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Datasets for Business and Consumer Analytics

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Book cover Business and Consumer Analytics: New Ideas

Abstract

This extended appendix provides information, summaries and methodological details for publicly available datasets and, in particular, those used by various authors throughout this volume. Each of these datasets are publicly available and readers are highly encouraged to investigate these datasets for themselves for the continued journey and challenge of finding new ideas in business and consumer analytics.

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Notes

  1. 1.

    http://jmcauley.ucsd.edu/data/amazon/links.html.

  2. 2.

    http://www.json.org.

  3. 3.

    https://docs.mongodb.com.

  4. 4.

    Amazon Standard Identification Numbers.

  5. 5.

    http://www.versace.com.

  6. 6.

    https://en.wikipedia.org/wiki/Versace.

  7. 7.

    Check for the file ‘churn.txt’ found inside the compressed file at: http://dataminingconsultant.com/DKD2e_data_sets.zip.

  8. 8.

    https://archive.ics.uci.edu/ml/datasets.html.

  9. 9.

    http://marvel.com/comics.

  10. 10.

    http://www-personal.umich.edu/~mejn/netdata/lesmis.zip.

  11. 11.

    https://doi.org/10.6084/m9.figshare.1573032.v1.

  12. 12.

    https://www.macalester.edu/{~}abeverid/thrones.html.

  13. 13.

    https://networkofthrones.wordpress.com.

  14. 14.

    https://grouplens.org/datasets/movielens/.

  15. 15.

    https://webscope.sandbox.yahoo.com.

  16. 16.

    Note: most researchers call them ‘vectors’ but ‘array’ is probably more correct.

  17. 17.

    https://www.kaggle.com.

  18. 18.

    https://gist.github.com/entaroadun/1653794.

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Acknowledgements

P.M. acknowledges this research by The University of Newcastle, and previous funding from the Australian Research Council grants Future Fellowship FT120100060 and Discovery Project DP140104183. P.M. also thanks M.N. Haque and A. Gabardo for discussions and in particular for verifying that all links cited in this chapter were operational at the time of completion. The authors would also like to thank all the publishers of the publicly available datasets and the authors and editors for supporting the open sharing of data and information.

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  1. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia

    Natalie Jane de Vries & Pablo Moscato

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  1. Natalie Jane de Vries
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Correspondence to Natalie Jane de Vries .

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  1. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia

    Pablo Moscato

  2. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia

    Natalie Jane de Vries

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de Vries, N.J., Moscato, P. (2019). Datasets for Business and Consumer Analytics. In: Moscato, P., de Vries, N. (eds) Business and Consumer Analytics: New Ideas. Springer, Cham. https://doi.org/10.1007/978-3-030-06222-4_26

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  • DOI: https://doi.org/10.1007/978-3-030-06222-4_26

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