Text Similarity Checker guide
Compare the vocabulary overlap of two passages with a transparent cosine-similarity score and shared-term list.
What this tool does
The Text Similarity Checker converts each passage into a word-frequency vector and calculates cosine similarity between those vectors. The result ranges from zero to 100 percent. A higher value means the passages use analyzed terms in more similar proportions, while a lower value means their word-frequency patterns differ.
By default, common English function words are removed so terms such as “the,” “and,” and “with” do not dominate a short comparison. You can include them when exact surface wording matters. The tool also displays up to twelve shared terms, ranked by their combined frequency contribution.
This is lexical comparison, not semantic understanding or plagiarism detection. Two passages can express the same idea with different vocabulary and receive a low score. They can also repeat the same terms while making opposite claims. The result does not determine authorship, originality, truth, citation quality, or permission to reuse material.
How to use it
- Paste one passage into each text area.
- Decide whether to ignore common English function words.
- Select Compare texts.
- Review the percentage, overlap description, analyzed-term counts, and shared terms.
- Read both original passages before drawing a conclusion.
For meaningful comparisons, use passages with similar scope. Comparing one sentence against an entire article makes the vector lengths and term distribution difficult to interpret. Break long documents into corresponding sections when you want to see where wording overlaps.
Benefits
- Produces a repeatable cosine-similarity percentage
- Shows prominent shared words behind the score
- Offers optional English common-word filtering
- Explains what the calculation can and cannot establish
- Keeps both passages on the current device
Interpreting the score
ToolSeta labels 75 percent or more as high lexical overlap, 40 to 74.9 as moderate, and lower values as low. These bands are interface descriptions, not research thresholds. Appropriate cutoffs depend on text length, domain, preprocessing, and the decision being considered.
Use the result to compare drafts, identify repeated product vocabulary, inspect localization changes, or explore whether two descriptions share terminology. Do not use it alone to accuse someone of plagiarism, automatically reject writing, moderate a person, or make academic and employment decisions.
Practical notice: This output is a limited vocabulary metric, not a finding about authorship, intent, plagiarism, or legal rights. Important reviews require the full text and appropriate human judgment.