Open AccessTruthful Mechanism for Task Assignment in Crowdsourcing with Social Network
Author(s) -
Haiyan Qin,
Yonglong Zhang,
Bin Li
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1284/1/012038
Subject(s) - crowdsourcing , crowds , task (project management) , computer science , mechanism (biology) , social network (sociolinguistics) , cohesion (chemistry) , knowledge management , data science , world wide web , social media , computer security , economics , management , philosophy , chemistry , organic chemistry , epistemology
Macrotasks like document writing, product design, or web development, require expert skills and the collective contributions of the crowds. In fact, there are few studies give close attention to the workers with social network in crowdsourcing. Social networks provide an available platform for cooperation among social workers. In this paper, we discuss the complex task assignment in crowdsourcing where the workers are in a social network. A Truthful Mechanism for the task assignment in Crowdsourcing with Social Network (TMC-SN) is proposed to solve the challenges in this scenario. The problem is modeled as an auction, where the requesters are buyers, workers are sellers, and the crowdsourcing platform serves as an auctioneer. In order to find out the most appropriate team, TMC-SN measures Worker Fitness of the worker for the team from both Marginal Contribution and Team Cohesion. We demonstrate that TMC-SN has fine economic properties such as truthfulness, individual rationality, and budget balance. The evaluation results show that TMC-SN is advantageous in terms of Social Welfare and favorable for the workers.