Gac: A deep reinforcement learning model toward user incentivization in unknown social networks

S Wu, W Li, Q Bai - Knowledge-Based Systems, 2023 - Elsevier
In recent years, many applications have deployed incentive mechanisms to promote users'
attention and engagement. Most incentive mechanisms determine specific incentive values …

The Dark Side of Recruitment in Crowdsourcing: Ethics and Transparency in Micro-Task Marketplaces

H Xie, E Maddalena, R Qarout, A Checco - … Supported Cooperative Work …, 2023 - Springer
Micro-task crowdsourcing marketplaces like Figure Eight (F8) connect a large pool of
workers to employers through a single online platform, by aggregating multiple …

[PDF][PDF] The effects of autonomy and task meaning in algorithmic management of crowdwork

Y Toyoda, G Lucas, J Gratch - … of the 19th International Conference on …, 2020 - ifaamas.org
With the tremendous development of AI technologies, people will increasingly encounter
software algorithms that supervise their work. Algorithmic management is the term for AI that …

On dynamically pricing crowdsourcing tasks

X Miao, H Peng, Y Gao, Z Zhang, J Yin - ACM Transactions on …, 2023 - dl.acm.org
Crowdsourcing techniques have been extensively explored in the past decade, including
task allocation, quality assessment, and so on. Most of professional crowdsourcing platforms …

A budget-limited mechanism for category-aware crowdsourcing of multiple-choice tasks

Y Luo, NR Jennings - Artificial Intelligence, 2021 - Elsevier
Crowdsourcing harnesses human effort to solve computer-hard problems such as photo
tagging, entity resolution and sentiment analysis. Such tasks often have different levels of …

A clarity and fairness aware framework for selecting workers in competitive crowdsourcing tasks

SJ Bozorg Zadeh Razavi, H Amintoosi, M Allahbakhsh - Computing, 2024 - Springer
Crowdsourcing is a powerful technique for accomplishing tasks that are difficult for machines
but easy for humans. However, ensuring the quality of the workers who participate in the …

Identifying influential users in unknown social networks for adaptive incentive allocation under budget restriction

S Wu, W Li, H Shen, Q Bai - Information Sciences, 2023 - Elsevier
In recent years, recommenze the social influence among users to enhance the effect of
incentivization. Through incentivizing influential users directly, their followers in the social …

Incentivizing Crowdsourcing Workers via Social Networks in Edge Computing

W Tang, R Chen, Z Zhang, S Guo - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Crowdsourcing has proven to be an effective approach for leveraging collective intelligence
to solve tasks. However, in edge computing environments, crowdsourcing platforms often …

Cost-effective crowdsourced join queries for entity resolution without prior knowledge

B Yin, W Zeng, X Wei - Future Generation Computer Systems, 2022 - Elsevier
The join query, which finds matching pairs from two object sets, is a fundamental operation
in computer systems and helps to solve many real problems, eg, entity resolution. In this …

REFORM: reputation based fair and temporal reward framework for crowdsourcing

S Kanaparthy, S Damle, S Gujar - arXiv preprint arXiv:2112.10659, 2021 - arxiv.org
Crowdsourcing is an effective method to collect data by employing distributed human
population. Researchers introduce appropriate reward mechanisms to incentivize agents to …