<b>Why anchor entropy may describe natural profiles better than ratios</b>

<b>Why anchor entropy may describe natural profiles better than ratios</b>

Practitioners almost always model anchor health as a set of bucket percentages: branded, exact, partial, naked URL, generic. Useful, but it discards information. Two profiles can share identical bucket ratios while one looks organic and the other looks templated.

A more rigorous frame borrows from information theory. Treat each distinct anchor string as a token and compute the Shannon entropy of the distribution. Organic profiles tend toward high entropy — hundreds of near-unique phrasings, long-tail variation, sentence fragments people actually typed. Manufactured profiles collapse toward low entropy: the same six or seven optimized strings repeating.

— Ratio analysis asks 'what share is commercial?'
— Entropy analysis asks 'how mechanically repetitive is the phrasing?'

Google's own link-spam patents repeatedly describe detecting 'templated' or 'duplicated' anchor patterns, which maps far more closely to low entropy than to any single ratio threshold.

Limitation: entropy is sensitive to sample size — a 40-link profile will look artificially low-entropy versus a 4,000-link one, so cross-domain comparison requires normalization, and I have not seen a published, validated normalization for this.

On one hand entropy captures the 'naturalness' intuition; on the other it is trivially gameable by spinning anchor text, which would inflate entropy without changing intent.

Open question: would an entropy floor catch link networks that pass a ratio audit precisely because they were tuned to the ratio?