Text Entropy Calculator Online Free — Shannon Entropy
Calculate Shannon entropy to measure information randomness.
Shannon entropy H = −Σ p(x) log₂ p(x) bits per character. Max entropy for standard text is ~6.57 bits. Repetitive text (like "aaaaaa") has entropy near 0.
What is Text Entropy Calculator?
Calculates the Shannon entropy of your text — a measure of information randomness. Higher entropy means more unpredictable, information-dense text. Lower entropy means more repetitive, compressible text. Shows both character-level and word-level entropy.
Common Use Cases
Cryptography education, data compression analysis, information theory study, password strength assessment, linguistic research, and NLP preprocessing.
How It Works
For each character (or word), calculates its probability and computes H = −Σ p(x) log₂ p(x). Maximum entropy for ASCII text is ~6.57 bits/character.
Frequently Asked Questions
What is Shannon entropy?
Shannon entropy measures the average information content per character or word. High entropy = high unpredictability = more information. Low entropy = predictable/repetitive text.
What does a high entropy score mean?
High entropy (close to max) means each character is more unpredictable — typical of compressed data or random text. Low entropy means lots of repetition, like "aaaaaa".
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