Wisdom of the Crowd refers to the aggregated opinions of a crowd. It builds on a deceptively simple idea: Large groups of people are smarter than an elite few, no matter how brilliant—better at solving problems, fostering innovation, coming to wise decisions, even predicting the future.
However, this crowd is required to have certain characteristics so that it is likely outperform the individual group members. First, the crowd needs to be diverse, so that individuals can offer different pieces of information to the table. Second, the crowd needs to be decentralised, so that no one at the top dictates the collective output. Third, there needs to exist a way to summarise different opinions. Finally, the people in the crowd must be independent, so that they do not consider what others in the group think. Conversely, factors hampering crowd performance have been identified. For instance, social influence refers to how the opinions of one’s peers affect individual judgement and can undermine the generated knowledge.
In this project we explore methods and techniques to improve the quality of generated crowd knowledge during the implementation stage and the analysis stage. In the former, these methods and techniques entail guaranteeing crowd diversity and decentralisation, as well as implementing the tasks in a way that increases the likelihood of crowd engagement and serious input. The former stage focuses on developing and applying appropriate filtering mechanisms to remove low quality data, and contributors with poor performance.