Conversational crowdsourcing

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Abstract

The trend of remote work leads to the prosperity of crowdsourcing marketplaces. In crowdsourcing marketplaces, online workers can select their preferable tasks and then complete them to get paid, while requesters design and publish tasks to acquire their desirable data. The standard user interface of the crowdsourcing task is the web page, where users provide answers using HTML-based web elements, and the task-related information (including instructions and questions) is displayed on a single web page. Although the traditional way of presenting tasks is straightforward, it could negatively affect workers’ satisfaction and performance by causing problems such as boredom and fatigue. To address this challenge, we proposed a novel concept — conversational crowdsourcing, which employs conversational interfaces to facilitate crowdsourcing task execution. With conversational crowdsourcing, workers receive task information as messages from a conversational agent, and provide answers by sending messages back to the agent. In this vision paper, we introduce our recent work in terms of using conversational crowdsourcing to improve worker performance and experience by employing novel human-computer interaction affordances. Our findings reveal that conversational crowdsourcing has important implications in improving the worker satisfaction and requester-worker relationship in crowdsourcing marketplaces.

Original languageEnglish
Title of host publicationProceedings of the Crowd Science Workshop: Remoteness, Fairness, and Mechanisms as Challenges of Data Supply by Humans for Automation co-located with 34th Conference on Neural Information Processing Systems (NeurIPS 2020)
EditorsDmitry Ustalov, Fabio Casati, Alexey , Daria Baidakova
Pages1-6
Number of pages6
Volume2736
Publication statusPublished - 2020
Event2020 Crowd Science Workshop: Remoteness, Fairness, and Mechanisms as Challenges of Data Supply by Humans for Automation - Vancouver, Canada
Duration: 11 Dec 202011 Dec 2020

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS
ISSN (Print)1613-0073

Conference

Conference2020 Crowd Science Workshop: Remoteness, Fairness, and Mechanisms as Challenges of Data Supply by Humans for Automation
Abbreviated titleCSW 2020
CountryCanada
CityVancouver
Period11/12/2011/12/20

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