专题：Mobile Crowdsensing and Crowdsourcing

This cluster of papers focuses on the use of crowdsourcing platforms, particularly Amazon's Mechanical Turk, for research and data collection purposes. It explores topics such as data quality, incentive mechanisms, mobile sensing, truth discovery, and the application of crowdsourcing in behavioral research and participatory sensing.
最新文献
Joint Dependency and Conflicting Task Allocation in Collaboration-Aware Spatial Crowdsourcing

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Planning for New Threats to Online Research Data Validity: The Issue of Computer-Using Agents

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On the Use of Metadata Templates to Capture Knowledge About IoT Infrastructures

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Model training oriented mobile crowdsourcing tasks: Worker selection and incentive mechanism design

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Rethinking the Role of Crowds in the Age of AI

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Code and Data Repository for Human-Algorithm Collaborative Truth Inference in Crowdsourcing

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A Real-Time Material Demand Forecasting Method for Emergency Decision-Making Driven by Social Media Data

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Automatic Expert Discovery in LLM Upcycling via Sparse Interpolated Mixture-of-Experts

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Disaster Response Systems and Data Integrity: Optimizing Crowdsourced Inputs with Simple Machine Learning

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Tag-First: Mitigating Distributional Bias in Synthetic User Profiles through Controlled Attribute Generation

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近5年高被引文献
Advances and Open Problems in Federated Learning

book Full Text OpenAlex 1269 FWCI152.296

Federated Learning for Internet of Things: A Comprehensive Survey

article Full Text OpenAlex 894 FWCI80.795

Response rates of online surveys in published research: A meta-analysis

article Full Text OpenAlex 829 FWCI287.484

Data quality in online human-subjects research: Comparisons between MTurk, Prolific, CloudResearch, Qualtrics, and SONA

article Full Text OpenAlex 719 FWCI155.552

Exploring Millions of Footprints in Location Sharing Services

article Full Text OpenAlex 694 FWCI8.529

Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges

article Full Text OpenAlex 611 FWCI57.933

Federated learning on non-IID data: A survey

article Full Text OpenAlex 605 FWCI56.934

A Survey on Federated Learning for Resource-Constrained IoT Devices

article Full Text OpenAlex 505 FWCI48.166

“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI

article Full Text OpenAlex 502 FWCI65.957

An Empirical Study of Geographic User Activity Patterns in Foursquare

article Full Text OpenAlex 496 FWCI7.016