{"id":20957,"date":"2018-06-20T09:54:17","date_gmt":"2018-06-20T09:54:17","guid":{"rendered":"https:\/\/www.arimetrics.com\/blog\/viewing-internal-links-with-gephi"},"modified":"2026-05-12T12:17:03","modified_gmt":"2026-05-12T12:17:03","slug":"viewing-internal-links-with-gephi","status":"publish","type":"post","link":"https:\/\/www.arimetrics.com\/en\/blog\/viewing-internal-links-with-gephi","title":{"rendered":"Viewing internal links with Gephi"},"content":{"rendered":"\n<div class=\"geo-key-points\"><p><strong>Key points:<\/strong><\/p><ul><li>Define the objective before applying any tactic.<\/li><li>Validate data, search intent and the competitive context.<\/li><li>Connect execution with measurement, learning and continuous improvement.<\/li><\/ul><\/div>\n\n\n\n<figure class=\"wp-block-table\"><table><thead><tr><th>Aspect<\/th><th>What to review<\/th><th>Useful indicator<\/th><\/tr><\/thead><tbody><tr><td>Viewing internal links with Gephi<\/td><td>Goal, audience and expected impact<\/td><td>Qualified traffic, leads or conversions<\/td><\/tr><tr><td>Execution<\/td><td>Channels, content and required resources<\/td><td>Implementation quality and consistency<\/td><\/tr><tr><td>Measurement<\/td><td>Available data and later learning<\/td><td>Trend, cost, conversion and return<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"geo-answer-block\"><p><strong>Quick answer:<\/strong> Viewing internal links with Gephi matters in digital marketing when it is connected to business goals, reliable measurement and a clear strategy. The priority is to understand its impact, apply it with judgment and link it to actions that improve visibility, acquisition and conversion.<\/p><\/div>\n\n\nOne of the practices that tends to favor search engine positioning is the generation of links on a website. In general, <a href=\"https:\/\/www.arimetrics.com\/en\/digital-glossary\/linkbuilding\">link building,<\/a>both external and internal, gives authority to a domain and favors a hierarchical structure of the page.\n\nExplained in a summarized way, external backlinks are the links that link to your website or any of its links or content. While internal backlinks is the generation of internal links that point to our own pages, so that it facilitates navigation.\n\nIt is thus understood that the role of a good internal linkbuilding is in the hands of <a href=\"https:\/\/www.arimetrics.com\/en\/seo-agency-spain\">SEO experts.<\/a> Throughout this article, we will show, first, how to detect all the internal links of our website with the <a href=\"https:\/\/www.screamingfrog.co.uk\/seo-spider\/\" target=\"_blank\" rel=\"noopener\">Screaming Frog <\/a>tool. And second, how <a href=\"https:\/\/gephi.org\/\" target=\"_blank\" rel=\"noopener\">to visualize them with Gephi<\/a> in a way that gives a global vision, with which you can easily identify the structure and hierarchy of all the internal links of a<strong> website.<\/strong>\n<h2>1. <strong>Before using Gephi: detect and analyze internal links with Screaming Frog<\/strong><\/h2>\nThere are numerous tools with which it is possible to see the link structure of a web page. In this case, we will use Screaming Frog, a program that can be downloaded for free, both for Windows, Linux or Mac, and that allows you to track the entire structure of a domain, from CSS, HTML, PHP, etc.\n\nFor this example, we have used the paid version, although the free one offers us a collection of up to 500 URLs. Now, what interests us with Screaming Frog is to see what our internal links are <strong>to, later, visualize them with Gephi.<\/strong>\n\nFor this, just put the URL that interests us in the search engine above.\n\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/screaming-frog-links-internos.jpg\" alt=\"screaming-frog-links-internal\" width=\"1776\" height=\"903\" \/>\n\nOnce, 100% of the data has been loaded (a process that will take several minutes, depending on the size of the website), we look at the &#8216;Internal&#8217; tab. This is where all our <strong>internal links<\/strong>are. To make the handling of the data easier and the visualization more concrete and detailed, we will filter by HTML (this option is only available in the paid version, but you can also clean the database later, using filters).\n\nWhen your crawl is finished, we export them as shown in the following image:\n\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/descargar-links-screamingfrog.jpg\" alt=\"download-links-screamingfrog\" width=\"1768\" height=\"854\" \/>\n\n<strong>Before importing the data into Gephi,<\/strong>clean the spreadsheet:\n<ul>\n \t<li>Delete the first row containing &#8216;All Links&#8217;.<\/li>\n \t<li>Delete the first column, &#8216;Type&#8217;.<\/li>\n \t<li>Rename the column &#8216;Destination&#8217; to &#8216;Target&#8217;<\/li>\n \t<li>Delete the rest of the columns. If you prefer, you can leave other columns such as the status code or anchor text. This will depend on the data you prefer to display in the chart. In any case, the fields that interest us now are &#8216;Source&#8217; and &#8216;Target&#8217;.<\/li>\n<\/ul>\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/Datos-links-internos-base.jpg\" alt=\"Data-links-internal-base\" width=\"1862\" height=\"662\" \/>\n\nAs we have mentioned before, in case of using the free version of Screaming Frog, it will also be necessary to do a data cleaning to filter the images, CSS and JavaScript files. In this way, we will leave only HTML.\n<h2>2. <strong>Import internal link data into Gephi<\/strong><\/h2>\nWhen the database with all the internal links is organized and structured, it will be <strong>time to import them into Gephi.<\/strong> To do this, we will follow the following steps:\n<ul>\n \t<li>We open Gephi and select the &#8216;new project&#8217; option<\/li>\n \t<li>In the &#8216;file&#8217; tab (top left) click on &#8216;import spreadsheet&#8217; (important that it is in CSV format)<\/li>\n \t<li>We continue with the preset configuration (separated by commas, edge table and UT8)<\/li>\n<\/ul>\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/Importar-datos-a-Gephi.jpg\" alt=\"Import-data-to-Gephi\" width=\"784\" height=\"502\" \/>\n<ul>\n \t<li>In the options of &#8216;import parameters&#8217;, it is not necessary to make too many changes, since in addition, the database with which we are working for this example, is not too extensive. In any case, we have to look at the fact that our text fields contain &#8216;string&#8217; and the fields with numeric values are marked with the option &#8216;integer&#8217; or &#8216;float&#8217;.<\/li>\n<\/ul>\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/Importar-base-de-datos-a-Gephi-1.jpg\" alt=\"Import-database-to-Gephi (1)\" width=\"779\" height=\"500\" \/>\n<ul>\n \t<li>Once this, before finishing and if everything is correct we will see an image like this:<\/li>\n<\/ul>\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/Finalizar-importacion-de-datos-Gephi.jpg\" alt=\"Finish-import-data-Gephi\" width=\"668\" height=\"469\" \/>\n<h2>3. <strong>Calculate the PageRank and modularity of our internal links with Gephi<\/strong><\/h2>\nIn case the process of importing our database to Gephi has been correct, we will be presented with this black box on the screen that appears when clicking on the upper left tab &#8216;overview&#8217;.\n\nThis visualization that is obviously not useful, will be the one that we will change to be representative.\n\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/Gephi-visualizacion.jpg\" alt=\"Gephi-visualization\" width=\"1685\" height=\"945\" \/>\n\nAs we can see, to the right of the panel is the &#8216;statistics&#8217; part, in which we find several indicators. On this occasion, we will pay attention to &#8216;PageRank&#8217; and click on &#8216;run&#8217; with the preset settings. (Important, when we talk about this metric here we are not referring to <a href=\"https:\/\/www.arimetrics.com\/en\/digital-glossary\/pagerank\">Google&#8217;s Page Rank,<\/a>but to a ranking that Gephi&#8217;s own system elaborates).\n\nWe repeat the same process with &#8216;modularity&#8217;. On this occasion, it may have to be executed several times, so that it refines optimally. Unlike PageRank, with modularity we do not leave the configuration established, but we uncheck the box of &#8216;use weights&#8217;.\n\nModularity groups pages that are more connected to each other into groups or <strong>classes.<\/strong> Each represented by a number. For example, in our case, which we are analyzing &#8216;www.arimetrics.com&#8217;, the blog links could be represented as follows:\n\nGroup 1: Blog\n\nGroup 2: Digital Glossary\n\nGroup 3: Services\n\nTo check that the process we have followed was correct, just go to the &#8216;data laboratory&#8217; (upper left corner) and check that two new columns have been generated with &#8216;PageRank&#8217; and &#8216;modularity&#8217;. In the latter, it is convenient to see that the sections that have been grouped together make sense.\n<h2>4. <strong>We started visualizing internal links with Gephi<\/strong><\/h2>\nOnce all the above steps have been done, the time has come to shape our<strong> visualization of internal links with Gephi.<\/strong> The first thing you need to do is select a chart model in the &#8216;distribution&#8217; tab on the left. In this case, we select &#8216;ForceAtlas 2&#8217;.\n\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/Distribucin-ForceAtlas2.jpg\" alt=\"Distribution-ForceAtlas2\" width=\"1691\" height=\"997\" \/>\n\nNow, the parameters of this type of graph go to the taste of the consumer. It is about choosing what we like most visually or what we think will best represent the goal we are looking for. For this example what we have done is to modify the &#8216;gravity&#8217; section and change it to 0.7 and the &#8216;scaling&#8217; section up to 1000.\n\nClick on &#8216;run&#8217; and center the visualization on the screen with the magnifying glass that is in the lower left corner of the drawing. Now we should see something like this. Obviously, the display of <strong>internal links will change depending on how our website is structured.<\/strong>\n\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/visualizacin-con-gephi.jpg\" alt=\"visualization-with-gephi\" width=\"1688\" height=\"876\" \/>\n\nAs we have already said, our intention with this example is to represent the modularity and PageRank of our internal links. A useful way to do this is to adjust the <strong>size of the nodes based on PageRank<\/strong> and colors in <strong>modularity.<\/strong> In this way, the larger the nodes, the better positioning in the ranking and the more grouped the colors are, the better hierarchy of our website.\n\nTo do this, we will be placed in the &#8216;appearance&#8217; window on the left, select nodes, partition and choose modularity. To see the results click on &#8216;apply&#8217;.\n\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/modularidad-gephi.jpg\" alt=\"modularity-gephi\" width=\"1691\" height=\"986\" \/>\n\nNext, we select &#8216;nodes&#8217;, &#8216;ranking&#8217; and choose Page Rank. You can also change the parameters as appropriate. Click on apply.\n\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/visualizacion-links-gephi-pagerank.jpg\" alt=\"visualization-links-gephi-pagerank\" width=\"1713\" height=\"924\" \/>\n<h3>4.1. Modifying the display with Gephi<\/h3>\nNow, to give greater meaning to the visualization, it is advisable to tag the nodes to know what each page represents, either with the URL, anchor text&#8230; whatever we want to visualize. Of course, before it will be necessary to make small modifications in our database. For example, if we want to add a tag with the URL, we have to go to the &#8216;data lab&#8217; tab. Once here, we will select in the boxes below &#8216;copy data to another column&#8217;, and copy from &#8216;d&#8217; to &#8216;label&#8217; or &#8216;label&#8217;. In short, the idea is to put in &#8216;label&#8217; what we want to be visualized.\n\nNow, we return to the &#8216;preview&#8217; tab and we can already shape our <strong>internal link display.<\/strong> In the drop-down menu on the left, in default settings, the most common is to choose between: &#8216;by default&#8217; or &#8216;by default-Curved edges&#8217;. To see the changes we are making, click on the refresh button at the bottom left.\n\nIn this way, this is how our visualization of internal links with Gephi would look:\n\n<img decoding=\"async\" src=\"https:\/\/www.arimetrics.com\/wp-content\/uploads\/2020\/02\/links-internos-gephi.jpg\" alt=\"links-internal-gephi\" width=\"902\" height=\"744\" \/>\n\nIn the parameters menu, we can change the display according to our tastes or needs. Change font size, labels, etc. It is enough to refresh and choose, finally, the option that best suits us.\n\nIn the visualization of internal links above, the tags of nodes and borders are not activated, so as not to reveal the identity of the same. But what we can interpret with this graph is that there is an <strong>optimal hierarchy of internal backlinks,<\/strong>because the pages are grouped by blocks and linked internally. Remember that each color corresponds to a section of the web and the size of the nodes corresponds to the PageRank calculated by Gephi.\n\nIn this type of graphics, it would also be interesting to show the anchor text in the labels, to see if they also meet the same hierarchy. That&#8217;s why it&#8217;s critical to know what you want to visualize before importing your spreadsheet into Gephi.\n\n\n<p>It may also be useful to review this related article: <a href=\"https:\/\/www.arimetrics.com\/en\/blog\/what-is-seo\">what is seo<\/a>, to place connected concepts within a broader digital strategy.<\/p>\n\n\n\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@graph\": [\n    {\n      \"@type\": \"BlogPosting\",\n      \"@id\": \"https:\/\/www.arimetrics.com\/en\/blog\/viewing-internal-links-with-gephi#blogposting\",\n      \"mainEntityOfPage\": {\n        \"@type\": \"WebPage\",\n        \"@id\": \"https:\/\/www.arimetrics.com\/en\/blog\/viewing-internal-links-with-gephi\"\n      },\n      \"headline\": \"Viewing internal links with Gephi\",\n      \"description\": \"One of the practices that tends to favor search engine positioning is the generation of links on a website. 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They are usually exported from an SEO crawler.<\/p>\n  <\/details>\n  <details class=\"geo-faq-item\">\n    <summary>Which Gephi metrics are useful for SEO?<\/summary>\n    <p>Useful metrics may include in-degree, out-degree, internal PageRank, modularity, communities, centrality and isolated nodes. Interpretation should be connected to architecture and SEO goals.<\/p>\n  <\/details>\n  <details class=\"geo-faq-item\">\n    <summary>How can internal linking be improved after analysis?<\/summary>\n    <p>Strengthen strategic pages, reduce depth, link related content, fix orphan pages, remove broken links and ensure categories, hubs and transactional pages receive clear signals.<\/p>\n  <\/details>\n<\/div>\n\n\n\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"@id\": \"https:\/\/www.arimetrics.com\/en\/blog\/viewing-internal-links-with-gephi\/#faq\",\n  \"inLanguage\": \"en-US\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is the purpose of viewing internal links with Gephi?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Viewing internal links with Gephi helps understand how authority is distributed, which pages are isolated, which nodes concentrate links and how to improve architecture, crawling and strategic internal linking.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What data is needed to analyze internal links in Gephi?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"URLs, links between pages, status codes, depth, anchors and, when possible, traffic, crawl or business metrics are needed. 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Validate data, search intent and the competitive context. Connect execution with measurement, learning and continuous improvement. Aspect What to review Useful indicator Viewing internal links with Gephi Goal, audience and expected impact Qualified traffic, leads or conversions Execution Channels, content and required resources Implementation quality and [&hellip;]<\/p>\n","protected":false},"author":14,"featured_media":24140,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[275],"tags":[],"class_list":["post-20957","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-strategy"],"_links":{"self":[{"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/posts\/20957","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/comments?post=20957"}],"version-history":[{"count":4,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/posts\/20957\/revisions"}],"predecessor-version":[{"id":71421,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/posts\/20957\/revisions\/71421"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/media\/24140"}],"wp:attachment":[{"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/media?parent=20957"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/categories?post=20957"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.arimetrics.com\/en\/wp-json\/wp\/v2\/tags?post=20957"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}