Crowdsourcing developed rapidly for its inspiring public abilities. But how to effectively find qualified participants and how to find and prevent malicious workers may be the main difficulties to ensure the crowdsourcing quality. In this paper, the related theories of social network were used in crowdsourcing services, the task publisher (Seeker) was regarded as the network center, his Abilities Set (AS) would be quantified and his Friends Abilities Matrix (FAM) would be generated according to the communication between them, thus his social network was re-constructed. Subsequently, some friends that conformed to the ability requirements of the task would be chosen to be the task receivers (Solvers). The natural trust relationship in the social network was fully used to build a crowdsourcing service release system on weak centralization. By using the social network, even the privacy information needn’t to be shared with others, the system could help the seeker find solvers accurately in the seeker’s own social network according to task demands, and then help to reduce fraud and invalid data. The simulation experiments showed that the release system could help the seeker discover his own abilities, construct the FAM, and select the appropriate solvers precisely and automatically.
Peng, Zhenlong; Gui, Xiaolin; An, Jian; and Ji, Yali, "Ability Discovery and Weak Centralized Based Crowdsourcing Service Release System in Social Network" (2016). ICEB 2016 Proceedings. 84.