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An Investigation of the Impact of Data Breach Severity on the Readability of Mandatory Data Breach Notification Letters: Evidence From U.S. Firms

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  • Stephen Jackson
  • Nadia Vanteeva
  • Colm Fearon

Abstract

The aim of this article is to investigate the impact of data breach severity on the readability of mandatory data breach notification letters. Using a content analysis approach to determine data breach severity attributes (measured by the total number of breached records, type of data accessed, the source of the data breach, and how the data were used), in conjunction with readability measures (reading complexity, numerical intensity, length of letter, word size, and unique words), 512 data breach incidents from 281 U.S. firms across the 2012–2015 period were examined. The results indicate that data breach severity has a positive impact on reading complexity, length of letter, word size, and unique words, and a negative impact on numerical terms. Interpreting the results collectively through the lens of impression management, it can be inferred that business managers may be attempting to obfuscate bad news associated with high data breach severity incidents by manipulating syntactical features of the data breach notification letters in a way that makes the message difficult for individuals to comprehend. The study contributes to the information studies and impression management behavior literatures by analyzing linguistic cues in notifications following a data breach incident.

Suggested Citation

  • Stephen Jackson & Nadia Vanteeva & Colm Fearon, 2019. "An Investigation of the Impact of Data Breach Severity on the Readability of Mandatory Data Breach Notification Letters: Evidence From U.S. Firms," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(11), pages 1277-1289, November.
    • Handle: RePEc:bla:jinfst:v:70:y:2019:i:11:p:1277-1289
    DOI: 10.1002/asi.24188
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    Cited by:

    1. Wang, Xing, 2024. "The misuse of the nonlinear field normalization method: Nonlinear field normalization citation counts at the paper level should not be added or averaged," Journal of Informetrics, Elsevier, vol. 18(3).
    2. Sarel, Roee & Demirtas, Melanie, 2021. "Delegation in a multi-tier court system: Are remands in the U.S. federal courts driven by moral hazard?," European Journal of Political Economy, Elsevier, vol. 68(C).

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