Crowd-answering system via microblogging

Most crowdsourcing systems leverage the public platforms, such as Amazon Mechanical Turk (AMT), to publish their jobs and collect the results. They are charged for using the platform´s service and they are also required to pay the workers for each successful job. Although the average wage of the online human worker is not high, for a 24×7 running service, the crowdsourcing system becomes very expensive to maintain. We observe that there are, in fact, many sources that can provide free online human volunteers. Microblogging system is one of the most promising human resources. In this paper, we present our CrowdAnswer system, which is built on top of Weibo, the largest microblogging system in China. CrowdAnswer is a question-answering system, which distributes various questions to different groups of microblogging users adaptively. The answers are then collected from those users´ tweets and visualized for the question originator. CrowdAnswer maintains a virtual credit system. The users need credits to publish questions and they can gain credits by answering the questions. A novel algorithm is proposed to route the questions to the interested users, which tries to maximize the probability of successfully answering a question.