Enhancing the usage of crowd feedback for iterative design

Online crowd platforms (e.g. social networks, online communities, task markets) enable designers to gain insights from large audiences quickly and affordably. However, there is no guidance for designers to better allocate their social capital, time, and financial resources for acquiring feedback that meets their own needs. Also, feedback received online can be ambiguous and contradictory, making it difficult to interpret and act on. These limitations hinder the utility of crowd feedback, making designers hesitant to actively make use of feedback received. The goal of my dissertation is to 1) formulate a framework that suggests which crowd genres to solicit feedback according to individual needs, 2) develop lightweight activities that promote deeper interpretation on a large volume of feedback, and 3) design and deploy an experimental platform that collects long-term user data, and reduces the burden of conducting online studies of design feedback.