Toward crowdsourcing data mining

Abstract

Nowadays, crowdsourcing has emerged as a popular and important problem-solving approach. The major difference between crowdsourcing and traditional outsourcing lies on the people which tasks were outsourced. Those people involved in crowdsourcing are generally varied in knowledge, demographic properties, and number. Many applications and services have been developed to solve various types of tasks. However, these applications and services focus on providing platforms for outsourcing to the crowd. Little has been addressed so far on the management and usage of those information produced during the crowdsourcing process. Actually, as an emerging social network application and service, the data and social interactions created during crowdsourcing should carry important and valuable knowledge. This knowledge will develop various techniques for mining messages and information of crowdsourcing process. In this work, we address several approaches to discover useful knowledge from data created for and in crowdsourcing process. We hope the outcome of this research could help discovering usable knowledge from such emerging social network services and bring benefit in constructing crowdsourcing services.