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Data science and digital society

Author

Listed:
  • Chen Cathy Yi-Hsuan

    (Ladislaus von Bortkievicz Chair of Statistics; Institute for Statistics und Econometrics; School of Business and Economics; Humboldt-Universität zu Berlin; Berlin, Germany)

  • Härdle Wolfgang Karl

    (Ladislaus von Bortkievicz Chair of Statistics; Institute for Statistics und Econometrics; School of Business and Economics; Humboldt-Universität zu Berlin; Berlin, Germany)

Abstract

Data Science looks at raw numbers and informational objects created by different disciplines. The Digital Society creates information and numbers from many scientific disciplines. The amassment of data though makes is hard to find structures and requires a skill full analysis of this massive raw material. The thoughts presented here on DS2 - Data Science & Digital Society analyze these challenges and offers ways to handle the questions arising in this evolving context. We propose three levels of analysis and lay out how one can react to the challenges that come about. Concrete examples concern Credit default swaps, Dynamic Topic modeling, Crypto currencies and above all the quantitative analysis of real data in a DS2 context.

Suggested Citation

  • Chen Cathy Yi-Hsuan & Härdle Wolfgang Karl, 2017. "Data science and digital society," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 11(1), pages 669-675, July.
    • Handle: RePEc:vrs:poicbe:v:11:y:2017:i:1:p:669-675:n:71
    DOI: 10.1515/picbe-2017-0071
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    References listed on IDEAS

    as
    1. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    2. Härdle, Wolfgang Karl & Hautsch, Nikolaus & Mihoci, Andrija, 2012. "Modelling and forecasting liquidity supply using semiparametric factor dynamics," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 610-625.
    Full references (including those not matched with items on IDEAS)

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