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.
Chen S., Härdle, W.K., Liang C., Schienle M. (2017). Network dynamics of high-frequency trading data, J Econometrics submitted.
Chen, C.Y.H., Härdle, W.K., Okhrin, Y. (2017). Tail event driven networks of SIFIs. SFB DP2017-004, J Econometrics, revise and resubmit.
Chen S., Chen, C.Y.H., Härdle, W.K., Lee, T.M., Ong, B. (2017). A first econometric analysis of the CRIX family, in Handbook of Blockchain, Digital Finance and Inclusion, Vol 1, Cryptocurrency, FinTech, InsurTech, and Regulation, David LEE Kuo Chuen Robert Deng, eds. ISBN: 9780128104415, Academic Press, Elsevier.
Linton, M., Teo, E.G.S., Bommes, E., Chen, C.Y.H., Härdle, W.K. (2017). Dynamic Topic Modelling for Cryptocurrency Community Forums. in Applied Quantitative Finance (Härdle, Chen, Overbeck eds) Springer Verlag, ISBN 978-3-662-54486-0.