2016/09/10 by Malay Bhattacharyya, Bhattacharyya, Malay
Computer Science · #68Txx #FOS: Computer and information sciences #H.1.2 #Human-Computer Interaction (cs.HC) #I.2 #acm:68Txx #cs.HC #msc:68Txx
paper · pdf · doi:10.48550/arxiv.1609.03050
Works in Progress, Third AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2015), San Diego, USA
arxiv created 2016/09/10 · arxiv updated 2016/09/13
Crowdsourcing environments have shown promise in solving diverse tasks in limited cost and time. This type of business model involves both the expert and non-expert workers. Interestingly, the success of such models depends on the volume of the total number of workers. But, the survival of the fittest controls the stability of these workers. Here, we show that the crowd workers who fail to win jobs successively loose interest and might dropout over time. Therefore, dropout prediction in such environments is a promising task. In this paper, we establish that it is possible to predict the dropouts in a crowdsourcing market from the success rate based on the arrival pattern of workers.