Časové pámo 0.4 Gender 0.6 ololol 0.4 Daniel 1.2
PERSONALITY PRICE
About Personality Price
One of the key properties of new media is numerical representation. When transferred into the digital realm, formerly abstract categories like paint saturation or sound delicacy become data with concrete values. If we use social media networks, it is a part of our personality that undergoes similar transformation - into categories of likes, "friendships" or published posts. We ourselves become a part of digital environment. Hence, does principle of numerical representation include even us? Our project shows, that most of us have, based on our online activities, a particular price, just like digital photos have exact number of pixels. But instead of them, to express the value of our personality, we use by far more attractive variable - money. That is because on internet, you are not only a data file, but a commodity as well. And a very sought-after one. How much do you think you cost?
Methodology
Our methodology is a synthesis of existing calculators of personal information prices and theoretical findings about proportions between particular pieces of information. Compared to mentioned calculators, our application counts the price automatically. Our project is a necessary simplified model of very complex issue. Data are of course influenced by laws of demand and supply, their price mair therefore fluctuate a lot. A big increase in data volumes is followed by ever-increasing demand for its processing, related to trends in marketing and targeted advertising which further alter the prices. On the real market world, the variable that affects a price probably more then each particular piece of data is a social group into which given person belongs. Do you own a house? Are you trying to lose weight? Are you freshly engaged? If yes, the price of your data is probably a bit higher.

We assigned following prices to those chunks of data:

User data Financial Times calculator ($, a) Totally Money calculator ($, b) Average ($)
Birthday 0.0005 0.0924 0.046
Gender 0.0005 0.0004 0.0005
Relationship info 0.01 0.092 0.01
Education info 0.0005 X 0.0005
Hometown X 0.0004 0.0004
Location X 0.0004 0.0004
E-mail X 0.007 0.007
Work history 0.08 0.066 0.07
User data Price ($) Why?
Number of friends 0.0008/friend Approximated from other demographic data (see 1)
Number of page likes 0.001/like Approximated from other demographic data, higher usability taken into account (see 2)
Website URL 0.005 Approximated from e-mail price, lower usability taken into account (see 1,2)

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Authors

Daniel Šlahař (design)

daniel.slahar@gmail.com

Ondřej Trhoň (code)

www.ondrejtrhon.cz

Bára Hyclová (theory)

barbora.hyclova@gmail.com
Thank you for lending a coder's hand:
Petr Houška
Jan Kryšpín
Tomáš Jánský
This project is a part of Big Bang Data exhibition at DOX Centre for Contemporary Art in Prague.
Bára Hyclová
Ondřej Trhoň
Daniel Šlahař
© 2017