BetterCrowd: Human Computation for Big Data
In the last few years we have seen a rapid increase of available data. Digitization has become endemic. This has led to a data deluge that left many unable to cope with such large amounts of messy data. Also because of the large number of content producers and different formats, data is not always easy to process by machines due to its diverse quality and the presence of bias. Thus, in the current data-driven economy, if organisations can effectively analyse data at scale and use it as decision-support infrastructure at the executive level, data will lead to a key competitive advantage. To deal with the current data deluge, the BetterCrowd project will define and evaluate Human Computation methods to improve both the effectiveness and efficiency of currently available hybrid Human-Machine systems. The project comprises two main parts: (i) improving crowdsourcing effectiveness using novel techniques to detect malicious workers in crowdsourcing platforms; (ii) scaling up Human Computational techniques such that they can be applied to larger volumes of data.
Project lead: Dr Gianluca Demartini