Abstract

Internet-enabled technologies have provided a way for people to communicate and collaborate with each other. The collaboration and communication made crowdsourcing an efficient and effective activity. Crowdsourcing is a modern paradigm that employs cheap labors for accomplishing different types of tasks. The task is usually posted online as an open call, and members of the crowd self-select a task to be carried out. Crowdsourcing involves initiators or crowdsourcers, the crowd, crowdsourcing task, the process, and the crowdsourcing platform where requesters offer various tasks and crowd workers complete these tasks. As the crowdsourcing is carried out in the online environment, it gives rise to certain challenges. The major problem is the selection of crowd that is becoming a challenging issue with the growth in crowdsourcing popularity. Crowd selection has been significantly investigated in crowdsourcing processes. Nonetheless, it has observed that the selection is based only on a single feature of the crowd worker which was not sufficient for appropriate crowd selection. For addressing the problem of crowd selection, a novel “ant colony optimization-based crowd selection method” is presented in this paper that selects a crowd worker based on multicriteria features. By utilizing the proposed model, the efficiency and effectiveness of crowdsourcing activity will be increased.