So what’s with Google auto-completing actress names with “feet”?

Phil Pearson
5 min readSep 23, 2014

A few months — perhaps a year — ago, I started noticing something strange. Whenever I was searching for an actress’ name in Google, the suggested autocompletes would often include “imdb” and “films” as expected, but also sometimes “feet”. If I typed in Rachel Weisz, Google would suggest “Rachel Weisz feet”. Helena Bonham Carter? “Helena Bonham Carter feet”.

A quick word on Google’s autocomplete algorithm, before we move on… Google’s autocompletes are a “crowdsourced” service. That is, Google’s suggestions for how to complete your search are based upon their humongous database of other Google users’ real searches. So if you started typing “Hugh Grant” and Google suggests “Hugh Grant whores” as your search, that’s not an editorial decision on Google’s part. It just so happens that lots of people are interested in whether or not Hugh Grant used the services of certain Los Angeles prostitutes, and Google’s guessing that you may be one of them (statistically speaking, you probably are).

Most of the time, autocomplete is pretty helpful. I know that if I’m looking for a restaurant near my house, it’s helpful to be able to type “good restaurants kensa”, with one eye on the autocomplete suggestions, and just hit the “down” and “return” keys, when I have visual confirmation that Google knows I want to complete my search using “l rise”. (typing up to “kens” still assumes Kensington, but “kensa” switches the assumption to Kensal Rise. Clever, right?) However, occasionally, I see results that are weird, and sometimes offensive. My observation falls into the former camp. But basically, autocomplete is a democracy. The search box is the ballot box, and your search is your vote.

So let’s come back to “feet”. At first, I thought that I’d stumbled on an actress with niche appeal. Perhaps somewhere on the internet (4chan?) there’s a foot fetishist discussion group who have taken a vote, and they’ve decided that Rachel Weisz, in particular, has the best feet in showbiz. But then, as I searched more and more actresses, I found that it was happening for a surprisingly large proportion of them I was Googling. How many specifically? I decided to find out and got a list of 258 actresses to trial this on. My findings?

A whopping 28% of actresses are autocompleted with “feet”.

How does that autocomplete suggestion compare to other terms? Below is a list of the most common terms (some grouped):

IMDB: 52%
Social media (grouped Twitter/Instagram/Tumblr/Facebook): 49%
Twitter: 42%
Feet: 28%
Movies: 25%
Family members (grouped boyfriend/husband/children): 23%
Hot: 19%
Instagram: 18%
2013/2014: 9%
Tumblr: 7%
Facebook: 2%

So it could be said that actresses’ feet are only a little less interesting to Google users than actresses’ social media, and a little more interesting than actresses’ family members.

To take analysis a step further: how about the distribution of the autocorrect terms by the age of the actress?

Keyword: IMDb, whether keyword included in autocomplete results, grouped by age

A term such as “IMDb” shows relatively uniform representation across all actress age groups. A majority of actresses (52%) are accompanied with “IMDb” as a suggestion, and grouped by age group, the results show little deviation by age, with a moderate bulge around the peak commercial age range of 31 — 45.

Keyword: Movie/movies, whether keyword included in autocomplete results, grouped by age

An interesting contrast is the term “movies”. These increase as actress age increases. One potential explanation is a possible perception that if an actress is older, then they may be less likely to be covered on a database such as IMDb.

Certain other terms show a skew towards the youth, such as social media:

Keyword: Social media (grouped Twitter/Instagram/Tumblr/Facebook), whether keyword included in autocomplete results, grouped by age
Keyword: Instagram, whether keyword included in autocomplete results, grouped by age

Within all half-decade groupings between the ages of 16 and 40, the majority of these actresses prompted social media-related suggestions. Of actresses between 16 and 20, all searches had social media-related suggestions.

For Instagram specifically, the oldest individual actress that is accompanied by a suggestion is 50 (Ming-Na Wen). There is a notable skew to the younger actresses, even compared to social as a whole.

Keyword: Twitter, whether keyword included in autocomplete results, grouped by age

Coming to Twitter, the oldest is Faye Dunaway (73) (Glenda Jackson (78) shares a name with a British politician who appears the more likely match for Twitter searches for the name). Actresses up to the age of around 55 are well-searched in reference to their Twitter handle.

And “feet”?

Keyword: Feet, whether keyword included in autocomplete results, grouped by age

The core demographic for the “feet” autocomplete suggestion is the range 31 to 45, with a particular peak at the early 40s age group. Among that age group, a majority of actress names were autocompleted with “feet”.

Trends: while actresses are young, people are interested in their Tumblrs & Instagrams. As they grow in career and age towards early adulthood, people show more interest in their Twitter presences and check out their filmographies on IMDb. As they hit their early to mid 40s, interest in their feet peaks. Conclusion: the internet is weird.

A note on methodology: The default AOSP browser, rather than Google Chrome, on a recently-wiped Android phone was used. I was not signed in to Google on the phone, and privacy mode was turned on. All of this to assure the reader that any potential predilection on my part for actress’ podiatric parts should not have figured into Google’s autocorrect suggestions. Sample size: 258 actresses. Top 5 autocomplete suggestions noted for each. None were clicked on, to avoid giving Google any signals about the types of results I was looking for.

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Phil Pearson

Tech, Digital, Media, Advertising, Games, Culture, Asia, China, Japan, Podcasts | Global Account Supervisor @ Dentsu Isobar | Tokyo