Causal Analysis and Risk Assessment for Batch Crowdsourcing

doi:10.1109/TMC.2025.3532285

	Causal Analysis and Risk Assessment for Batch Crowdsourcing
	Chao, Ke 1; Wang, Shengling 1; Shi, Hongwei 1; Huang, Jianhui 2; Cheng, Xiuzhen 3
	2025-06-01
发表期刊	IEEE TRANSACTIONS ON MOBILE COMPUTING
ISSN	1536-1233
卷号	24 期号:6 页码:5312-5323
摘要	The way of task posting serves as the main pillar in achieving an efficient crowdsourcing market. Pioneer solutions on task posting can be categorized as retail task posting and batch task posting. Unlike retail task posting, which simply matches the most suitable worker to tasks, batch task posting considers the collaborations not only between workers and tasks but also among tasks, which brings high efficiency, low costs, and satisfactory task completion rates. However, the state of the arts on batch task posting leverage specific attributes to combine tasks as bundles for posting, leading to limited scalability. Hence, we propose a causal analysis framework for batch crowdsourcing to achieve an attribute-independent batch crowdsourcing solution that disentangles multi-factors to uncover the posting merits of tasks bundled at optimal prices, based on which an approximately optimal algorithm is further introduced to form reasonable bundles for posting. Since batch crowdsourcing may incur losses due to short-term profit fluctuation, a risk assessment method is proposed to encourage the requestor to act properly for loss mitigations. Our work explores the causal analysis and risk assessment in batch crowdsourcing for the first time, with the following highlights: 1) generality. It proposes a composite metric for gauging task bundles which avoids the issue of attribute dependence in the state of the arts, resulting in better universality; 2) synergy. By collaboratively considering the "value" and "relative position" of variables, our work derives results reflecting causal relationships rather than naive correlations; and 3) precision. We not only elucidate the probability of risk in batch crowdsourcing but also delineate the rate function governing its probability decay. This allows a requestor to know when and how fast to halt batch task posting.
关键词	Crowdsourcing Collaboration Mobile computing Sensors Scalability Resource management Prevention and mitigation Multitasking Costs Correlation causal inference risk assessment
DOI	10.1109/TMC.2025.3532285
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62402047] ; National Natural Science Foundation of China[62072044] ; National Natural Science Foundation of China[62293555] ; Major Program of Science and Technology Innovation 2030 of China[2022ZD0117105] ; Fundamental Research Funds for the Central Universities[2233100006] ; National Key R&D Program of China[2024YFC3308200]
WOS研究方向	Computer Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Telecommunications
WOS记录号	WOS:001483850200011
出版者	IEEE COMPUTER SOC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/40645
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Wang, Shengling
作者单位	1.Beijing Normal Univ, Sch Artificial Intelligence, Beijing 100875, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 3.Shandong Univ, Sch Comp Sci & Technol, Jinan 250100, Shandong, Peoples R China
推荐引用方式 GB/T 7714	Chao, Ke,Wang, Shengling,Shi, Hongwei,et al. Causal Analysis and Risk Assessment for Batch Crowdsourcing[J]. IEEE TRANSACTIONS ON MOBILE COMPUTING,2025,24(6):5312-5323.
APA	Chao, Ke,Wang, Shengling,Shi, Hongwei,Huang, Jianhui,&Cheng, Xiuzhen.(2025).Causal Analysis and Risk Assessment for Batch Crowdsourcing.IEEE TRANSACTIONS ON MOBILE COMPUTING,24(6),5312-5323.
MLA	Chao, Ke,et al."Causal Analysis and Risk Assessment for Batch Crowdsourcing".IEEE TRANSACTIONS ON MOBILE COMPUTING 24.6(2025):5312-5323.