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Age Ain’t Just a Number: Exploring the Volume vs. Age Dilemma for Textual Data to Enhance Decision Making

In: Artificial Intelligence, Data, and Decision-Making

Author

Listed:
  • Lukas Hägele

    (Institute of Businesss Analytics, University of Ulm)

  • Mathias Klier

    (Institute of Businesss Analytics, University of Ulm)

  • Andreas Obermeier

    (Institute of Businesss Analytics, University of Ulm)

  • Torben Widmann

    (Institute of Businesss Analytics, University of Ulm)

Abstract

The common belief that more data leads to better results often leads to all available data being used to derive the best possible decision. However, the age of data can strongly affect data-driven decision making. Consequently, the desire for larger data volume and at the same time contemporary data leads to the “volume vs. age” dilemma, which has not yet been sufficiently researched. In this work, we rigorously investigate the “volume vs. age” dilemma for textual data using four experiments with real-world data containing customer reviews from the Yelp platform. Contributing to theory and practice, we show that more data is not always better, as the effect of data age can outweigh the effect of data volume, resulting in overall poorer performance. Moreover, we demonstrate that different aspects within textual data can exhibit different temporal effects and that considering these effects when selecting training data can clearly outperform existing practices.

Suggested Citation

  • Lukas Hägele & Mathias Klier & Andreas Obermeier & Torben Widmann, 2026. "Age Ain’t Just a Number: Exploring the Volume vs. Age Dilemma for Textual Data to Enhance Decision Making," Lecture Notes in Information Systems and Organization, in: Christoph M. Flath & Gunther Gust & Frédéric Thiesse & Axel Winkelmann (ed.), Artificial Intelligence, Data, and Decision-Making, pages 293-310, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-08480-4_19
    DOI: 10.1007/978-3-032-08480-4_19
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