Information cascades and the filter bubble
Much has been written about the “filter bubble” (a term coined by Eli Pariser in his latest book/TED Talk of the same name). Pariser makes the argument that the filter bubble essentially arises from information cascades that occur in the world. This is particularly interesting when looking at viral trends (video and news especially) that occur over twitter. Often times, I find that certain news events (such as Occupy Wall Street or a major venture financing in the NYC metro area) generate so much noise in my Twitter feed that I’m unable to figure out what else is going on at the time. Because I follow a large amount of early stage technologists in the NYC startup ecosystem, an event that may be relatively small feels like a giant occurrence in my twitter feed. This is effectively an information cascade that magnifies the importance of something to me relative to its actual importance.
This can be great occasionally, but without effective tools to put all of this in context relative to other events happening outside my social graph, things can get problematic. This can also be an issue when incorrect news or information is reported since many times the incorrect news is just reinforced.
Introducing serendipity/chaos into social networks and disrupting information cascades presents a host of interesting discussions. Pariser argues that being constrained to a “Filter Bubble” is not a good thing – while I can agree with this for a few of the reasons outlined above, ultimately the power of these information cascades is one that can be used for good as well. The power of the internet is that it more easily facilitates frictionless transfer of information. In the right circumstances, this can be a healthy thing, but until we get better at managing the social graph, more easily facilitated information cascades may remain a simultaneous advantage and drawback of the internet.