Computer Science ›› 2020, Vol. 47 ›› Issue (12): 18-24.doi: 10.11896/jsjkx.201200055

Special Issue: Software Engineering & Requirements Engineering for Complex Systems

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What Users Think about Predictive Analytics?——A Domestic Survey on NFRs

YANG Jing-wei1, WEI Zi-qi2, LIU Lin2   

  1. 1 Department of Computer ScienceCalifornia State University-Sacramen to Sacramen to California 95819USA
    2 School of Software Beijing National Research Center for Information Science and Technology Tsinghua University Beijing 100084,China
  • Received:2020-09-05 Revised:2020-10-30 Online:2020-12-15 Published:2020-12-17
  • About author:YANG Jing-wei,born in 1983Ph.Dassistant professor.His main research interests include requirements engineeringhuman-computer interactionand data &knowledge engineering.
    WEI Zi-qi,born in 1986Ph.D.His main research interests include computing theoryhealth ageing and big data techniques in health care.
  • Supported by:
    Baidu-Tsinghua School of Software Medical AI Cooperation Project.

Abstract: With the recent advancement in data sciencepredictive analytics (PA) functions have been built into many commercial productswhich affects several "non-functional" goalsincluding usabilityperformanceand transparency of the softwareas well as privacy and well-being of the user.The direct and indirect consequences are yet to be understood better before the service providers take any further actions in response.In this worka domestic survey is conducted with a sample set of 565 domestic respondents from Chinaon their acceptance of applications with PA.The result shows that many consumers recognize the benefit of PA featuresbut they are not without concerning about transparencyprivacyand personal well-being.Once users are highly concernedthey may choose not to use these features or even give up the products altogether.Based on the survey resultthis paper discusses requirements engineering can help the stakeholders make better decisions related to PA adoption and designand how RE tools can help address user concerns related to PA.

Key words: Acceptance, Consumer, Non-functional requirements (NFRs), Predictive analytics (PA), Survey

CLC Number: 

  • TP391
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