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Everybody Lies

Big Data, New Data and What the Internet Can Tell Us About Who We Really Are

By Seth Stephens-Davidowitz
13-minute read
Audio available
Everybody Lies: Big Data, New Data and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz

Everybody Lies (2017) is about the data collected in vast quantities by computers and over the internet. This data can help reveal fascinating information about the human psyche, behavior and quirks, because, as it turns out, people aren’t always so willing to communicate their true hopes and desires to others.

  • Anyone interested in the complex nature of human behavior
  • Media studies experts and social scientists
  • Anyone concerned about the power of the internet and online privacy

Seth Stephens-Davidowitz is an expert on internet data and big data in particular. He holds degrees from Stanford and Harvard Universities and worked previously as a data scientist at Google.

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Everybody Lies

Big Data, New Data and What the Internet Can Tell Us About Who We Really Are

By Seth Stephens-Davidowitz
  • Read in 13 minutes
  • Audio & text available
  • Contains 8 key ideas
Everybody Lies: Big Data, New Data and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz
Synopsis

Everybody Lies (2017) is about the data collected in vast quantities by computers and over the internet. This data can help reveal fascinating information about the human psyche, behavior and quirks, because, as it turns out, people aren’t always so willing to communicate their true hopes and desires to others.

Key idea 1 of 8

Data science is more intuitive than you think.

You’ve heard the term, but what exactly is big data?

The clue is in the name. Big data refers to an immense volume of data. A volume that’s so vast, in fact, that the human mind can hardly comprehend it. In other word, big data is data for which computational power is required to recognize patterns. Paradoxically, however, despite its remarkable scale, data science has an intuitive aspect to it. After all, if you think about it, we’re all data scientists in a way.

The author points to his grandmother. One Thanksgiving, she started suggesting to the author what his ideal partner should be like – at least as far as she was concerned! The partner needed to be clever, nice, funny, sociable and pretty (though no supermodels needed apply).

At 88, his grandma had seen plenty of relationships come and go. She was using years of information and data gathering to articulate the characteristics she saw as essential in successful relationships. She was utilizing information to spot patterns and predict how certain variables would impact one another – just as a data scientist would.

However, although data science is an intuitive process, intuition itself isn’t actually science. That’s why utilizing gathered data correctly is essential to refining one’s worldview. Data provides us with the material to confirm or rebut our initial gut feelings. It helps us identify more precise patterns and predictions than personal experience alone ever could.

Let’s return to grandma; she was convinced that relationships last longer if partners have mutual friends. This notion was based on her own experience, as she and her husband had spent many an evening with their friends in Queens, New York.

But in reality, her sample size was too small and the hard data suggests that she was mistaken. A 2014 study by Lars Backstrom and Jon Kleinberg, based on Facebook data, showed couples with more friends in common were more likely to change their relationship status from “in a relationship” to “single.”

This goes to show that though a gut feeling may get us far, data refine even the most intuitive person’s perspective.

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