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Citations and the readers’ information-extracting costs of finance articles

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Listed:
  • Berninger, Marc
  • Kiesel, Florian
  • Schiereck, Dirk
  • Gaar, Eduard

Abstract

This paper focuses on the relationship between the reader's information-extracting costs of finance articles and the article's number of citations. The reader's information-extracting costs are measured using three metrics: (i) the Flesch-Kincaid readability score, (ii) the article's length, and (iii) the number of complex words. Based on a sample of more than 14,000 full text articles published between 2000 and 2016 in 16 finance journals, we show that the information-extracting costs of finance journals have significantly increased over time, while the topics of these articles, determined by machine-learning topic modeling, remained relatively constant. We find a positive correlation between the reader's information-extracting costs and the number of citations achieved by a paper for articles that are published in the top-three finance journals (JF, JFE, RFS), but do not observe this pattern for articles published in other major finance journals.

Suggested Citation

  • Berninger, Marc & Kiesel, Florian & Schiereck, Dirk & Gaar, Eduard, 2021. "Citations and the readers’ information-extracting costs of finance articles," Journal of Banking & Finance, Elsevier, vol. 131(C).
    • Handle: RePEc:eee:jbfina:v:131:y:2021:i:c:s0378426621001473
    DOI: 10.1016/j.jbankfin.2021.106188
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    More about this item

    Keywords

    Information extracting costs; Readability; Textual analysis; Finance literature; Machine learning; Scientometrics;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G00 - Financial Economics - - General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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