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research article

Toward a mixed-initiative QA system: from studying predictors in Stack Exchange to building a mixed-initiative tool

Convertino, Gregorio
•
Zancanaro, Massimo
•
Piccardi, Tiziano
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2017
International Journal Of Human-Computer Studies

This article envisions a new customer support solution that merges the efficiency of crowd-based Question and Answer (QA) sites with the effectiveness of traditional customer care services. QA sites use crowdsourcing to solve problems in a very efficient way and they represent a new approach that can compete with traditional customer support services. Despite the remarkable efficiency of popular QA sites, if a question is not solved almost immediately, the chances are that it will not be solved soon or perhaps ever. This article provides evidence of a consistent Dark Side, a group of questions that remain unsatisfied or are satisfied very late, in eight popular QA sites on Stack Exchange. About 25-30% of all the questions in these sites fall into this Dark Side group. The findings show that predicting if a question will end up in the Dark Side is feasible, although with some approximation, without relying on content features. On the basis of this evidence, the article first presents and tests a model to predict the Dark Side and then presents a proof-of-concept of a mixed-initiative tool that helps a crowd-manager to decide whether an incoming question will be solved by the crowd or it should be redirected to a dedicated operator. Multiple evaluations of the proposed tool are reported. Finally, it concludes with lessons for the design and management of future QA platforms.

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Type
research article
DOI
10.1016/j.jhcs.2016.10.008
Web of Science ID

WOS:000392038700001

Author(s)
Convertino, Gregorio
Zancanaro, Massimo
Piccardi, Tiziano
Ortega, Felipe
Date Issued

2017

Publisher

Academic Press Ltd- Elsevier Science Ltd

Published in
International Journal Of Human-Computer Studies
Volume

99

Start page

1

End page

20

Subjects

Question Answering sites

•

Crowdsourcing

•

Mixed-initiative tools

•

Customer Support

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
IINFCOM  
Available on Infoscience
February 17, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/134497
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