{"id":581,"date":"2025-12-18T23:01:59","date_gmt":"2025-12-18T21:01:59","guid":{"rendered":"https:\/\/www.etkad.ee\/?page_id=581"},"modified":"2026-03-25T12:03:01","modified_gmt":"2026-03-25T12:03:01","slug":"suurel-skaalal-ngrammidega","status":"publish","type":"post","link":"https:\/\/www.etkad.ee\/en\/humal\/toovood\/suurel-skaalal-ngrammidega\/","title":{"rendered":"Large-scale study of attention change trends using ngrams"},"content":{"rendered":"<div class=\"wp-block-group alignfull is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"kb-row-layout-wrap kb-row-layout-id581_2250d3-34 alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-2-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n\n<div class=\"wp-block-kadence-column kadence-column581_74c2a8-f5\"><div class=\"kt-inside-inner-col\">\n<p class=\"kt-adv-heading581_1c7d04-1e_0 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading581_1c7d04-1e_0\">The workflow enables the analysis of mention frequencies across different categories over long time periods or with dense data, in order to reveal similarities and emerging patterns. Data is aggregated into matrices, which are used to create<em>heatmaps<\/em>that allow large datasets to be presented visually in a clear and comparable manner. These visuals can be read both across time and across categories, enabling the comparison of different periods and topics, and combining intuitive qualitative visual analysis with quantitative methods. Mathematical transformations (e.g., normalization and logarithmic transformation) are applied to highlight relationships from different perspectives, especially when data values vary greatly. Additional perspectives are provided by other data science methods, such as time series vectorization and clustering.<\/p>\n\n\n\n<p class=\"kt-adv-heading581_1c7d04-1e_1 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading581_1c7d04-1e_1\">In our example, we studied the mention frequency of the word \u201cUkraine\u201d in 28 different languages over 15 years in the Twitter (now X) dataset, based on data obtained from the public API. The goal was to understand how and when attention directed at Ukraine in different languages increased or decreased.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-column kadence-column581_47a758-29\"><div class=\"kt-inside-inner-col\">\n<ul class=\"wp-block-list has-theme-palette-8-background-color has-background\">\n<li><strong>Authors:<\/strong>\n<ul class=\"wp-block-list\">\n<li><a href=\"\/en\/humal\/mark-mets\/\" data-type=\"page\" data-id=\"117\">Mark Mets<\/a> (Tallinn University, Estonian Literary Museum)<\/li>\n\n\n\n<li>Maximilian Schich (Tallinn University)<\/li>\n\n\n\n<li>Peter S. Dodds (University of Vermont, USA)<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Licence:<\/strong> <a href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/deed.et\" target=\"_blank\" rel=\"noreferrer noopener\">CC-BY<\/a><\/li>\n\n\n\n<li><strong>Date\/version: <\/strong>24.03.2026 v2<\/li>\n\n\n\n<li><strong>Keywords (content):<\/strong> <a href=\"https:\/\/ems.elnet.ee\/id\/EMS007448\" target=\"_blank\" rel=\"noreferrer noopener\">vector analysis<\/a>, <a href=\"https:\/\/ems.elnet.ee\/id\/EMS141995\" target=\"_blank\" rel=\"noreferrer noopener\">transformations<\/a>, <a href=\"https:\/\/ems.elnet.ee\/id\/EMS021875\" target=\"_blank\" rel=\"noreferrer noopener\">visualization<\/a>, <a href=\"https:\/\/ems.elnet.ee\/id\/EMS172055\" target=\"_blank\" rel=\"noreferrer noopener\">interdisciplinarity<\/a>, <a href=\"https:\/\/ems.elnet.ee\/id\/EMS132119\" target=\"_blank\" rel=\"noreferrer noopener\">Ukraine<\/a>, <a href=\"https:\/\/ems.elnet.ee\/id\/EMS163206\" target=\"_blank\" rel=\"noreferrer noopener\">social media<\/a>, <a href=\"https:\/\/ems.elnet.ee\/id\/EMS162132\" target=\"_blank\" rel=\"noreferrer noopener\">Twitter<\/a>, <a href=\"https:\/\/ems.elnet.ee\/id\/EMS000555\" target=\"_blank\" rel=\"noreferrer noopener\">attention<\/a>, time series, n-gram<\/li>\n\n\n\n<li><strong>Keywords (<a href=\"https:\/\/tadirah.info\/index.html\" target=\"_blank\" rel=\"noreferrer noopener\">Tadirah<\/a>):<\/strong> <a href=\"\/en\/humal\/toovood\/marksonad\/andmete-visualiseerimine\/\" data-type=\"marksonad\" data-id=\"60\">Data Visualization<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/jarjestuste-joondamine\/\" data-type=\"marksonad\" data-id=\"148\">Sequence alignment<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/kauguse-mootmine\/\" data-type=\"marksonad\" data-id=\"71\">Distance measurement<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/pohikomponentide-analuus\/\">Principal component analysis<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/klasteranaluus\/\" data-type=\"marksonad\" data-id=\"35\">Cluster analysis<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/andmekaeve\/\" data-type=\"marksonad\" data-id=\"58\">Data mining<\/a><\/li>\n\n\n\n<li><strong>Subject field: <\/strong><a href=\"https:\/\/www.etkad.ee\/en\/eriala\/kultuuride-uuringud\/\" data-type=\"eriala\" data-id=\"83\">cultural studies<\/a><\/li>\n\n\n\n<li><strong>Data media type:<\/strong> <a href=\"https:\/\/www.etkad.ee\/en\/andmete-meediatuup\/metaandmed\/\" data-type=\"andmete-meediatuup\" data-id=\"86\">metadata<\/a>, <a href=\"https:\/\/www.etkad.ee\/en\/andmete-meediatuup\/tekst\/\" data-type=\"andmete-meediatuup\" data-id=\"91\">text<\/a><\/li>\n\n\n\n<li><strong>Output:<\/strong><a href=\"https:\/\/www.etkad.ee\/en\/valjund\/visualiseering\/\" data-type=\"valjund\" data-id=\"98\"> visualisation<\/a>, <a href=\"https:\/\/www.etkad.ee\/en\/valjund\/teadusartikkel\/\" data-type=\"valjund\" data-id=\"97\">scholarly article<\/a><\/li>\n\n\n\n<li><strong>Related materials: <\/strong>\n<ul class=\"wp-block-list\">\n<li>Artikkel: Mets, M., Dodds, P. S., Schich, M. (2026). Crisis-induced differences in attention towards Ukraine in Twitter 2008-2023. arXiv preprint <a href=\"https:\/\/arxiv.org\/abs\/2603.17899\">arXiv:2603.17899<\/a>.<\/li>\n\n\n\n<li>Kood: <a href=\"https:\/\/github.com\/markmets\/Ukraine-Twitter\">https:\/\/github.com\/markmets\/Ukraine-Twitter<\/a><\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Reference:<\/strong> Mets, Mark, Schich, Maximilian, Dodds, Peter S. (2026) Large-scale study of attention change trends using ngrams <a href=\"https:\/\/www.etkad.ee\/en\/humal\/toovood\/suurel-skaalal-ngrammidega\/\">https:\/\/www.etkad.ee\/humal\/toovood\/suurel-skaalal-ngrammidega\/ <\/a><\/li>\n<\/ul>\n<\/div><\/div>\n\n<\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-column kadence-column581_47a9f8-8e\"><div class=\"kt-inside-inner-col\">\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;69de8814f1b6d&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"69de8814f1b6d\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"950\" height=\"804\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/www.etkad.ee\/wp-content\/uploads\/2026\/03\/Twitter_2026marts_eng.png\" alt=\"\" class=\"wp-image-1647\" srcset=\"https:\/\/www.etkad.ee\/wp-content\/uploads\/2026\/03\/Twitter_2026marts_eng.png 950w, https:\/\/www.etkad.ee\/wp-content\/uploads\/2026\/03\/Twitter_2026marts_eng-300x254.png 300w, https:\/\/www.etkad.ee\/wp-content\/uploads\/2026\/03\/Twitter_2026marts_eng-768x650.png 768w, https:\/\/www.etkad.ee\/wp-content\/uploads\/2026\/03\/Twitter_2026marts_eng-14x12.png 14w\" sizes=\"auto, (max-width: 950px) 100vw, 950px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewbox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-group alignfull is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"kb-row-layout-wrap kb-row-layout-id581_187d75-5f alignfull has-light-beige-background-color kt-row-has-bg wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top kb-theme-content-width\">\n\n<div class=\"wp-block-kadence-column kadence-column581_807258-40 kb-section-dir-vertical inner-column-1\"><div class=\"kt-inside-inner-col\"><div class=\"kb-row-layout-wrap kb-row-layout-id581_4629f9-22 alignnone wp-block-kadence-rowlayout\"><div class=\"kt-row-column-wrap kt-has-1-columns kt-row-layout-equal kt-tab-layout-inherit kt-mobile-layout-row kt-row-valign-top\">\n\n<div class=\"wp-block-kadence-column kadence-column581_4a6850-d7\"><div class=\"kt-inside-inner-col\">\n<h1 class=\"kt-adv-heading581_aa5deb-81 wp-block-kadence-advancedheading has-theme-palette-3-color has-text-color\" data-kb-block=\"kb-adv-heading581_aa5deb-81\">Workflow steps<\/h1>\n\n\n\n<div class=\"wp-block-kadence-accordion alignnone\"><div class=\"kt-accordion-wrap kt-accordion-id581_54d1e0-4d kt-accordion-has-9-panes kt-active-pane-0 kt-accordion-block kt-pane-header-alignment-left kt-accodion-icon-style-basic kt-accodion-icon-side-left\" style=\"max-width:none\"><div class=\"kt-accordion-inner-wrap\" data-allow-multiple-open=\"false\" data-start-open=\"0\">\n<div class=\"wp-block-kadence-pane kt-accordion-pane kt-accordion-pane-1 kt-pane581_39f76a-f0\"><div class=\"kt-accordion-header-wrap\"><button class=\"kt-blocks-accordion-header kt-acccordion-button-label-show\" type=\"button\"><span class=\"kt-blocks-accordion-title-wrap\"><span class=\"kt-blocks-accordion-title\">1. Data acquisition and cleaning into a format suitable for analysis<\/span><\/span><span class=\"kt-blocks-accordion-icon-trigger\"><\/span><\/button><\/div><div class=\"kt-accordion-panel kt-accordion-panel-hidden\"><div class=\"kt-accordion-panel-inner\">\n<p><strong>Keywords:<\/strong> <a href=\"\/en\/humal\/toovood\/marksonad\/kontseptualiseerimine\/\" data-type=\"marksonad\" data-id=\"45\">Conceptualization<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/avastamine\/\" data-type=\"marksonad\" data-id=\"68\">Discovering<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/paringud\/\" data-type=\"marksonad\" data-id=\"135\">Inquiries<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/eeltootlus\/\" data-type=\"marksonad\" data-id=\"128\">Preprocessing<\/a><\/p>\n\n\n\n<p>The goal of this stage was to select the research topic, initial research questions, and dataset, as well as to download the data and format it appropriately. In our example study, we used the <a href=\"https:\/\/storywrangling.org\/\" target=\"_blank\" rel=\"noreferrer noopener\">Storywrangler open data API<\/a>, which contains Twitter tweet usage frequencies over its usage history, until the closure of large-scale scientific use of Twitter in 2023. The goal was to obtain frequencies of tweets concerning Ukraine. For this, we selected the most suitable keywords referring to \u201cUkraine\u201d in different languages, which involved translation and conducting initial test searches in the database.<\/p>\n\n\n\n<p>Each downloaded keyword was added to a single table containing the category of interest (in our example, language) and the frequency for each day over a 15-year period. This table serves as the input for further analysis.<\/p>\n<\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-pane kt-accordion-pane kt-accordion-pane-2 kt-pane581_c84f7c-70\"><div class=\"kt-accordion-header-wrap\"><button class=\"kt-blocks-accordion-header kt-acccordion-button-label-show\" type=\"button\"><span class=\"kt-blocks-accordion-title-wrap\"><span class=\"kt-blocks-accordion-title\">2. Initial exploratory data analysis<\/span><\/span><span class=\"kt-blocks-accordion-icon-trigger\"><\/span><\/button><\/div><div class=\"kt-accordion-panel kt-accordion-panel-hidden\"><div class=\"kt-accordion-panel-inner\">\n<p><strong>Keywords:<\/strong> <a href=\"\/en\/humal\/toovood\/marksonad\/andmete-visualiseerimine\/\" data-type=\"marksonad\" data-id=\"60\">Data Visualization<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/eeltootlus\/\" data-type=\"marksonad\" data-id=\"128\">Preprocessing<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/uurimine\/\" data-type=\"marksonad\" data-id=\"80\">Exploration<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/jarjestuste-joondamine\/\" data-type=\"marksonad\" data-id=\"148\">Sequence alignment<\/a><\/p>\n\n\n\n<p>This stage consisted of creating initial data plots through trial and error, which provided an overview of the dataset and helped identify the most important patterns. First, we experimented with line charts, which are difficult to read for distinguishing and comparing 28 variables, then we created an initial version of a heatmap in Excel. We also experimented with different transformations, such as logarithmic scale and accounting for the expected attention share in different languages.<\/p>\n\n\n\n<p>As a result of this stage, an initial overview of the data and key findings was obtained. The most useful data transformation methods and visualization approaches for providing an overview were identified.<\/p>\n<\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-pane kt-accordion-pane kt-accordion-pane-3 kt-pane581_213e81-80\"><div class=\"kt-accordion-header-wrap\"><button class=\"kt-blocks-accordion-header kt-acccordion-button-label-show\" type=\"button\"><span class=\"kt-blocks-accordion-title-wrap\"><span class=\"kt-blocks-accordion-title\">3. Additional analyses and visualization<\/span><\/span><span class=\"kt-blocks-accordion-icon-trigger\"><\/span><\/button><\/div><div class=\"kt-accordion-panel kt-accordion-panel-hidden\"><div class=\"kt-accordion-panel-inner\">\n<p><strong>Keywords:<\/strong> <a href=\"\/en\/humal\/toovood\/marksonad\/andmete-visualiseerimine\/\" data-type=\"marksonad\" data-id=\"60\">Data Visualization<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/uurimine\/\" data-type=\"marksonad\" data-id=\"80\">Exploration<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/jarjestuste-joondamine\/\" data-type=\"marksonad\" data-id=\"148\">Sequence alignment<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/kauguse-mootmine\/\" data-type=\"marksonad\" data-id=\"71\">Distance measurement<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/pohikomponentide-analuus\/\" data-type=\"marksonad\" data-id=\"131\">Principal component analysis<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/klasteranaluus\/\" data-type=\"marksonad\" data-id=\"35\">Cluster analysis<\/a><\/p>\n\n\n\n<p>In this stage, we analyzed the initial results and visualizations and created more precise figures and additional analyses based on them. We transferred the initial heatmap created in Excel to Python and selected suitable libraries and visual expression methods. Additionally, we applied vector analysis and clustering for closer analysis, along with supporting visualizations.<\/p>\n\n\n\n<p>For the additional analyses, we drew on the initial results, which pointed to the most significant time periods according to languages, such as, expectedly, the 2014 and 2022 Russian invasions of Ukraine. The result was visualizations based on multiple computational methods and overviews of the main patterns.<\/p>\n<\/div><\/div><\/div>\n\n\n\n<div class=\"wp-block-kadence-pane kt-accordion-pane kt-accordion-pane-4 kt-pane581_58519b-0d\"><div class=\"kt-accordion-header-wrap\"><button class=\"kt-blocks-accordion-header kt-acccordion-button-label-show\" type=\"button\"><span class=\"kt-blocks-accordion-title-wrap\"><span class=\"kt-blocks-accordion-title\">4. Structured description of results<\/span><\/span><span class=\"kt-blocks-accordion-icon-trigger\"><\/span><\/button><\/div><div class=\"kt-accordion-panel kt-accordion-panel-hidden\"><div class=\"kt-accordion-panel-inner\">\n<p><strong>Keywords:<\/strong> <a href=\"\/en\/humal\/toovood\/marksonad\/visuaalne-analuus\/\" data-type=\"marksonad\" data-id=\"178\">Visual analysis<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/modelleerimine\/\" data-type=\"marksonad\" data-id=\"111\">Modeling<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/teooria-loomine\/\" data-type=\"marksonad\" data-id=\"163\">Theorizing<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/kontekstualiseerimine\/\" data-type=\"marksonad\" data-id=\"48\">Contextualizing<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/disain\/\" data-type=\"marksonad\" data-id=\"64\">Design<\/a>, <a href=\"\/en\/humal\/toovood\/marksonad\/kirjutamine\/\" data-type=\"marksonad\" data-id=\"184\">Writing<\/a><\/p>\n\n\n\n<p>The goal of this stage was to systematically record and interpret the results that emerged from the previous analyses, and to annotate visualizations where necessary. We refined figures to highlight the most important aspects (such as specific events or periods) and developed a suitable narrative for presentations and scientific articles.<\/p>\n\n\n\n<p>For example, we selected the most central visualizations and annotated them in image editing software. We confirmed suitable theoretical frameworks and finalized the literature review. We organized the article and figures based on the narrative, for instance by dividing the analysis sections into micro-, meso-, and macro-levels, which related different methods and results to each other.<\/p>\n<\/div><\/div><\/div>\n<\/div><\/div><\/div>\n<\/div><\/div>\n\n<\/div><\/div><\/div><\/div>\n\n<\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"<p>T\u00f6\u00f6voog v\u00f5imaldab anal\u00fc\u00fcsida eri kategooriate mainimissagedusi pika ajavahemiku jooksul v\u00f5i tihedate andmetega, et teha n\u00e4htavaks sarnasused ja t\u00f5statuvad mustrid. Andmed koondatakse maatriksiteks, mille p\u00f5hjal luuakse kuumkaarte (heatmap\u2019e), mis v\u00f5imaldavad esitada suuri andmehulkasid visuaalselt selgelt ja v\u00f5rreldavalt. Neid visuaale saab lugeda nii ajas kui ka kategooriate l\u00f5ikes, mis teeb v\u00f5imalikuks eri perioodide ja teemade k\u00f5rvutamise ning [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[77],"tags":[],"marksonad":[9,11,35,13,14,62,63,64,17,19,65,41,66,67,68,44,45],"eriala":[],"valjund":[],"andmete-meediatuup":[],"class_list":["post-581","post","type-post","status-publish","format-standard","hentry","category-toovood","marksonad-andmekaeve","marksonad-andmete-visualiseerimine","marksonad-avastamine","marksonad-disain","marksonad-eeltootlus","marksonad-jarjestuste-joondamine","marksonad-kauguse-mootmine","marksonad-kirjutamine","marksonad-klasteranaluus","marksonad-kontekstualiseerimine","marksonad-kontseptualiseerimine","marksonad-modelleerimine","marksonad-paringud","marksonad-pohikomponentide-analuus","marksonad-teooria-loomine","marksonad-uurimine","marksonad-visuaalne-analuus"],"_links":{"self":[{"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/posts\/581","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/comments?post=581"}],"version-history":[{"count":34,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/posts\/581\/revisions"}],"predecessor-version":[{"id":1652,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/posts\/581\/revisions\/1652"}],"wp:attachment":[{"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/media?parent=581"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/categories?post=581"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/tags?post=581"},{"taxonomy":"marksonad","embeddable":true,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/marksonad?post=581"},{"taxonomy":"eriala","embeddable":true,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/eriala?post=581"},{"taxonomy":"valjund","embeddable":true,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/valjund?post=581"},{"taxonomy":"andmete-meediatuup","embeddable":true,"href":"https:\/\/www.etkad.ee\/en\/wp-json\/wp\/v2\/andmete-meediatuup?post=581"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}