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Applying Analytics to Artist Provided Text to Model Prices of Fine Art

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Complex Pattern Mining

Part of the book series: Studies in Computational Intelligence ((SCI,volume 880))

Abstract

This work develops a set of text based features to be used in the prediction of the price of a work of contemporary art sold online. These features are developed using text clustering based on vectors and sentiment analysis. These features are then examined for their impact on the accuracy of a predictive model.

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Acknowledgements

This research is supported by the National Science Foundation under grant IIP 1749105. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Author information

Authors and Affiliations

  1. University of North Carolina at Charlotte, Charlotte, NC, 28223, USA

    Laurel Powell, Anna Gelich & Zbigniew W. Ras

  2. New Media Arts Department, Polish-Japanese Academy of Information Technology, 02-008, Warsaw, Poland

    Anna Gelich

  3. Computer Science Department, Polish-Japanese Academy of Information Technology, 02-008, Warsaw, Poland

    Zbigniew W. Ras

Authors
  1. Laurel Powell
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  2. Anna Gelich
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  3. Zbigniew W. Ras
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Corresponding author

Correspondence to Laurel Powell .

Editor information

Editors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Bari Aldo Moro, Bari, Italy

    Annalisa Appice

  2. Dipartimento di Informatica, Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

  3. Dipartimento di Informatica, Università degli Studi di Bari Aldo Moro, Bari, Italy

    Corrado Loglisci

  4. ICAR-CNR, Rende, Italy

    Giuseppe Manco

  5. Università degli Studi di Napoli Federico II, Naples, Italy

    Elio Masciari

  6. Department of Computer Science, University of North Carolina, Charlotte, NC, USA

    Zbigniew W. Ras

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Powell, L., Gelich, A., Ras, Z.W. (2020). Applying Analytics to Artist Provided Text to Model Prices of Fine Art. In: Appice, A., Ceci, M., Loglisci, C., Manco, G., Masciari, E., Ras, Z. (eds) Complex Pattern Mining. Studies in Computational Intelligence, vol 880. Springer, Cham. https://doi.org/10.1007/978-3-030-36617-9_12

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