Estimating Conversational Styles in Conversational Microtask Crowdsourcing

Estimating Conversational Styles in Conversational Microtask Crowdsourcing

Qiu, S. (TU Delft Web Information Systems)
Gadiraju, Ujwal (TU Delft Web Information Systems)
Bozzon, A. (TU Delft Human-Centred Artificial Intelligence; TU Delft Web Information Systems)

2020

Crowdsourcing marketplaces have provided a large number of opportunities for online workers to earn a living. To improve satisfaction and engagement of such workers, who are vital for the sustainability of the marketplaces, recent works have used conversational interfaces to support the execution of a variety of crowdsourcing tasks. The rationale behind using conversational interfaces stems from the potential engagement that conversation can stimulate. Prior works in psychology have also shown that ‘conversational styles’ can play an important role in communication. There are unexplored opportunities to estimate a worker’s conversational style with an end goal of improving worker satisfaction, engagement and quality. Addressing this knowledge gap, we investigate the role of conversational styles in conversational microtask crowdsourcing. To this end, we design a conversational interface which supports task execution, and we propose methods to
estimate the conversational style of a worker. Our experimental setup was designed to empirically observe how conversational styles of workers relate with quality-related outcomes. Results show that even a naive supervised classifier can predict the conversation style with high accuracy (80%), and crowd workers with an Involvement conversational style provided a significantly higher output quality, exhibited a higher user engagement and perceived less cognitive task load in comparison to their counterparts. Our findings have important implications on task design with respect to improving worker performance and their engagement in microtask crowdsourcing.

cognitive task load.
conversational style
microtask crowdsourcing
user engagement
work outcomes

http://resolver.tudelft.nl/uuid:50ceaacc-6bfa-4bc2-9673-59cae2c783fb

https://doi.org/10.1145/3392837

2021-11-08

Proceedings of ACM Human-Computer Interaction (CSCW), 4 (CSCW1)

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2020 S. Qiu, Ujwal Gadiraju, A. Bozzon