-
Notifications
You must be signed in to change notification settings - Fork 1
/
resources.html
49 lines (43 loc) · 3.44 KB
/
resources.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>Network Navigator</title>
<link rel="stylesheet" href="https://unpkg.com/tachyons@4.12.0/css/tachyons.min.css" />
<link href="https://emoji-css.afeld.me/emoji.css" rel="stylesheet">
<link rel="stylesheet" type="text/css" href="https://cdn.datatables.net/v/dt/dt-1.10.22/b-1.6.5/b-html5-1.6.5/datatables.min.css"/>
<link rel="stylesheet" type="text/css" href="main.css">
<link rel="icon"
href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>🧭</text></svg>">
</head>
<body class="helvetica bg-near-white">
<header class="w-100 pa3 gradient">
<nav class="w-100 f4 fw6 tracked i white bb">
<h2 class="retro-font">
<a class="link white dim" href="/">NETWORK NAVIGATOR</a> <span class="f7 fs-normal">v2.0</span>
</h2>
</nav>
</header>
<main class="center pv3 measure-wide lh-copy">
<h1>Resources & Next Steps</h1>
<p>For more information about managing network data and an introduction to the various network metrics used here, we recommend two <em>Programming Historian</em> tutorials:
<p><a class="link black b dim" href="https://programminghistorian.org/lessons/creating-network-diagrams-from-historical-sources" target="_blank">Creating Network Diagrams from Historical Sources</a></p>
<p><a class="link black b dim" href="https://programminghistorian.org/lessons/exploring-and-analyzing-network-data-with-python" target="_blank">Exploring and Analyzing Network Data with Python</a></p>
<hr>
<p>If you have <a class="link black b dim" href="http://scottbot.net/networks-demystified-9-modality/" target="_blank">bipartite or bimodal</a> network data (a network that includes 2 kinds of entities, like one of authors and their books), you will need to <em>project</em> your data before you use Network Navigator. There is a quick tool for transforming your data here:
<p><a class="link black b dim" href="https://the-project-project.glitch.me/" target="_blank">The <em>Project</em> Project</a></p>
<hr>
<p>Once you've explored your network on our site, you may want to move to a more robust set of network analysis and visualization tools. We recommend the following:</p>
<p><a class="link black b dim" href="https://networkx.org/" target="_blank">NetworkX</a>, a Python library</p>
<p><a class="link black b dim" href="https://igraph.org/r/" target="_blank">iGraph</a>, an R library</p>
<p><a class="link black b dim" href="https://gephi.org/" target="_blank">Gephi</a>, a desktop program</p>
<p><a class="link black b dim" href="https://cytoscape.org/" target="_blank">Cytoscape</a>, a desktop program</p>
<p><a class="link black b dim" href="https://observablehq.com/@d3/force-directed-graph" target="_blank">D3 Force-Directed Graph</a>, a JavaScript library with tools for network visualization</p>
<hr>
<p>For general guidance on network analysis and Python cultural analytics approaches, we recommend Melanie Walsh's <a class="link black b dim" href="https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html" target="_blank">Introduction to Cultural Analytics & Python</a> and John Ladd's <a class="link black b dim" href="https://earlyprint.org/jupyterbook/intro.html">EarlyPrint + Python</a>.</p>
<p><em>Last Updated: April 2021</em></p>
</main>
</body>
</html>