Final Project Realisation: Swappie


One can argue that taking selfies is an empowering method of visual self-expression, because we savor the control that we have over the process of creating.Art is defined by the process of expression and revealing ourselves with intentionality.The power and deliberation with which we take selfies is what we enjoy so much about the artistic process. When you take a selfie, you self-construct an image; a visual self-documentation to express personal autonomy. Often shared and broadcasted through social media and networking sites, selfies and wefies (group selfies) has allowed the general public to reclaim photography as a source of empowerment in a way that has never been possible before.

Therefore, taking and posting selfies is a way for us to create culture by subtly countering the messages that the media distributes. Even when we don’t counter the messages, per se, we are, at the very least, still publicizing our response to them, because what’s more personal than a close-up of one’s own face? Although the selfie as an art form is a debatably valid categorization, one thing is certain: We, with our #selfie , #wefie and #ussie, are actively participating in a modern take on the historic art of portraiture.

“Selfies are part of the evolution of self-portraiture, because at one point in our lives, the concept of a selfie didn’t exist,”
Alondra Nelson, a Columbia Sociology Professor



Swappie is the post-selfie selfie; a self-portrait that somehow plays with, jokes about, undermines, or contradicts the usual purpose of the selfie. A selfie is supposed to be a recognizable, generally flattering, self-portrait. The selfie is not going away; it is a worldwide trend, as the recent international data project Selfie City showed. The post-selfie selfie acknowledges all of this and, one way or another, breaks some cardinal rule of the form.

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To achieve this, I initially thought I had to create a programme in which participants can create their own swappies. I had found some open source Javascript codes and approached Juan who was kind enough to create a codepen of it for me. Alas, my knowledge and experience in coding and programming language were close to nil and I couldnt figure how to change and appropriate it; except for the text button (haha -.-)
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Randall then suggested I could do away with the programme and work on it in future which was much to my relief. He also had suggested that I use Tumblr as a medium to publish my swappies in – theres the reblog, like and follow option which is great. I created my tumblr site and looked for #faceswap #swap and #facebomb to see what existing content there are on the tumblrsphere. I then reblogged a few people to fill my site with inspiration. What I found were mostly celebrities face mashed with other celebrities bodies. Nicholas Cage as a meme (as seen from the movie FaceOff) and One Direction appeared most.

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I then began on a quest to manually faceswap my friends public images stolen from their social networking accounts on Photoshop. The front-facing pictures work the best (as opposed to people looking sideways or tilting their face at an angle) and also photos with more than one person generates more interest in the subject; So thus the trolling on Facebook began…


…and so did the swappin’.


and soon my whole tumblr page was filled with swappies that I had created myself. Though I’m generally pleased with the layout and how the page looks like a virtual gallery, I was disatisfied looking at the amount of attention/interaction of people. I felt as though I’m posting content that people would not get to see unless they follow me and it appears on their dashboard. Friends viewed their own images on my site but couldn’t leave any comments. So I thought, maybe tumblr wasn’t the best creative outlet at all.

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I took my project back to where it all began: Facebook.

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I created and curated a page called Swappie – which thankfully reached a much higher viewing rating then my tumblr site. The highest number of likes and comments in 1 photo was of my friend and her boyfriend. According to her, her boyfriends face on her body resembled her younger brother; and apparently many of her friends enjoyed her “boyshort” hairstyle. LOL

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And sharanya also mentioned that her face swapped onto MJ’s body looked like her cousin. Who woud’ve thought!


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…and some even started to look like they were of another race/ethnicity.


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Generally, the comments a favourable and nobody had came forward or requested that I remove their pictures.

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In no time at all, the comments and likes came coming in and flooding my notifications- which is a good sign! Facebook worked better for my project then tumblr did cause it allowed me to tag my friends in the swappies – allowing both their friends and acquaintances to view them and also leave comments and allowed me to reach a broader audience.

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I would say all in all my project achieved what it set out to do; which is to introduce the post-selfie selfie and also to get peoples attention and get people talking about what they think about the byproducts.

P.s: Initially I wanted to remain anonymous and tell people I’m just the banksy of faceswapping but people soon found out it was me by word of mouth 🙁 but hey, at least people were curious enough to talk about it!


My tumblr gallery:
My swappie facebook page:

Research: Selfie City by Lev Manovich


Oxford Dictionaries named “selfie” as its word of the year as usage of the word had increased by 17000% over the past 12 months, said the publisher of the Oxford English Language Dictionary. The act of selfie-taking has been examined microscopically perhaps because its popularity seems to encompass what society thinks to be the ills of young: narcissism, over-sharing, and endless aping of celebrity culture. 

In Selfiecity, the selfie is treated as a form of self-expression of individual Instagram users as well as a communal and social practice. The research project considers both the individual artistic intentions of a singular image and the overall patterns revealed by large amount of selfies made in a particular geographic location during one week.

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Montage of selfies from Selfiecity

Selfiecity, which was just released by Lev Manovich is an immersive project that investigates and analyzes a sample of 3,200 selfies taken in New York, Moscow, Berlin, Bangkok, and Sao Paulo.


When popular media covers exceptional events such as social upheavals,
revolutions, and protests, typically they just show you a few professionally shot photographs
that focus on this moment of protest at particular points in the city. So we were wondering if
examining Instagram photos that were shared in the central part of Kiev would give us a
different picture. Not necessarily an objective picture because Instagram has its own biases and it’s definitely not a transparent window into reality, but would give us, let’s say, a
more democratic picture.

– Lev Manovich, interview with Randall Packer


It is rather interesting to compare the professionally shot pictures published by popular media and ones taken by amateurs/anyone with access to a camera/smartphone. This project gives us actual statistics, data science, data visualizations, and interactive information about selfies taken around the world. The images were then subject to high-level face analysis with the help of Orbeus Inc.’s software, sorting by the presence of visual cues like smiles, glasses, and orientation of the head. The result is a sophisticated data visualization.

The website invites visitors to inspect selfies and how to reconcile different approaches to the selfie — how to view the same images as data. Given the cultural popularity of the selfie and its rapid growth, computational social science may offer a better way to interpret modern self-portraiture than conventional psychology.

“While art historians traditionally would engage in a close reading of a singular image and practice formal analysis of a unique artifact, the current project instead focuses on patterns in a larger set of images, analyzing such features as pose, facial expression and mood,” writes Alise Tifentale, a researcher on the aesthetics of new media at CUNY.


Not only does SelfieCity offer findings about the demographics of people taking selfies (as well as information about their various poses and expressions, such as trends in their smiles), it also shares a variety of data visualizations (such as collages that overlay hundreds of selfies that share similar characteristics), and allows visitors to explore the entire photo collection, could reveal patterns or trends that ripple throughout selfie culture based on the demographics of the participants.

Manovich explains that, “the central point of this project is to say, let me produce as many interesting visualizations as I can, maybe select the most interesting, even juxtapose them, and then to basically say that it’s not that one is more true than another. Everyone views a different idea.”

I’ve never thought that selfie’s could be a source of data that can be extracted to reveal a larger picture; one that says a lot about life and real lives in an increasingly digital and ‘virtual’ culture. A study Manovich created called “cultural analytics,” looks at large at sets of social media data as a means of better understanding our changing culture through new media. I am amazed by the level of complexity and degree of user interactions and interactivity and see it as an inspiration for my Project hyperessay and final project which applies a similar concept.

I believe that the age of the selfie is not over – in fact, its only just beginning. Humans beings have never been able to not look at themselves. When we have #selfiefriday, #selfiesunday, #selfieoftheday, and #selfiesfordays, and surely someday soon, the hologram selfie, the data need never stop flowing. SelfieCity suggests these casual acts of self-love may tell analysts of the future not just where we were but where we were at.

Micro-Project: Max Net Appropriation


I’m the kind of person that likes to idly scroll my facebook newsfeed or instagram feed when I’m bored. This way. I can see what my friends are up to and how life is treating them. Most of my friends are avid posters of selfies. I get to see what my friends look like without actually being with them in real life. I wanted to explore this concept further in MAX for allowing me to see more selfies (even of people I do not know” tagged with “selfie” or “wefie” on Flickr to see how many of these are posted on the Flickr Stream. Thank you August Black and Randall Packer for creating a MAX Patch that a software n00b like me can easily digest 😛


This video is based on August’s original Flickr Search that has been e-mailed to us. I had  I then followed the instructions for audio and visual manipulation. 

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(The original unedited MAX Patch)

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Firstly, I entered the two search queries which is “selfie” and “wefie”.

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The “movie” was moving at a speed to fast for me to screenshot so I adjusted it to 250 from 150:Screen shot 2014-10-08 at 9.50.09 AM


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Changing the presets would make it look like filters; the ones you would get on instagram.

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I also renamed it to Ruzana’s Flickr Search before turning on the audio.

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The final MAX Patch Product…

Click the above video to see my MAX working file

Click the above video to see the final video

My concept for this video is inspired by selfies/wefies on instagram. In instagram, you’re able to choose from a vast array of image filters to pimp your selfie. I adjusted various parameters on the max file to create a gradual change of filter and recorded it. The video starts of slow, representing the beginning of selfie culture and then gradually becomes faster and the filters so extreme that you can’t even see the faces in the images anymore. The accompanied sound also stops and sounds “glitched” at some point and then becomes really really fast – This is to represent how something as innocent as taking a picture of yourself and uploading it onto social media websites online may erupt and evolve into something bigger; an issue of self-objectification.

I find the idea of appropriating real-time images by searching for them on the internet very interesting. Prior to this, I had no idea you could generate audio based on visual information and transpose our data from one media type to another. I’ve learnt a lot from this exercise though it proved to be rather challenging at first 🙂 I’m happy I pulled through!