“Structural change” is a phrase I’m hearing often this year. From political candidates to collegiate administrators, folks across all industries are finding that some issues cannot be fixed by simple policy prescriptions. Rather, the change must be more ground breaking. I claim this is true for social networks as well. The incremental changes that Twitter and Facebook do to their respective timelines is never going to absolve them of the challenges they continue to face with misinformation.
My thesis will be exploring this area. Fundamentally, it asks if we can design a scalable network that guarantees users won’t get two things - misinformation and filter bubbles. Both words are very broad and I can go on a long tangent on how to clearly define these terms, but I’ll reserve that for a different blog post!
I claim that users want (and deserve) two things when reading a news timeline on any network: the right to only be given news that is written without malicious intentions (that is, articles not written to purposely deceive readers for personal gain) and the right to learn new things. Why the right to learn new things? Because if I get my news exclusively from certain timelines, I don’t know what I don't know. These algorithms are tuned to mostly tell me more about things I already know. It is therefore the obligation of those timelines to expose me to new information. I claim that this will not only be a valuable trait for society (if all timelines pushed new, non-trending, accurate information to users) but it will also increase user engagement on the network.
These claims largely conflict with popular wisdom. After all, isn’t fake news pervasive in digital networks because of human attraction to clickbait? And don’t filter bubbles (where networks recommend more things based on what you like) naturally increase user engagement?
I would comfortably answer “probably, yes” to both those questions. But that doesn’t negate the opposite. Humans can equally be interested in networks pushing reliable/accurate content. Further, users can be more attracted to networks that purposely push new types of information that have no relation to their past interests.
That’s what this thesis will study. I will be designing a real information network with those rules in place and testing if people find it to be more satisfying than being on other popular networks - namely Facebook and Twitter.