null 2f:["$","title",null,{"children":"Tampa Meetup Group Network (Shared Members) | Fabio DeSousa | Observable"}] 34:T521,md` ## Centrality Measures ### Degree (higher = more connected) Degree centrality is the number of ties that a node has. ### Betweenness (higher = more important the node is to overall connectivity) Betweenness centrality is a measure of centrality in a graph based on shortest paths. For every pair of vertices in a connected graph, there exists at least one shortest path between the vertices such that either the number of edges that the path passes through (for unweighted graphs) or the sum of the weights of the edges (for weighted graphs) is minimized. The betweenness centrality for each vertex is the number of these shortest paths that pass through the vertex. ### Closeness (higher = closer on average to all other nodes. 1 = direct connection to every other node on the connected graph) In a connected graph, the normalized closeness centrality of a node is the average length of the shortest path between the node and all other nodes in the graph. Thus the more central a node is, the closer it is to all other nodes. ### Eccentricity (higher = greater distance to the furthest node) The eccentricity centrality of a node is the greatest distance between that node and any other node in the network. It can be thought of as how far a node is from the node most distant from it in the graph. `35:Tc73,chart = { //const nodes = data.nodes.map(d => Object.create(d)).sort((a,b) => a.id > b.id ? -1 : 1); const nodes = get_nodes(group_members).map(d => Object.create(d)).sort((a,b) => a.id > b.id ? -1 : 1); const node_map = {} nodes.forEach(d => node_map[d.id] = true); const links = data.links.filter(d => filter_func(d)).map(d => Object.create(d)).filter(d => (d.source in node_map && d.target in node_map)); var g = ngraph(); links.forEach(d => {g.addLink(d.source, d.target)}); centrality_measures['betweenness'] = centrality.betweenness(g); centrality_measures['closeness'] = centrality.closeness(g); centrality_measures['degree'] = centrality.degree(g); centrality_measures['eccentricity'] = centrality.eccentricity(g); const {betweenness, closeness, degree, eccentricity} = {...centrality_measures} const simulation = d3.forceSimulation(nodes) .force("link", d3.forceLink(links).id(d => d.id)) .force("charge", d3.forceManyBody().strength(-200).distanceMax(70).distanceMin(20)) .force("center", d3.forceCenter(width / 2, height / 2)); const svg = d3.select(DOM.svg(width, height)); var active_group = false; const show_centrality = (svg, active_group) => { svg.append("text") .attr("x", 50) .attr("y", 50) .text(active_group ? `Degree: ${degree[active_group].toPrecision(3)} | Betweenness: ${betweenness[active_group].toPrecision(3)} | Closeness: ${closeness[active_group].toPrecision(3)} | Eccentricity: ${eccentricity[active_group].toPrecision(3)}` : '') .attr("font-size", "20px") .attr("class", "centrality"); } const show_name = (svg, active_group) => { svg.append("text") .attr("x", 50) .attr("y", 25) .text(active_group ? `${active_group}` : '') .attr("font-size", "20px") .attr("class", "name"); } const remove_text = (svg) => { svg.selectAll("text").remove(); } const mouseover = (d) => { active_group = d.id; show_name(svg, active_group); show_centrality(svg, active_group); }; const mouseout = () => { active_group = false; remove_text(svg) }; const link = svg.append("g") .attr("stroke", "#999") .attr("stroke-opacity", 0.7) .selectAll("line") .data(links) .join("line") .attr("stroke-width", d => Math.sqrt(d.value)) const node = svg.append("g") .attr("stroke", "#fff") .attr("stroke-width", 1.5) .selectAll("circle") .data(nodes) .join("circle") .attr("r", d => size_attendees ? Math.sqrt(Object.keys(group_members[d.id]).length) : 5) .attr("fill", color) .call(drag(simulation)) .on('mouseover', d => mouseover(d)) .on('mouseout', mouseout); node.append("title") .text(d => `${d.id} | ${Object.keys(group_members[d.id]).length} members`); simulation.on("tick", () => { link .attr("x1", d => d.source.x) .attr("y1", d => d.source.y) .attr("x2", d => d.target.x) .attr("y2", d => d.target.y); node .attr("cx", d => d.x) .attr("cy", d => d.y); }); invalidation.then(() => simulation.stop()); return svg.node(); }36:[] 32:{"id":"ab57887e6288a7e0","slug":"tampa-meetup-group-network-shared-members","title":"Tampa Meetup Group Network (Shared Members)","thumbnail":"523e57d8321a68462ee2f1d65a79b23a67d014d7717c1cf72bb0830844c9e263","access_level":"public","create_time":"$D2019-02-07T19:35:34.873Z","update_time":"$D2019-02-19T20:01:48.079Z","view_time":null,"first_public_time":"$D2019-02-07T21:34:58.397Z","has_unpublished_edits":null,"fork":{"id":"a6c00de7c09bdfa1","slug":"force-directed-graph-component","title":"Force-directed graph component","owner":{"id":"863951e3ebe4c0ae","login":"d3","name":"D3"}},"stars":0,"starred":false,"owner":{"type":"team","id":"d6efb9381b3c7a49","login":"fabiodesousa","name":"Fabio DeSousa","avatar_url":"https://avatars-next.observableusercontent.com/714bcaff938cebc4dbc85416dfb0be12f89394cf3b5b859670b64b836d33aeda","tier":"starter_2024"},"version":431,"publish_version":431,"role":null,"authored":false,"authors":[{"type":"individual","id":"084cb9281298bdfa","login":"fabiodesousa","name":"Fabio DeSousa","avatar_url":"https://avatars-next.observableusercontent.com/714bcaff938cebc4dbc85416dfb0be12f89394cf3b5b859670b64b836d33aeda","tier":null}],"members":[{"type":"individual","id":"084cb9281298bdfa","login":"fabiodesousa","name":"Fabio DeSousa","avatar_url":"https://avatars-next.observableusercontent.com/714bcaff938cebc4dbc85416dfb0be12f89394cf3b5b859670b64b836d33aeda","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Tampa Meetup Group Network (Shared Members)","cells":[{"id":1,"value":"md`# Tampa Meetup Group Network (Shared Members)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":134,"value":"viewof lower_bound = number(\n {\n title:\"Group Tie Strength Lower Bound (aka how many shared members do two groups need before we consider those groups connected?)\",\n value:\"20\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":224,"value":"viewof person_lower_bound = number(\n {\n title:\"Attendee Lower Bound (aka how many events do you attend before we consider you an active member of a group? Max=10 because we only have data on the ten most recent events.\",\n value:1\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":181,"value":"viewof filter = checkbox({\n description: \"When checked, this will remove ties to groups in the filter list, but their nodes will remain\",\n options: [{ value: true, label: \"Filter out groups in the Filter List?\" }],\n value: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":242,"value":"viewof size_attendees = checkbox({\n description: \"When checked, the radius of each node will equal the square root of the number of distinct attendees that group's last ten events has had\",\n options: [{ value: true, label: \"Use number of attendees to determing node size?\" }],\n value: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":341,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":402,"value":"chart ? table(centrality_measures) : table(centrality_measures)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":372,"value":"table = (centrality_measures) => {return html`\n \n \n \n \n \n \n \n ${Object.keys(centrality_measures).map( measure => {\n console.log(measure)\n const values = Object.keys(centrality_measures[measure]).map(key => centrality_measures[measure][key]);\n return `\n \n \n \n \n \n \n `\n })\n }\n

Centrality Measure	Average	Max	Min
${measure}	${(values.reduce((accumulator, current) => accumulator + current)/values.length).toPrecision(3)}	${(values.reduce((accumulator, current) => accumulator > current ? accumulator : current)).toPrecision(3)}	${(values.reduce((accumulator, current) => accumulator < current ? accumulator : current)).toPrecision(3)}

\n`}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":413,"value":"mutable refresh = true //you can ignore this, it's just to keep the table updated with the graph","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":178,"value":"filter_list = [\n 'Tampa-Bay-AWS-Group',\n 'microsoft-azure-tampa',\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":180,"value":"filter_func = (d) => {\n const lower = lower_bound ? d.value >= lower_bound : 1\n const in_list = !filter_list.includes(d.source) && !filter_list.includes(d.target)\n if(filter) {\n return in_list && lower\n }\n else {\n return lower\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":349,"value":"centrality_measures = {\n return {}\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3,"value":"data = d3.json(\"https://gist.githubusercontent.com/fabiodesousa/d866e400ff7dd185dc1f7db9cc9c03b8/raw/b6114e32c2a1b2fc12294b169b1ec7ac9cf7c0db/group_graph_data.json\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":200,"value":"group_members =\nd3.json(\"https://gist.githubusercontent.com/fabiodesousa/98cc4cf220a12a42f998c10ee825cf7a/raw/82c3f4dd88f87f9d95c2bad71282b96630e003bc/group_members.json\")","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":218,"value":"test = get_nodes(group_members)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":206,"value":"get_nodes = (members) => {\n const nodes = []\n Object.keys(members).forEach(d => {\n const attendees = members[d];\n if(person_lower_bound) {\n var filtered = {}\n for(var person in attendees) {\n if(attendees[person] >= person_lower_bound) {\n filtered[person] = attendees[person] \n }\n }\n if(Object.keys(filtered).length > 0) {\n nodes.push({id: d, group: 0});\n }\n }\n else {\n nodes.push({id: d, group: 0});\n }\n });\n return nodes;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":32,"value":"height = 800","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":150,"value":"color_list = ['#e6194b', '#3cb44b', '#ffe119', '#4363d8', '#f58231', '#911eb4', '#46f0f0', '#f032e6', '#bcf60c', '#fabebe', '#008080', '#e6beff', '#9a6324', '#800000', '#aaffc3', '#808000', '#ffd8b1', '#000075', '#808080', \"#89e1cf\", \"#f2617a\", \"#3b3836\", \"#ffc730\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"color = {\n const scale = d3.scaleOrdinal().range(color_list);\n return d => scale(d.id);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":76,"value":"drag = simulation => {\n \n function dragstarted(d) {\n if (!d3.event.active) simulation.alphaTarget(0.3).restart();\n d.fx = d.x;\n d.fy = d.y;\n }\n \n function dragged(d) {\n d.fx = d3.event.x;\n d.fy = d3.event.y;\n }\n \n function dragended(d) {\n if (!d3.event.active) simulation.alphaTarget(0);\n d.fx = null;\n d.fy = null;\n }\n \n return d3.drag()\n .on(\"start\", dragstarted)\n .on(\"drag\", dragged)\n .on(\"end\", dragended);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":295,"value":"ngraph = require('https://bundle.run/ngraph.graph@0.0.3')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":314,"value":"centrality = require('https://bundle.run/ngraph.centrality@0.3.0');","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":136,"value":"import {number, checkbox, select} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W36","stdlib":"1","titling":"auto"}} 33:"$32:body"