Are we creating personalized propaganda bubbles? Do you only follow news outlets that pump out the same rhetoric?
New data visualizations give a startling picture of online activity during the latest conflict between Israelis and Palestinians. And they reveal just how much online media and social networks help us to create our own information bubbles, customized to reinforce our political beliefs.
Gilad Lotan is the chief data scientist at betaworks, which has launched high-profile companies that include SocialFlow and bitly. Looking at Lotan’s network graph of Twitter traffic from his blog i love data, I can’t help but feel that we really are living in a version of The Matrix. The media constructs our reality and we’re plugged into it 24/7. Except here, in theory, we have the freedom to make our own decisions.
In Lotan’s view, however, that’s a big part of the problem:
Not only is there much more media produced, but it is coming at us at a faster pace, from many more sources. … the landscape is much more nuanced, and highly personalized. We construct a representation of our interest by choosing to follow or like specific pages. The more we engage with certain type of content, the more similar content is made visible in our feeds.
If you’re rooting for Israel, you might have seen videos of rocket launches by Hamas adjacent to Shifa Hospital. Alternatively, if you’re pro-Palestinian, you might have seen the following report on an alleged IDF sniper who admitted (on Instagram) to murdering 13 Gazan children. Israelis and their proponents are likely to see IDF videos such as this one detailing arms and tunnels found within mosques passed around in their social media feeds, while Palestinian groups are likely to pass around images displaying the sheer destruction caused by IDF forces to Gazan mosques. One side sees videos of rockets intercepted in the Tel-Aviv skies, and other sees the lethal aftermath of a missile attack on a Gazan neighborhood.
The better we get at modeling user preferences, the more accurately we construct recommendation engines that fully capture user attention. In a way, we are building personalized propaganda engines that feed users content which makes them feel good and throws away the uncomfortable bits.