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Big Data Analytics – Subtle Patterns and Relationships

Identity
Author: Mark Dixon
Thursday, March 14, 2013
8:55 am

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A recent Wall Street Journal article, “When ‘Likes’ Can Shed Light,” stated:

Patterns of “Likes” posted by people on Facebook can unintentionally expose their political and religious views, drug use, divorce and sexual orientation …

My first response was, “Duh, of course!”  But I think the implications are much deeper.  A wide range of disparate conditions can be linked together to imply seemingly distant results.  For example:

“Likes” for Austin, Texas; “Big Momma” movies; and the statement “Relationships Should Be Between Two People Not the Whole Universe” were among a set of 10 choices that, combined, predicted drug use. 

“Likes” for swimming, chocolate-chip cookie-dough ice cream and “Sliding On Floors with Your Socks On” were part of a pattern predicting that a person didn’t use drugs.

What in the world do all those things have to do with each other?
 
The article suggests that this type of analysis …
… arises from an emerging discipline in which experts sift through extremely large digital data sets, such as collections of web searches or Twitter messages, for subtle patterns and relationships.
“Subtle Patterns and Relationships” is the key phrase.  In our highly connected world, we all leave digital breadcrumbs scattered about that are subject to this type of analysis.  Sophisticated data analytics will progressively be able to pinpoint behavior patterns and even predict behavior, based on relationships between seemingly disparate and unrelated bits of data.
 
Will this be used to do a better job of targeting advertising?  If so, that might be beneficial to vendors and consumers alike.
 
But could it be used for nefarious purposes – even harassment, stalking, exploitation or discrimination?  You bet.  We had best be careful out there.
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