Rankr: A Mobile System for Crowdsourcing Opinions [chapter]

Yarun Luon, Christina Aperjis, Bernardo A. Huberman
2012 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
Evaluating large sets of items, such as business ideas, is a difficult task. While no one person has time to evaluate all the items, many people can contribute by each evaluating a few. Moreover, given the mobility of people, it is useful to allow them to evaluate items from their mobile devices. We present the design and implementation of a mobile service, Rankr, which provides a lightweight and efficient way to crowdsource the relative ranking of ideas, photos, or priorities through a series
more » ... f pairwise comparisons. We discover that users prefer viewing two items simultaneously versus viewing one image at a time with better fidelity. Additionally, we developed an algorithm that determines the next most useful pair of candidates a user can evaluate to maximize the information gained while minimizing the number of votes required. Voters do not need to compare and manually rank all of the candidates.
doi:10.1007/978-3-642-32320-1_2 fatcat:wemrhibkfbbajbzc7xc2eipgpu