selfiecity


Investigating the style of self-portraits (selfies) in five cities across the world.


Selfiecity investigates selfies using a mix of theoretic, artistic and quantitative methods:

  • We present our findings about the demographics of people taking selfies, their poses and expressions.
  • Rich media visualizations (imageplots) assemble thousands of photos to reveal interesting patterns.
  • The interactive selfiexploratory allows you to navigate the whole set of 3200 photos.
  • Finally, theoretical essays discuss selfies in the history of photography, the functions of images in social media, and methods and dataset.

Imageplots


Poses


Each city has a different style when it comes to selfies. Compare yourself:


In these grids, we have arranged the photos horizontally by head tilt; the vertical axis shows you if people look up or down.
In addition, we can crop and rotate the photos to center on the faces:


Gender and age profiles per city

Case by case inspection of photos can reveal a lot of detail, but it is difficult to quantify the patterns observed.

"Is it just me, or do Sao Paulo women actually tilt their heads more? Do New Yorkers or Berliners look older?"

In order to answer these questions, and supplement our rudimentary automatic face analysis with human judgment, we had thousands of photos inspected by Mechanical Turk workers, who estimated age and gender of the people on the photos. Here are the results:


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Smile distributions by gender and city

We can also the determine the facial expressions of the selfies in a city — who smiles the most, and who has more reserved looks?


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the selfiexploratory


Experiment with all the data we collected.


Do angry people tilt their heads more strongly? And what is a characteristic mood for people in Moscow? 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 judgement.

How we collected and filtered the data

To locate selfies photos, we randomly selected 120,000 photos (20,000-30,000 photos per city) from a total of 656'000 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.


Our main findings

People take less selfies than often assumed

Depending on the city, only 3-5% of images we analysed were actually selfies.

Significantly more women

In every city we analyzed, there are significantly more women selfies than men selfies (from 1.3 times as many in Bangkok to 1.9 times more in Berlin). Moscow is a strong outlier - here, we have 4.6 times more female than male selfies!


A young people's sport? Indeed.

Most people in our photos are pretty young (23.7 estimated median age). Bangkok is the youngest city (21.0), whereas NYC is the oldest (25.3). Men's average age is higher than that of women in every city. Surprisingly, more older men (30-) post selfies on Instagram than women.

Bangkok, Sao Paulo are all smiles

Our mood analysis revealed that you can find lots of smiling faces in Bangkok (0.68 average smile score) and Sao Paulo (0.64). People taking selfies in Moscow smile the least (only 0.53 on the smile score scale).


Women strike more extreme poses, especially in Sao Paulo

Women's selfies show more expressive poses; for instance, the average amount of head tilt is 50% higher than for men: (12.3° vs. 8.2°). Sao Paulo is most extreme - there, the average head tilt for females is 16.9°!


Theory and reflection


How can history of photography help to better understand selfies phenomena? How can we approach theoretically social media images in general?

The Selfie: Making sense of the “Masturbation of Self-Image” and the “Virtual Mini-Me”

Alise Tifentale, The Graduate Center, CUNY

This essay reviews some of the most recent debates on the selfie phenomenon and places it into a broader context of photographic self-portraiture, investigating how the Instagrammed selfie differs from its precursors. The Selfie phenomenon should be viewed in the light of history of photography as a sub-genre of self-portraiture and as a new subject of vernacular photography studies as well as treated as a side product of technological developments that have led to the easy availability of image-making devices and image-sharing platforms.


  Read the essay

Imagined Data Communities

Nadav Hochman, University of Pittsburgh

Writing about media interface presentations and their relation to larger cultural trends is tricky. Different elements are constantly added, changed or removed, new services are frequently developed and released to public use, and new technologies capture the imaginations of many. Within this flux, what can we say about social photography in particular and contemporary image productions in general, that is not confined to the characteristics of one platform or another? Can we identify overarching processes that cross platforms and are destined to change the way we interact with images?


   Read the essay

Beyond Biometrics: Feminist Media Theory Looks at Selfiecity

Elizabeth Losh, University of California, San Diego

As large-scale media visualizations from the Selfiecity database of images shot in five cities on four continents indicate, the selfie has become a truly transnational genre that is as much about placemaking as it is about the narrowcasting of particular faces and bodies. At the same time, the scholarly literature around this specific form of self-representation through closely distant mobile photography has struggled to keep up with theorizing emergent new media practices that utilize lenses, screens, mirrors, and armatures in novel ways and generate compositions with distinctive framing and posing that mark belonging to selfie taxonomies.


   Read the essay

Team


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.

softwarestudies.com
manovich.net

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.

moritz.stefaner.eu

Mehrdad Yazdani

Data analysis

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

lab.softwarestudies.com/

Dr. Dominikus Baur

Data visualization and UI

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

do.minik.us

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.

danielgoddemeyer.com

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.

gc-cuny.academia.edu/AliseTifentale

Nadav Hochman

Theory and analysis

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

nadavhochman.net

Jay Chow

Data collection and management

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

jayjchow.com

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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.


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

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A DigitalThoughtFacility project, 2014