A video montage of 640 selfie images from London. The individual images are identically aligned with respect to eye position and sorted by the head tilt angle. The blending animation is designed to create abstractions of the individual images, but still maintains a degree of fidelity with respect to image details and context.

selfiecity London

Investigating the style of self-portraits (selfies) in six cities across the world using a mix of theoretical, artistic and quantitative methods.

This is a special edition of the original selfiecity project for the Big Bang Data exhibition, Somerset House, London.

We collected and analyzed 152,462 Instagram images from central London for the week of September 21–27, 2015 and compared the results to our findings from five other cities. Experiment with the new data in the selfiexploratory, and scroll down for an overview of the London findings.


First, here is what we found about how London selfies compare to other cities in terms of demographics, using a mixture of automatic methods and human judgments:

  • The estimated average age of male selfies in London (28.0 years) is higher than the average for the other cities (26.3 years).
  • The estimated average age of female selfies in London is very similar to other cities (23.7 years vs. 23.6 years).
  • In London we found 62.8% female selfies (versus 37.2% male selfies). To compare, here are the proportions of female selfies in other cities we found: 55.2% in Bangkok, 59.4% in Berlin, 61.6% in New York, 65.4% in Sao Paolo, 82.0% in Moscow. London female to male selfies ratio is the second highest after Moscow.

How would you like your selfie?

Using automatic face recognition software, we also learned that compared to New York, Moscow, Berlin, Bangkok, and São Paulo, London selfies have:

  • The most straight poses - 15° average head turn angle, as opposed to 20° average for other cities.
  • Smallest proportion of faces showing happy emotions – London’s average is 0.55 vs. 0.62 for other cities. (Face analysis software estimates happiness emotion on 0-1 scale, 0 = least happy; 1 most happy.)
  • The highest number of glasses (29% vs. 18% in other cities) and also the highest number of eyes closed (28% vs. 20% in other cities).

the selfiexploratory

Experiment with all the data we collected.

Do angry people tilt their heads more strongly? And what are the typical moods of selfie takers in London? Find out!

→ Launch

Data collection and analysis

This project is based on a unique dataset we compiled by analysing tens of thousands of images from each city both through automatic image analysis and human judgements.

How we collected and filtered the data

To locate selfies photos, we randomly selected 140,000 photos (20,000-30,000 photos per city) from a total of 808,000 images we collected on Instagram. 2-4 Amazon’s Mechanical Turk workers tagged each photo. For these, we asked Mechanical Turk workers the simple question "Does this photo shows a single selfie"?

We then selected top 1000 photos for each city (i.e., photos which at least 2 workers tagged as a single person selfie).

We submitted these photos to Mechanical Turk again, asking three "master workers" (i.e. more skilled workers) not only to verify that a photo shows a single selfie, but also to guess the age and gender of the person.

On the resulting set of selfie images, we ran automatic face analysis, supplying us with algorithmic estimations of eye, nose and mouth positions, the degrees of different emotional expressions, etc.

As the final step, one or two members of the project team examined all these photos manually. While most photos were tagged correctly, we found some mistakes. We wanted to keep the data size the same (to make visualizations comparable), so our final set contains 640 selfie photos for every city.


How many photos contain faces, anyway?

We manually categorized a set of 2000 images in four genres: single selfies, selfies showing two or more faces, single portraits, and portraits with two or more people. Here is what we found:

  • Only 1/4 (25.6%) of photos shared in central London are portraits or selfies.
  • Among these images, there are almost four times more portraits (20%) than selfies (5.6%).
  • The proportions of selfies showing one person and selfies showing two or more people are the same - 2.8% each.
  • The proportions of portraits with one person and with two people or groups are the same - 10% each.

Where do people take photos with faces?

Besides the manual tagging described above, we also used the openCV software library to automatically detect faces in all 152,462 images we collected from central London. This allowed us, for instance, to visualize the average number of faces per location.

The resulting map reveals a very interesting pattern: locations with fewer photos have much higher proportions of faces in these photos. Perhaps people are looking for smaller, more private spots for their portrait or seflie photos or simply prefer to take these photos in interesting and unique spaces with no tourists around.

A city of photos

In addition to Instagram, we also used a sample of images shared in London on Twitter. This data came from the unique dataset of 265 million geolocated tweets with images for 2011-2014 provided to our lab by Twitter as part of their 2014 Twitter Data Grants. The map below shows locations of 3,691,003 tweets with images in London (shared between November 2012 and July 2014) from our dataset.

See it live

This project is on display at the Big Bang Data exhibition, Somerset House, London, 03 Dec 2015 — 28 Feb 2016. The exhibit features a portrait mode adaptation of the selfiexploratory as well as a large rear projection of the selfiecity London video montage and large prints of some of the graphics seen on this site.


Dr. Lev Manovich

Project coordinator /
theory and analysis

Expert on digital art and culture; Professor of Computer Science, The Graduate Center, CUNY; Director, Software Studies Initiative.


Moritz Stefaner

Creative direction /
data visualization

Independent consultant in information visualization / Truth and Beauty Operator. M.A. in Interface Design, B.Sc. in Cognitive Science.


Mehrdad Yazdani

Data analysis

Researcher Scientist, Software Studies Initiative; Ph.D. in Computational Neuroscience, UCSD.


Dr. Dominikus Baur

Data visualization and UI

Data visualization and mobile interaction designer, Ph.D. in Media Informatics from the University of Munich.


Daniel Goddemeyer

Concept Development

Freelance Consultant; exploring the cultural impacts of ubiquitous access to information to create new products and services. M.A. Royal College of Art.


Alise Tifentale

Theory and analysis

Art historian and curator; co-curated the Latvian Pavilion at the 55th Venice Biennale in 2013; Ph.D. student, The Graduate Center, City University of New York.


Nadav Hochman

Theory and analysis

Visual social media researcher, PhD student, University of Pittsburgh. Project director, phototrails.net


Jay Chow

Data collection and management

Researcher, Software Studies Initiative; Web and Mobile Developer at Motive Interactive.


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Supported by


The development of selfiecity was supported by The Graduate Center, City University of New York, California Institute for Telecommunication and Information, and The Andrew W. Mellon Foundation.

Augmented-data.comperformed face detection in Instagram images from London.

And big thanks to gnip for the support with the data collection!

Read more

 Download press material
selfiecity.net main page


Selfies taken in London are some of the saddest in the world
The Times
It’s another miserable day in capital of grim selfies
The Telegraph
Big Bang Data, Somerset House, review: 'alarming'
The Guardian
London selfies glummer, less tilted and more bespectacled, study finds
Selfies Taken in London Are the Most Miserable Selfies in the World
The Memo
Londoners look most gloomy & bespectacled, selfie data shows
It's nice that
London selfies are “most miserable” in the world, study shows
Yahoo UK
Can You Guess Which City Takes The Most Miserable Selfies?
Lifehacker UK
Study Finds Londoners Take the Most Miserable Selfies