N-gram Analyzer - Extract & Analyze Patterns
Extract unigrams, bigrams, trigrams and custom n-grams from any text. Get real frequency counts, density scores, and SEO keyword insights instantly.
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0 words • 0 charsTop 10 Frequency Chart
| # | N-gram | Frequency | Density | Length |
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Text Insights
What is N-gram Analysis?
Explore the foundational concepts of contiguous sequence modeling and linguistic extraction.
Unigram (1-gram)
Analysis of single word units to determine individual keyword frequency and core topical density.
Bigram (2-gram)
Evaluation of two-word sequences to identify common phrases and potential long-tail seeds.
Trigram (3-gram)
Extraction of three-word sequences that offer deep contextual meaning and specific topic clusters.
NLP Tokenization
The algorithmic process of breaking text into manageable tokens for advanced pattern recognition.
Stop-word Logic
Identifying and removing common noise words (the, a, is) to highlight significant semantic patterns.
Statistical Freq
Measuring the raw mathematical occurrence of sequences to find the most dominant concepts.
Density Metrics
Calculating the percentage of a sequence's occurrence relative to the total document volume.
Linguistic Maps
Visualizing recurrent structures that define the professional tone and topic of your copy.
Why Extract N-grams?
Surface hidden keyword opportunities and ensure your content aligns with modern search algorithms.
Intent Discovery
Uncover high-intent multi-word phrases that single keyword analysis often overlooks.
Avoid Over-use
Detect phrase-level over-optimization that might trigger spam filters in search engine bots.
BERT Optimization
Improve your content's "Natural Language" score to better align with transformer-based search models.
Competitor Audits
Break down top-ranking competitor pages to see exactly which phrases they are prioritizing.
Style Consistency
Identify repetitive crutch phrases that lower the quality and readability of your writing.
Topical Depth
Ensure you are covering all semantically related phrase variations to build absolute authority.
Ranking Relevance
Inject naturally occurring high-weight sequences to improve the relevancy score of your page.
AI Refinement
Identify and remove common "AI-sounding" repetitive patterns to make generated text feel more human.
How to Analyze Your Text
Follow this strategic workflow to turn n-gram data into actionable content optimizations.
Paste Content
Start by inserting your full article, including headings, to see your true linguistic distribution.
Set Thresholds
Filter for sequences occurring 2+ times to ignore random noise and focus on deliberate patterns.
Gap Identification
Compare your result trigrams with Google Search snippets to find phrases your competitors use.
Anchor Polish
Use unigram data to ensure your internal link anchor text isn't becoming overly repetitive.
Subhead Tuning
Extract top trigrams from search results to create more semantically relevant subheaders (H2s).
Export Reports
Download CSV lists to provide your writing team with approved n-gram keyword targets.
Visual Audit
Review the frequency charts to see the "weight" of concepts across your content distribution.
Iterative Review
Analyze your content after every major draft to keep your phrase health within optimal SEO limits.