In website operation and search engine optimization (SEO), keyword density is a common but often misunderstood concept.It refers to the ratio of the number of times a keyword appears in the web content to the total number of words, usually expressed as a percentage.Although today's search engine algorithms are more complex, it is no longer the era where simply stacking keywords can achieve good rankings, but moderately paying attention to keyword density can help us ensure that the content theme is clear and convey the core information of the page to the search engine.countFilter, performing a preliminary analysis of the keyword density on the template level.
Understanding core tools:countFilters andwordcountFilter
AnQiCMS template engine supports a variety of filters, includingcountThe filter is the key to counting the frequency of keywords. According to the document,countThe filter can "calculate the number of times a keyword appears in a line of string or array". This means we can use it to count the frequency of specific words in titles, descriptions, or the body of text.
In addition, to calculate the density, we also need to know the total number of words on the page. This is where another important filter is needed—wordcount.wordcountThe filter can accurately count the number of words in a string, which provides the denominator data for us to calculate the keyword density.
Suppose we want to count the number of occurrences of the keyword "AnQiCMS" in the article title and get the word count of the article content, as shown in the following example:
{% set keyword = "AnQiCMS" %}
{% set title_occurrences = archive.Title|count:keyword %}
<p>关键词 "{{ keyword }}" 在标题中出现 {{ title_occurrences }} 次。</p>
{% set content_word_count = archive.Content|striptags|wordcount %}
<p>文章内容总词数（纯文本）：{{ content_word_count }}。</p>
It is worth noting that when counting the number of words in the content of an article, we usually want to exclude the interference of HTML tags and only count the vocabulary of pure text. Therefore, we first usestriptagsThe filter removes HTML tags and then useswordcountfor counting. This avoids the text within HTML tags from being incorrectly counted in the total word count, thereby improving the accuracy of density analysis.
Build keyword density analysis logic
Now, we will combine these tools to build a complete keyword density analysis logic. Usually, we will be in the article detail page (such asdetail.htmlorarchiveDetail.html）The template is used for this type of analysis.
First, we need to define the keywords to be analyzed.To enhance the flexibility of the analysis, we can store this keyword in a variable.Then, we calculate the number of times the keyword appears in the main content area of the page (such as the title, description, and text), and calculate the total number of words in these areas.
Let us take the density of the single keyword “AnQiCMS” in the article title and content as an example:
{# 定义要分析的关键词 #}
{% set target_keyword = "AnQiCMS" %}
{# 获取文章标题、描述和纯文本内容 #}
{% set page_title = archive.Title %}
{% set page_description = archive.Description %}
{% set page_content = archive.Content|striptags %} {# 先去除HTML标签 #}
{# 统计关键词在不同区域的出现次数 #}
{% set keyword_in_title = page_title|count:target_keyword %}
{% set keyword_in_description = page_description|count:target_keyword %}
{% set keyword_in_content = page_content|count:target_keyword %}
{# 计算关键词总出现次数 #}
{% set total_keyword_occurrences = keyword_in_title + keyword_in_description + keyword_in_content %}
{# 统计所有分析区域的总词数 #}
{% set total_words = page_title|wordcount + page_description|wordcount + page_content|wordcount %}
{# 计算关键词密度，并进行除零判断，避免报错 #}
{% if total_words > 0 %}
{% set keyword_density = (total_keyword_occurrences / total_words) * 100 %}
<p>关键词 "{{ target_keyword }}" 在页面中的密度约为：{{ keyword_density|stringformat:"%.2f" }}%</p>
{% else %}
<p>页面内容过少，无法计算关键词密度。</p>
{% endif %}
In the above code, we use{% set %}Labels define multiple variables to store intermediate results, making the logic clearer.We include the title, description, and main content in the scope of statistics, as these are important bases for search engines to judge the theme of the page.|stringformat:"%.2f"The filter is used to format the calculated floating-point number as a percentage with two decimal places, enhancing readability.In this way, you can intuitively see the density of each keyword on the article detail page.
If you need to analyze multiple keywords, you can store multiple target keywords in an array and then useforLoop through this array and calculate and display the density of each keyword one by one.
Practical application and precautions
This keyword density analysis method based on AnQiCMS template provides a convenient real-time feedback mechanism, helping you to initially evaluate the focus of the page content on the core keywords after the content is published.However, it is important to note that this is only a basic analysis method.
- Consider the quality of content comprehensively:The role of keyword density is to assist in content creation, not to dominate the content.Always prioritize creating content that is valuable to users, natural and smooth, avoid keyword stacking to prevent affecting user experience and even triggering search engine penalty mechanisms.
- Dynamically adjust the analysis scope:You can adjust the page area included in the density analysis according to your actual needs, for example, only analyzing the main content, or combining with the keywords field in the page metadata (
archive.KeywordsPerform a more in-depth aggregate analysis. - Not the only indicator:Modern SEO is a multi-dimensional and comprehensive process.Keyword density is just one of the reference indicators, and it also needs to be combined with factors such as the user experience of the page, authority, and external link quality to optimize comprehensively.
By integrating keyword density analysis into the AnQiCMS template, you can conveniently perform an initial SEO self-check on the content, thereby better adjusting your content strategy to achieve better search performance.