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Big Data and Economics Research

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The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIOT 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1282))

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Abstract

Big data technology is a new digital technology, which is as famous as the Internet of things and artificial intelligence in the past 20 years. It is an important technology that will profoundly change the way of human production and life. For economic researchers, the popularization and development of big data will bring subversive changes to the acquisition, collation and timeliness of data in economic research, and will play a positive role in promoting the development of economic research methods. In terms of the availability of data sources, the combination of big data technology and computer technology can make researchers easily obtain the required data, no matter the structured data we usually use or the unstructured data we don’t often use. In terms of the timeliness of data acquisition, big data technology makes the timeliness of economic data possible and effectively solves the lag in economic research Post problem: in terms of the value of data acquisition, although massive data reduces the value density of data, the quality of data captured by big data technology is far higher than that of ordinary data acquisition methods.

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References

  1. Tao, H., Bhuiyan, M.Z.A., Rahman, M.A., Wang, G., Wang, T., Ahmed, M.M., Li, J.: Economic perspective analysis of protecting big data security and privacy. Future Gener. Comput. Syst. 98, 660–671 (2019)

    Google Scholar 

  2. Anejionu, O.C.D., (Vonu) Thakuriah, P., McHugh, A., Sun, Y., McArthur, D., Mason, P., Walpole, R.: Spatial urban data system: a cloud-enabled big data infrastructure for social and economic urban analytics. Future Gener. Comput. Syst. 98, 456–473 (2019)

    Google Scholar 

  3. Dembitz, Š., Gledec, G., Sokele, M.: An economic approach to big data in a minority language. Procedia Comput. Sci. 35, 427–436 (2014)

    Article  Google Scholar 

  4. Khan, R., Jammali-Blasi, A., Todkar, A., Heaney, A.: PHS61-Using big data for an economic evaluation of reducing the innappropriate prescribing of atypical antipsychotics among dementia patients. Value Health 18(3), A257 (2015)

    Google Scholar 

  5. Roth, S., Schwede, P., Valentinov, V., Žažar, K. and Kaivo-oja, J.: Big data insights into social macro trends (1800–2000): a replication study. Technol. Forecast. Soc. Change 149, 119759 (2019)

    Google Scholar 

  6. Vialetto, G., Noro, M.: An innovative approach to design cogeneration systems based on big data analysis and use of clustering methods. Energy Convers. Manag. 214, 112901 (2020)

    Article  Google Scholar 

  7. Aboelmaged, M., Mouakket, S.: Influencing models and determinants in big data analytics research: a bibliometric analysis. Inf. Process. Manage. 57(4), 102234 (2020). ISSN 0306–4573

    Google Scholar 

  8. Baig, M.I., Shuib, L., Yadegaridehkordi, E.: Big data adoption: state of the art and research challenges. Inf. Process. Manage. 56(6), 102095 (2019). ISSN 0306–4573

    Google Scholar 

  9. e Camargo Fiorini, P., Seles, B.M.R.P., Jabbour, C.J.C., Mariano, E.B., de Sousa Jabbour, A.B.L.: Management theory and big data literature: from a review to a research agenda. Int. J. Inf. Manage. 43, 112–129 (2018). ISSN 0268-4012

    Google Scholar 

  10. Surbakti, F.P.S., Wang, W., Indulska, M., Sadiq, S.: Factors influencing effective use of big data: a research framework. Inf. Manage. 57(1), 103146 (2020). ISSN 0378-7206

    Google Scholar 

  11. Cuquet, M., Fensel, A.: The societal impact of big data: a research roadmap for Europe. Technol. Soc. 54, 74–86 (2018). ISSN 0160-791X

    Google Scholar 

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Author information

Authors and Affiliations

  1. School of Economics, Shanghai University, 99 Shangda Road, Baoshan District, Shanghai, 200000, China

    Wanting Zhang

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  1. Wanting Zhang
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Correspondence to Wanting Zhang .

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Editors and Affiliations

  1. David Goldman Informatics Centre, University of Sunderland, Sunderland, UK

    John MacIntyre

  2. University of Shanghai for Science and Technology, Shanghai, China

    Jinghua Zhao

  3. Shenzhen University, Shenzen, Guangdong, China

    Xiaomeng Ma

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Zhang, W. (2021). Big Data and Economics Research. In: MacIntyre, J., Zhao, J., Ma, X. (eds) The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. SPIOT 2020. Advances in Intelligent Systems and Computing, vol 1282. Springer, Cham. https://doi.org/10.1007/978-3-030-62743-0_51

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