Some of the most pressing challenges facing humanity today, such as how to respond to climate change or govern the internet, are too complex for any individual or small group to completely understand by themselves, but a lot of people each know a piece of the problem or solution. This is somewhat like a billion-piece jigsaw puzzle where somebody threw away the box and mailed each piece to a different person. Attempts are now being made to build platforms where people can bring their pieces and assemble them into solutions. This thesis examines such platforms, how people use and perceive them and their content, and how certain design decisions such as the exposure of discussion behind collaboratively produced content can affect those perceptions. Through a set of studies ranging from qualitative interviews to controlled experiments with hundreds or thousands of participants, this thesis adds to our understanding of how humans use and perceive content on such platforms, including when primary content is presented alongside related content or discussion, so that we can better understand how to design these systems to better achieve their users’ intended goals. The research integrates insights from computer science and social psychology with latent variable modeling techniques in order to increase our understanding of what people are trying to accomplish on an example platform designed to support large-scale collaboration around a complex issue, and experimentally explores how people perceive the content they find on such sites. Data and projects used in this thesis come from a diversity of sources including Wikipedia, the President’s SAVE award ideation contest (facilitated through the IdeaScale ideation platform), and the MIT Climate CoLab.