theatlantic:

Behind the Machine’s Back: How Social Media User Avoid Getting Turned Into Big Data

Social media companies constantly collect data on their users because that’s how they provide customized experiences and target their advertisements. All Twitter and Facebook users know this, and there is a broad array of feelings about how good or bad the persistent tracking of their social relationships is. 
What we do know, though, is that—when they want to—they are aware of how to go behind the machine’s back. They know how to communicate with just the humans without tipping their intentions to the algorithm. 
In a new paper, University of North Carolina sociologist Zeynep Tufekci explores some of these strategies among Turkish protesters. She looks at these behaviors as analytical challenges for researchers who are trying to figure out what’s going on. “Social media users engage in practices that alter their visibility to machine algorithms, including subtweeting, discussing a person’s tweets via ‘screen captures,’ and hate-linking,” Tufekci writes. “All these practices can blind big data analyses to this mode of activity and engagement.”
The same practices, though, from the user perspective, can be understood as strategies for communicating without being computed. All they require to execute is thinking like an algorithm.
Read more. [Image: Renee Magritte via Wikimedia Commons/The Atlantic]

theatlantic:

Behind the Machine’s Back: How Social Media User Avoid Getting Turned Into Big Data

Social media companies constantly collect data on their users because that’s how they provide customized experiences and target their advertisements. All Twitter and Facebook users know this, and there is a broad array of feelings about how good or bad the persistent tracking of their social relationships is. 

What we do know, though, is that—when they want to—they are aware of how to go behind the machine’s back. They know how to communicate with just the humans without tipping their intentions to the algorithm. 

In a new paper, University of North Carolina sociologist Zeynep Tufekci explores some of these strategies among Turkish protesters. She looks at these behaviors as analytical challenges for researchers who are trying to figure out what’s going on. “Social media users engage in practices that alter their visibility to machine algorithms, including subtweeting, discussing a person’s tweets via ‘screen captures,’ and hate-linking,” Tufekci writes. “All these practices can blind big data analyses to this mode of activity and engagement.”

The same practices, though, from the user perspective, can be understood as strategies for communicating without being computed. All they require to execute is thinking like an algorithm.

Read more. [Image: Renee Magritte via Wikimedia Commons/The Atlantic]


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