{"id":2856,"date":"2015-10-07T18:00:20","date_gmt":"2015-10-07T12:30:20","guid":{"rendered":"http:\/\/rankwatch.com\/blog\/?p=2856"},"modified":"2024-01-15T12:45:43","modified_gmt":"2024-01-15T07:15:43","slug":"3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search","status":"publish","type":"post","link":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/","title":{"rendered":"3 reasons for copywriters to relax: keyword density, TF-IDF, and semantic search"},"content":{"rendered":"

Content is for humans. But humans find content by using search engines.<\/strong><\/p>\n

For each query, Google retrieves the most relevant pages from its databases. As a professional SEO copywriter, you do believe that your webpage is the best one out of all indexed pages. However, Google\u2019s bots might not share your opinion.<\/p>\n

To avoid misunderstanding with search engine bots, you are trying to understand what they take into account while estimating your content\u2019s quality.<\/p>\n

But sometimes, while analysing ranking factors, you get confused. Are you targeting the right keywords? Should you add more of them into your post? Oh, may this be considered spam? Should you then remove them?<\/p>\n

Do you want to focus on producing SEO-friendly content without constantly wondering whether or not it would pass search engine crawlers\u2019 checks? Then, read on!<\/p>\n

In this post, we will take a closer look at keyword density, TF-IDF and semantic search. Personally, these three phenomena were my biggest SEO confusions. That\u2019s why today I propose to discuss how to approach them.<\/p>\n

Should keyword density stay or go?<\/h2>\n

\u201cKeyword density is a SEO myth. There is no ideal percent of keywords. Measuring percentage of keywords is a waste of time.<\/strong>\u201d This is what we hear the most about this phenomenon, and this sounds quite logical.<\/p>\n

Search engines are smart, and they use complicated information retrieval mechanisms. That\u2019s why it would be naive to believe that we can seduce search bots by incorporating more keywords into a webpage.<\/p>\n

So, dear SEO copywriters, breathe\u00a0a deep\u00a0sigh of relief, and forget about counting keywords! Instead, focus on their placement in your copy.<\/p>\n

For purposes of making your content more understandable for bots and more eye-catching for humans, make sure that you have your target keywords in:<\/p>\n

(Strongly recommended)<\/p>\n

    \n
  1. \n

    Title tag<\/p>\n<\/li>\n

  2. \n

    Meta description<\/p>\n<\/li>\n

  3. \n

    H1 tag<\/p>\n<\/li>\n<\/ol>\n

    (Optionally, in case if relevant)<\/p>\n

      \n
    1. \n

      Sub-headings (h2, h3, etc.)<\/p>\n<\/li>\n

    2. \n

      ALT texts and names of images<\/p>\n<\/li>\n

    3. \n

      The URL of a webpage.<\/p>\n<\/li>\n<\/ol>\n

      As for keyword usage in the <body> element of your webpage, it is crucial not to overuse terms.<\/p>\n

      This is when keyword density analysis tools come handy. They help us avoid keyword stuffing by analysing information on counts and percentage of a keyword or phrase within a webpage, its body, title, meta description, URL, etc.\u00a0<\/b><\/b><\/p>\n

      Here are few tools you can use to check whether or not your copy is overloaded with particular keywords:<\/p>\n

        \n
      1. Keyword Density Analysis tool by Internet Mar<\/a>k<\/a>eting Ninjas<\/a><\/strong><\/strong>\"\"<\/a><\/li>\n
      2. Plugin Seoq<\/a>uake<\/a><\/strong><\/strong>\"\"<\/a><\/li>\n
      3. \"SEOquake-Density\"<\/a><\/li>\n
      4. Keyword Density Analyzer by SEO book<\/a><\/strong><\/strong>\"\"<\/a><\/li>\n
      5. By the way, if you ever see that your copy has too many \u201cto\u201d, \u201cyou\u201d, \u201cand\u201d, don\u2019t worry.<\/span><\/span><\/li>\n<\/ol>\n

        \"\"<\/a><\/p>\n

        Should I worry about TF-IDF?<\/h2>\n

        The TF-IDF algorithm goes beyond counting how many times a term appeared on a webpage. It determines a term\u2019s significance (or weight) by calculating its frequency within a specific document compared to the inverse proportion of this term over the entire collection of documents (or a corpus).<\/p>\n

        Terms that appear in a small group of documents will have higher TF-IDF weight than common words such as articles and prepositions.<\/p>\n

        Summing the TF-IDF for each query term in a search phrase can serve as one of ranking factors.<\/p>\n

        The Term Frequency (TF)<\/strong> shows a keyword or phrase\u2019s importance within a single document, and it can be simply represented by raw frequency:<\/p>\n

        \n\n\n\n<\/colgroup>\n\n\n
        \n

        TF \u00a0\u00a0=<\/strong><\/p>\n<\/td>\n

        		\n

        number of times a word appeared in a document<\/strong><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

        \u00a0<\/b><\/b>In order to normalize the TF value with respect to the document length, term frequency can be divided by the total number of terms in a document:<\/p>\n

        \n\n\n\n<\/colgroup>\n\n\n
        \n

        TF \u00a0\u00a0=<\/strong><\/p>\n<\/td>\n

        		\n

        number of times a word appeared in a document \/<\/strong><\/p>\n

        total number of words in a document<\/strong><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

        You can also find more variants to calculate term frequency:<\/p>\n

        \"\"<\/a><\/p>\n

        In this post, we will use the first two variants.<\/p>\n

        The Inverse Document Frequency (IDF) represents a term\u2019s significance over a corpus, and it can be calculated based on the following formula:<\/p>\n

        \n\n\n\n<\/colgroup>\n\n\n
        \n

        IDF \u00a0\u00a0=<\/strong><\/p>\n<\/td>\n

        		\n

        log (number of documents in a corpus\/ number of documents containing a word)<\/strong><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

        \u00a0<\/b><\/b>The use of logarithms (here the base of the log is 10) serves to weigh down more frequent terms and to add more weight to rare ones.<\/p>\n

        What did you say?! Logarithm?!!<\/p>\n

        \"\"<\/a><\/p>\n

        No worries, guys! I wasn\u2019t a big fan of logarithmic quotations in high school neither. So pinky swear, no complex calculations.<\/p>\n

        To get the TF-IDF score, we should simply multiply Term Frequency by Inverse Document Frequency:<\/p>\n

        Formula 1<\/strong><\/p>\n

        \n\n\n\n\n\n<\/colgroup>\n\n\n
        \n

        TF-IDF score \u00a0=<\/p>\n<\/td>\n

        		\n

        number of times a word appeared in a document<\/p>\n<\/td>\n

        		\n

        *<\/p>\n<\/td>\n

        		\n

        (log (number of documents in a corpus \/ \u00a0\u00a0\u00a0\u00a0\u00a0number of documents containing a word))<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

        Or<\/p>\n

        Formula 2<\/strong><\/p>\n

        \n\n\n\n\n\n<\/colgroup>\n\n\n
        \n

        TF-IDF score \u00a0=<\/p>\n<\/td>\n

        		\n

        number of times a word appeared in a document\/<\/p>\n

        total number of words in a document<\/p>\n<\/td>\n

        		\n

        *<\/p>\n<\/td>\n

        		\n

        log (number of documents in a corpus number of documents containing a word)<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

        \u00a0<\/b><\/b><\/p>\n

        Let\u2019s use these formulas and our imagination to better understand what TF-IDF means.<\/p>\n

        Imagine, we want to write an article using the term \u201cfolding bike\u201d and to calculate its weight. We also have an imaginary collection of 10,000 webpages related to transport, and only 800 webpages containing both \u201cfolding\u201d and \u201cbike\u201d terms. We have already data for the IDF calculation:<\/p>\n

          \n
        1. \n

          the number of documents in a corpus: 10,000<\/em><\/p>\n<\/li>\n

        2. \n

          the number of documents containing a term: 800.<\/em><\/p>\n<\/li>\n<\/ol>\n

          One more imagined condition is that three pages of our collection appeared at the top of Google\u2019s search results for the query \u201cfolding bike\u201d. Logically, the webpage with the highest TF-IDF should pop up on the first position, and the one with the lowest score should appear at the third position. Let\u2019s check this idea.<\/p>\n

          \"\"<\/a><\/p>\n

          For this purpose, let\u2019s create a term count table containing the number of times words \u201cfolding\u201d and \u201cbike\u201d appeared in a webpage, as well as the total number of words per article:<\/p>\n

          \n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n
          \n

          Position<\/p>\n<\/td>\n

          		\n

          URL of a document<\/p>\n<\/td>\n

          		\n

          folding<\/p>\n<\/td>\n

          		\n

          bikes<\/p>\n<\/td>\n

          		\n

          total<\/p>\n<\/td>\n<\/tr>\n

          \n

          1<\/p>\n<\/td>\n

          		\n

          https:\/\/en.wikipedia.org\/wiki\/Folding_bicycle<\/a><\/p>\n<\/td>\n

          		\n

          64<\/p>\n<\/td>\n

          		\n

          33<\/p>\n<\/td>\n

          		\n

          2324<\/p>\n<\/td>\n<\/tr>\n

          \n

          2<\/p>\n<\/td>\n

          		\n

          http:\/\/www.independent.co.uk\/life-style\/the-10-best-folding-bikes-8683766.html<\/p>\n<\/td>\n

          		\n

          17<\/p>\n<\/td>\n

          		\n

          14<\/p>\n<\/td>\n

          		\n

          1197<\/p>\n<\/td>\n<\/tr>\n

          \n

          3<\/p>\n<\/td>\n

          		\n

          http:\/\/www.nycewheels.com\/compact-bikes.html<\/p>\n<\/td>\n

          		\n

          31<\/p>\n<\/td>\n

          		\n

          44<\/p>\n<\/td>\n

          		\n

          1087<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

          *The SEO Keyword Density checker was used for counting words.<\/p>\n

          Now, let\u2019s use this data to calculate the TF-IDF score separately for words \u201cfolding\u201d and \u201cbike\u201d for each document, and then sum up their values.<\/p>\n

          It\u2019s time to incorporate data into our formulas. As promised, using logarithms won\u2019t require you any additional efforts. Just use Google\u2019s search bar, and you\u2019ll get the TF-IDF almost automagically!<\/p>\n

          \"Calculation\"<\/a><\/p>\n

          By using the Formula 1, we\u2019ve got the following results:<\/p>\n

          \n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n
          \n

          Position<\/p>\n<\/td>\n

          		\n

          URL<\/p>\n<\/td>\n

          		\n

          TF-IDF folding<\/p>\n<\/td>\n

          		\n

          TF-IDF<\/p>\n

          bikes<\/p>\n<\/td>\n

          		\n

          TF-IDF<\/p>\n

          Sum<\/p>\n<\/td>\n<\/tr>\n

          \n

          1<\/p>\n<\/td>\n

          		\n

          https:\/\/en.wikipedia.org\/wiki\/Folding_bicycle<\/a><\/p>\n<\/td>\n

          		\n

          70.2022408325<\/p>\n<\/td>\n

          		\n

          36.1980304293<\/p>\n<\/td>\n

          		\n

          106.400271262<\/p>\n<\/td>\n<\/tr>\n

          \n

          2<\/p>\n<\/td>\n

          		\n

          http:\/\/www.independent.co.uk\/life-style\/the-10-best-folding-bikes-8683766.html<\/a><\/p>\n<\/td>\n

          		\n

          18.6474702211<\/p>\n<\/td>\n

          		\n

          15.3567401821<\/p>\n<\/td>\n

          		\n

          34.0042104032<\/p>\n<\/td>\n<\/tr>\n

          \n

          3<\/p>\n<\/td>\n

          		\n

          http:\/\/www.nycewheels.com\/compact-bikes.html<\/a><\/p>\n<\/td>\n

          		\n

          34.0042104032<\/p>\n<\/td>\n

          		\n

          48.2640405724<\/p>\n<\/td>\n

          		\n

          82.2682509756<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

          \u00a0<\/b><\/b><\/p>\n

          Surprisingly, the webpage from Independent.co.uk, which has a lower TF-IDF score than the article from Nycewheels.com, appears higher in search results:<\/p>\n

          \"\"<\/a><\/p>\n

          By using the Formula 2, we get the heaviest TF-IDF for the Nycewheels.com\u2019s article. But the post by Independent.co.uk still has the lowest score.<\/p>\n

          \n\n\n\n\n\n\n<\/colgroup>\n\n\n\n\n\n
          \n

          Position<\/p>\n<\/td>\n

          		\n

          URL<\/p>\n<\/td>\n

          		\n

          TF-IDF folding<\/p>\n<\/td>\n

          		\n

          TF-IDF bikes<\/p>\n<\/td>\n

          		\n

          Sum<\/p>\n<\/td>\n<\/tr>\n

          \n

          1<\/p>\n<\/td>\n

          		\n

          https:\/\/en.wikipedia.org\/wiki\/Folding_bicycle<\/a><\/p>\n<\/td>\n

          		\n

          0.03020750466<\/p>\n<\/td>\n

          		\n

          0.01557574459<\/p>\n<\/td>\n

          		\n

          0.04578324925<\/p>\n<\/td>\n<\/tr>\n

          \n

          2<\/p>\n<\/td>\n

          		\n

          http:\/\/www.independent.co.uk\/life-style\/the-10-best-folding-bikes-8683766.html<\/a><\/p>\n<\/td>\n

          		\n

          0.01557850477<\/p>\n<\/td>\n

          		\n

          0.01282935687<\/p>\n<\/td>\n

          		\n

          0.02840786164<\/p>\n<\/td>\n<\/tr>\n

          \n

          3<\/p>\n<\/td>\n

          		\n

          http:\/\/www.nycewheels.com\/compact-bikes.html<\/a><\/p>\n<\/td>\n

          		\n

          0.03128262226<\/p>\n<\/td>\n

          		\n

          0.04440114128<\/p>\n<\/td>\n

          		\n

          0.07568376354<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

          \u00a0<\/b><\/b><\/p>\n

          \"Keyword-density-score-distribution\"<\/a><\/p>\n

           <\/p>\n

           <\/p>\n

           <\/p>\n

          Surely, this is just an imaginary example. We don\u2019t know for sure the size of a corpus and the number of relevant documents Google analysed before listing search results. But hypothetically, we can still assume that, due to the little term frequency of the Independent.co.uk\u2019s document, its TF-IDF score will be dramatically lower than this one of Nycewheels.com\u2019s post.<\/p>\n

          Obviously, TF-IDF is just a part of the huge and complex Google\u2019s information retrieval and analysis mechanisms, and it doesn\u2019t have a direct impact on rankings.<\/p>\n

          So don\u2019t be stressed about your scores, but just try to make it more understandable. How? Of course, semantically!<\/p>\n

          Semantic research is the answer<\/h2>\n

          With the arrival of the Hummingbird algorithm, the keyword era ended. Since then, only the user-intent matters. What is the intent behind a user\u2019s search query? This is what you should keep in mind while editing your copy.<\/p>\n

          Your content should aim a specific intent and answer a particular user\u2019s question. Keywords are just tools for modelling your topic and help bots to extract contextual meaning.<\/p>\n

          For example, there are all kinds of synonyms and related terms for the phrase \u201cfolding bikes\u201d:<\/p>\n

          Synonyms<\/h3>\n

          Folding bicycle<\/p>\n

          Compact bicycle<\/p>\n

          Portable bike<\/p>\n

          Collapsible bike<\/p>\n

          Electric bike<\/p>\n

          Mountain bike<\/p>\n

          Road bikes<\/p>\n

          Antonyms<\/h3>\n

          Non-folding models<\/p>\n

          Standard bike<\/p>\n

          Regular bike<\/p>\n

          General notions<\/h3>\n

          Urban transport<\/p>\n

          Cycling<\/p>\n

          Features<\/h3>\n

          Folding mechanisms<\/p>\n

          Folding speed<\/p>\n

          Folding ease<\/p>\n

          Compactness<\/p>\n

          Compact mode<\/p>\n

          Folding version<\/p>\n

          Portability<\/p>\n

          Off-road riding<\/p>\n

          Material and elements<\/h3>\n

          Aluminium frame<\/p>\n

          Disc brakes<\/p>\n

          Gears<\/p>\n

          Folding pedals<\/p>\n

          Steel model<\/p>\n

          BMX wheels<\/p>\n

          Upgradeable frame<\/p>\n

          Brands<\/h2>\n

          DAHON JIFO<\/p>\n

          BIRDY TOURING DISC<\/p>\n

          STRIDA SX<\/p>\n

          And more!<\/p>\n

          You can combine the same keywords to cover different users’ needs. Decide what exactly you\u2019d like to cover: The best folding bike; Where to buy a folding bike; The cheapest folding bike; Folding bikes vs. Standard bikes; A folding bike for urban cycling; the best model of folding bikes for off-road riding; Steel vs. Aluminium models. Or something else.<\/p>\n

          Once you have a direction, make sure that you fully answer a user\u2019s question by providing him or her with information-rich and well-structured content. This way, the right keywords will come over naturally.<\/p>\n

          Final Thoughts<\/h2>\n

          Ranking factors and search algorithms constantly evolve and might seem confusing. But they all tend to provide a user with the best answers. So, if you do the same, relax and create great content:<\/p>\n

            \n
          1. \n

            Instead of stuffing your target keyword all over the webpage, make sure you place them in title and meta description tags, as well as in headings.<\/p>\n<\/li>\n

          2. \n

            Since less frequent terms might have more search weight, you can try more niche and low-volume keywords for your content.<\/p>\n<\/li>\n

          3. \n

            User-intent is everything, keywords are just tools.<\/p>\n<\/li>\n<\/ol>\n

            What is the most confusing thing in SEO for you? Share with us in comments.<\/p>\n","protected":false},"excerpt":{"rendered":"

            Content is for humans. But humans find content by using search engines. For each query, Google retrieves the most relevant pages from its databases. As a professional SEO copywriter, you do believe that your webpage is the best one out of all indexed pages. However, Google\u2019s bots might not share your opinion. To avoid misunderstanding […]<\/p>\n","protected":false},"author":26,"featured_media":2863,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":"","footnotes":""},"categories":[28],"tags":[],"class_list":["post-2856","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-keyword-research","entry"],"acf":[],"yoast_head":"\n3 Major Reasons for Copywriters to Relax<\/title>\n<meta name=\"description\" content=\"Content is for humans. But humans find content by using search engines. Discover 3 reasons for copywriters to relax keyword density TF-IDF & semantic search.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"3 Major Reasons for Copywriters to Relax\" \/>\n<meta property=\"og:description\" content=\"Content is for humans. But humans find content by using search engines. Discover 3 reasons for copywriters to relax keyword density TF-IDF & semantic search.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/\" \/>\n<meta property=\"og:site_name\" content=\"RankWatch Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/RankWatch\/\" \/>\n<meta property=\"article:published_time\" content=\"2015-10-07T12:30:20+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-01-15T07:15:43+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png\" \/>\n\t<meta property=\"og:image:width\" content=\"512\" \/>\n\t<meta property=\"og:image:height\" content=\"512\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Elena Dryamina\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@https:\/\/twitter.com\/Elena_Dryamina\" \/>\n<meta name=\"twitter:site\" content=\"@rankwatch\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Elena Dryamina\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"10 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/\"},\"author\":{\"name\":\"Elena Dryamina\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#\/schema\/person\/d9e0f92a1cebf8ecc408c72c7ae63998\"},\"headline\":\"3 reasons for copywriters to relax: keyword density, TF-IDF, and semantic search\",\"datePublished\":\"2015-10-07T12:30:20+00:00\",\"dateModified\":\"2024-01-15T07:15:43+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/\"},\"wordCount\":1657,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1\",\"articleSection\":[\"Keyword Research\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/\",\"url\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/\",\"name\":\"3 Major Reasons for Copywriters to Relax\",\"isPartOf\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1\",\"datePublished\":\"2015-10-07T12:30:20+00:00\",\"dateModified\":\"2024-01-15T07:15:43+00:00\",\"description\":\"Content is for humans. But humans find content by using search engines. Discover 3 reasons for copywriters to relax keyword density TF-IDF & semantic search.\",\"breadcrumb\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#primaryimage\",\"url\":\"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1\",\"contentUrl\":\"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1\",\"width\":512,\"height\":512,\"caption\":\"copy-writers\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.rankwatch.com\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"3 reasons for copywriters to relax: keyword density, TF-IDF, and semantic search\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#website\",\"url\":\"https:\/\/www.rankwatch.com\/blog\/\",\"name\":\"RankWatch Blog\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.rankwatch.com\/blog\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#organization\",\"name\":\"Rankwatch\",\"url\":\"https:\/\/www.rankwatch.com\/blog\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2021\/07\/400x90rec.png?fit=400%2C90&ssl=1\",\"contentUrl\":\"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2021\/07\/400x90rec.png?fit=400%2C90&ssl=1\",\"width\":400,\"height\":90,\"caption\":\"Rankwatch\"},\"image\":{\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/RankWatch\/\",\"https:\/\/x.com\/rankwatch\",\"https:\/\/www.instagram.com\/rankwatch_seo\/\",\"https:\/\/in.linkedin.com\/company\/rankwatch\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#\/schema\/person\/d9e0f92a1cebf8ecc408c72c7ae63998\",\"name\":\"Elena Dryamina\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.rankwatch.com\/blog\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/8e6834f74845937d296edde2d4248def?s=96&d=blank&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/8e6834f74845937d296edde2d4248def?s=96&d=blank&r=g\",\"caption\":\"Elena Dryamina\"},\"description\":\"Elena Dryamina . is strongly experienced in content production, starting from defining buyer personas to localization and post-production activities. Her expertise also includes technical, marketing, SEO and UI copywriting as well as localization and web project management, translation and sales.\",\"sameAs\":[\"http:\/\/elenawriting.com\/\",\"https:\/\/www.linkedin.com\/pub\/elena-dryamina\/6b\/a25\/a87\",\"https:\/\/www.pinterest.com\/edryamina\/\",\"https:\/\/x.com\/https:\/\/twitter.com\/Elena_Dryamina\"],\"url\":\"https:\/\/www.rankwatch.com\/blog\/author\/elenadryamina\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"3 Major Reasons for Copywriters to Relax","description":"Content is for humans. But humans find content by using search engines. Discover 3 reasons for copywriters to relax keyword density TF-IDF & semantic search.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/","og_locale":"en_US","og_type":"article","og_title":"3 Major Reasons for Copywriters to Relax","og_description":"Content is for humans. But humans find content by using search engines. Discover 3 reasons for copywriters to relax keyword density TF-IDF & semantic search.","og_url":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/","og_site_name":"RankWatch Blog","article_publisher":"https:\/\/www.facebook.com\/RankWatch\/","article_published_time":"2015-10-07T12:30:20+00:00","article_modified_time":"2024-01-15T07:15:43+00:00","og_image":[{"width":512,"height":512,"url":"https:\/\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png","type":"image\/png"}],"author":"Elena Dryamina","twitter_card":"summary_large_image","twitter_creator":"@https:\/\/twitter.com\/Elena_Dryamina","twitter_site":"@rankwatch","twitter_misc":{"Written by":"Elena Dryamina","Est. reading time":"10 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#article","isPartOf":{"@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/"},"author":{"name":"Elena Dryamina","@id":"https:\/\/www.rankwatch.com\/blog\/#\/schema\/person\/d9e0f92a1cebf8ecc408c72c7ae63998"},"headline":"3 reasons for copywriters to relax: keyword density, TF-IDF, and semantic search","datePublished":"2015-10-07T12:30:20+00:00","dateModified":"2024-01-15T07:15:43+00:00","mainEntityOfPage":{"@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/"},"wordCount":1657,"commentCount":0,"publisher":{"@id":"https:\/\/www.rankwatch.com\/blog\/#organization"},"image":{"@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#primaryimage"},"thumbnailUrl":"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1","articleSection":["Keyword Research"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/","url":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/","name":"3 Major Reasons for Copywriters to Relax","isPartOf":{"@id":"https:\/\/www.rankwatch.com\/blog\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#primaryimage"},"image":{"@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#primaryimage"},"thumbnailUrl":"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1","datePublished":"2015-10-07T12:30:20+00:00","dateModified":"2024-01-15T07:15:43+00:00","description":"Content is for humans. But humans find content by using search engines. Discover 3 reasons for copywriters to relax keyword density TF-IDF & semantic search.","breadcrumb":{"@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#primaryimage","url":"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1","contentUrl":"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1","width":512,"height":512,"caption":"copy-writers"},{"@type":"BreadcrumbList","@id":"https:\/\/www.rankwatch.com\/blog\/3-reasons-for-copywriters-to-relax-keyword-density-tf-idf-and-semantic-search\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.rankwatch.com\/blog\/"},{"@type":"ListItem","position":2,"name":"3 reasons for copywriters to relax: keyword density, TF-IDF, and semantic search"}]},{"@type":"WebSite","@id":"https:\/\/www.rankwatch.com\/blog\/#website","url":"https:\/\/www.rankwatch.com\/blog\/","name":"RankWatch Blog","description":"","publisher":{"@id":"https:\/\/www.rankwatch.com\/blog\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.rankwatch.com\/blog\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.rankwatch.com\/blog\/#organization","name":"Rankwatch","url":"https:\/\/www.rankwatch.com\/blog\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.rankwatch.com\/blog\/#\/schema\/logo\/image\/","url":"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2021\/07\/400x90rec.png?fit=400%2C90&ssl=1","contentUrl":"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2021\/07\/400x90rec.png?fit=400%2C90&ssl=1","width":400,"height":90,"caption":"Rankwatch"},"image":{"@id":"https:\/\/www.rankwatch.com\/blog\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/RankWatch\/","https:\/\/x.com\/rankwatch","https:\/\/www.instagram.com\/rankwatch_seo\/","https:\/\/in.linkedin.com\/company\/rankwatch"]},{"@type":"Person","@id":"https:\/\/www.rankwatch.com\/blog\/#\/schema\/person\/d9e0f92a1cebf8ecc408c72c7ae63998","name":"Elena Dryamina","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.rankwatch.com\/blog\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/8e6834f74845937d296edde2d4248def?s=96&d=blank&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/8e6834f74845937d296edde2d4248def?s=96&d=blank&r=g","caption":"Elena Dryamina"},"description":"Elena Dryamina . is strongly experienced in content production, starting from defining buyer personas to localization and post-production activities. Her expertise also includes technical, marketing, SEO and UI copywriting as well as localization and web project management, translation and sales.","sameAs":["http:\/\/elenawriting.com\/","https:\/\/www.linkedin.com\/pub\/elena-dryamina\/6b\/a25\/a87","https:\/\/www.pinterest.com\/edryamina\/","https:\/\/x.com\/https:\/\/twitter.com\/Elena_Dryamina"],"url":"https:\/\/www.rankwatch.com\/blog\/author\/elenadryamina\/"}]}},"jetpack_featured_media_url":"https:\/\/i0.wp.com\/www.rankwatch.com\/blog\/wp-content\/uploads\/2015\/10\/copy-512.png?fit=512%2C512&ssl=1","amp_enabled":true,"_links":{"self":[{"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/posts\/2856","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/users\/26"}],"replies":[{"embeddable":true,"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/comments?post=2856"}],"version-history":[{"count":15,"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/posts\/2856\/revisions"}],"predecessor-version":[{"id":22364,"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/posts\/2856\/revisions\/22364"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/media\/2863"}],"wp:attachment":[{"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/media?parent=2856"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/categories?post=2856"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.rankwatch.com\/blog\/wp-json\/wp\/v2\/tags?post=2856"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}