Text Analysis is the process of using computer technology to statistically analyze, classify, extract, and interpret text data. It is widely used in content creation, search engine optimization (SEO), data mining, and natural language processing (NLP). Through text analysis, we can quickly understand the structural characteristics, linguistic features, and content focus of an article.
• Total Characters: The total count of all characters, the most basic text length metric
• Chinese Characters: Count of Chinese characters, a core metric for Chinese content creation
• Word Count: Total number of words after segmentation by spaces or punctuation, an important indicator of text scale
• Paragraph Count: Number of paragraphs separated by blank lines, reflecting the article's structural hierarchy
• Reading Time: Estimated time needed based on average reading speed, helping readers plan their reading schedule
• Keyword Density: The proportion of keywords in the text, one of the core metrics in SEO optimization
This online text analyzer is simple to use with comprehensive functionality. Here is the detailed guide:
Input Text: Paste or type the text you want to analyze in the input box. The tool supports mixed Chinese and English text and automatically recognizes and categorizes various character types. After entering, click the "Analyze" button, and the tool will immediately perform a comprehensive analysis.
View Statistics: After analysis, the results are displayed as cards including total characters, Chinese characters, English characters, word count, line count, paragraph count, sentence count, and estimated reading time. These metrics help you quickly understand the overall scale and structural characteristics of the text.
Word Frequency Analysis: In the "Word Frequency" section, the tool extracts high-frequency words from the text (after removing common stop words) and displays the top 20 words sorted by occurrence count. This is very helpful for understanding the core topic and optimizing keyword layout.
Sample Text: Click the "Sample" button to quickly load sample text for a demo. Click "Clear" to remove the current content. All operations run locally with no data uploaded to servers.
The online text analyzer has wide applications in multiple fields. Here are several typical use cases:
Content Creation & Formatting: Real-time understanding of article word count and structure to ensure compliance with platform requirements. For example, WeChat articles are recommended at 800-1500 words, while Zhihu answers are suggested above 2000 words. The text analyzer helps quickly confirm whether the article length meets requirements and whether paragraph distribution is reasonable.
SEO Optimization: Through keyword density analysis, check whether target keywords are evenly distributed throughout the article. Keyword density is recommended between 2%-8%; too high may be judged as keyword stuffing by search engines, while too low is unfavorable for ranking. The text analyzer helps you precisely control keyword density to improve search engine friendliness.
Translation Workload Estimation: Translation project quotes are usually calculated by word count. The text analyzer can quickly obtain the character count and word count of the source text, providing a basis for translation quotes. Chinese character count statistics help determine translation difficulty and required time, improving work efficiency.
Natural Language Processing (NLP): Text analysis is the foundation of natural language processing. Modern NLP technology can perform advanced analysis such as sentiment analysis, topic modeling, and named entity recognition. However, basic text statistical analysis remains the first step in understanding text and lays the groundwork for subsequent deep analysis. This tool provides the most basic text statistics, suitable for quickly understanding text overview.
TF-IDF Algorithm: Term Frequency-Inverse Document Frequency is a commonly used weighting technique in information retrieval and data mining. It measures a word's importance to a document by counting how often it appears in the document and how rare it is across the entire corpus. Although this tool only provides simple word frequency statistics, understanding TF-IDF helps analyze text content more deeply.
Scientific Basis for Reading Speed: Adult Chinese reading speed is approximately 400-500 characters per minute, while English reading speed is about 200-300 words per minute. However, reading speed is affected by multiple factors including text difficulty, font size, line spacing, and reading purpose. Academic literature reading speed is usually lower than novels, and technical documentation may be even slower. This tool uses a medium speed estimate for reference only.
It supports total characters, Chinese characters, English characters, digits, punctuation marks, and spaces. It also calculates word count, line count, paragraph count, sentence count, and estimated reading time.
The tool extracts all words from the text, removes common stop words (e.g., the, and, is, of), counts the frequency of each word, and displays the top 20 most frequent words sorted by occurrence count.
Reading time is based on average adult reading speed: approximately 400-500 characters per minute for Chinese and 200-300 words per minute for English. The tool calculates separately for Chinese and English content and uses the average as the final estimate.
Keyword density refers to the percentage of times a keyword appears relative to the total word count in a text. In SEO optimization, a keyword density between 2% and 8% is generally recommended. Higher density may be seen as keyword stuffing by search engines.
No. This tool runs entirely in your browser. All text analysis and statistics are computed locally on your device. No data is ever uploaded to any server, ensuring complete privacy.