Publication

PokeME: Applying Context-Driven Notifications to Increase Worker Engagement in Mobile Crowd-Sourcing

Lakmal Buddika Meegahapola
2020
Conference Papers

Abstract

In mobile crowd-sourcing systems, simply relying on people to opportunistically select and perform tasks typically leads to drawbacks such as low task acceptance/completion rates and undesirable spatial skews. In this paper, we utilize data from TASKer, a campus-based mobile crowd-sourcing platform, to empirically study and discover whether and how various context-aware notification strategies can help overcome such drawbacks. We first study worker interactions, in the absence of any notifications, to discover some spatio-temporal properties of task acceptance and completion. Based on these insights, we then experimentally demonstrate the effectiveness of two novel, non-personal, context-driven notification strategies, comparing the outcomes to two different baselines (no-notification and random-notification). Finally, using the data from the random-notification mechanism, we derive a classification model, incorporating several novel contextual features, that can predict a worker's responsiveness to notifications with high accuracy. Our work extends the crowd-sourcing literature by emphasizing the power of smart notifications for greater worker engagement.

Official source

https://infoscience.epfl.ch/entities/publication/4a3203a6-d3c2-43c0-ad58-631e0c06a0a6

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Lakmal Buddika Meegahapola
2020
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/4a3203a6-d3c2-43c0-ad58-631e0c06a0a6

About this result

Related concepts (17)

Network congestion

Network congestion in data networking and queueing theory is the reduced quality of service that occurs when a network node or link is carrying more data than it can handle. Typical effects include queueing delay, packet loss or the blocking of new connections. A consequence of congestion is that an incremental increase in offered load leads either only to a small increase or even a decrease in network throughput.

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In routers and switches, active queue management (AQM) is the policy of dropping packets inside a buffer associated with a network interface controller (NIC) before that buffer becomes full, often with the goal of reducing network congestion or improving end-to-end latency. This task is performed by the network scheduler, which for this purpose uses various algorithms such as random early detection (RED), Explicit Congestion Notification (ECN), or controlled delay (CoDel). RFC 7567 recommends active queue management as a best practice.

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