to the state-of-the-art offline mechanism. Index Terms—Crowdsourcing, incentive mechanism, mobile sensing Ç 1

applications and systems lack good incentive mechanisms that can attract more user participation. To address this issue, we design incentive mechanisms for mobile phone sensing. We consider two system models: the platform-centric model where the platform provides a reward shared by participating users

crowdsourcing making use of the real world context. In this paper we assess how the idea of user-generated content, web-based crowdsourcing, and mobile electronic coordination can be combined to extend crowdsourcing beyond the digital domain and link it to tasks in the real world. To explore our concept we

to be crowdsourced without any explicit effort on the part of users. Zee leverages the inertial sensors (e.g., accelerometer, compass, gyroscope) present in the mobile devices such as smartphones carried by users, to track them as they traverse an indoor environment, while simultaneously performing WiFi scans. Zee

Mechanical Turk, and etc.) emerged in recent years that allow requesters from all around the world to post tasks and seek help from an equally global pool of workers. However, intrinsic incentive problems reside in crowdsourcing applications as workers and requester are selfish and aim

Abstract—Mobile phone sensing has become increas-ingly popular since it can collect and analyze real-time data anywhere anytime, especially with the help of mobile phone users via crowdsourcing. In order to stabilize the mobile crowdsourcing at a massive scale, incentive mecha-nisms are needed

several incentive-based models and examine their effects. Next, we assess the accuracy measures of our incentive models against a gold standard and ascertain which incentives provide the best results. We find that some incentives actually encourage quality if the task is designed appropriately.

Abstract: This paper presents details of a general purpose micro-task on-demand platform based on the crowdsourcing philosophy. This platform was specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquity and iii) embedded sensors

Online social networks offer unprecedented potential for rallying a large number of people to accomplish a given task. Here we focus on information gathering tasks where rare information is sought through ‘‘referral-based crowdsourcing’’: the information request is propagated recursively through

In this subsection, we describe human factors that are pertinent to tasks, namely Feedback and Incentives. Skill Variety represents the number of different skills a task requires from a worker. Task Identity represents whether a task is part of a bigger task or not. Task Autonomy indicates if a worker depends