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Succinct effect or informative effect: the relationship between title length and the number of citations

Author

Listed:
  • Feng Guo

    (Shanghai University of Finance and Economics)

  • Chao Ma

    (Southeast University
    Yale University)

  • Qingling Shi

    (East China Normal University
    East China Normal University)

  • Qingqing Zong

    (Shanghai University of Finance and Economics)

Abstract

Previous studies produced mixed results with respect to the correlation between title length and number of citations. This research aims to provide a new explanation for this controversy by examining one of the largest pools of papers to date, containing over 300,000 economics papers spanning a much longer time period (1956–2012). The results show that correlation between title length and the number of citations is negative between 1956 and 2000, but becomes positive after 2000, when online searches became the predominant method for literature retrieval. Moreover, heterogeneity analyses show that longer titles are especially crucial for papers with relatively lower influence, which researchers can typically only access using online searches.

Suggested Citation

  • Feng Guo & Chao Ma & Qingling Shi & Qingqing Zong, 2018. "Succinct effect or informative effect: the relationship between title length and the number of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1531-1539, September.
    • Handle: RePEc:spr:scient:v:116:y:2018:i:3:d:10.1007_s11192-018-2805-8
    DOI: 10.1007/s11192-018-2805-8
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    References listed on IDEAS

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    Cited by:

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    2. Bornmann, Lutz & Haunschild, Robin & Mutz, Rüdiger, 2020. "Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 14(4).
    3. Ma, Chao & Li, Yiwei & Guo, Feng & Si, Kao, 2019. "The citation trap: Papers published at year-end receive systematically fewer citations," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 667-687.
    4. Ha, Taehyun, 2022. "An explainable artificial-intelligence-based approach to investigating factors that influence the citation of papers," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
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    7. Claudia N. Gonzalez Brambila & José I. Ponce & Silvia B. Gonzalez Brambila & Matias F. Milia, 2023. "Determining the Characteristics of Papers That Garner the Most Significant Impact: A Deep Dive into Mexican Engineering Publications," Publications, MDPI, vol. 11(4), pages 1-14, September.
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    10. Syed Hasan & Robert Breunig, 2021. "Article length and citation outcomes," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7583-7608, September.
    11. Martorell Cunil, Onofre & Otero González, Luis & Durán Santomil, Pablo & Mulet Forteza, Carlos, 2023. "How to accomplish a highly cited paper in the tourism, leisure and hospitality field," Journal of Business Research, Elsevier, vol. 157(C).
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    13. Brady D. Lund & Sanjay Kumar Maurya, 2020. "The relationship between highly-cited papers and the frequency of citations to other papers within-issue among three top information science journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2491-2504, December.
    14. Sergio Jimenez & Youlin Avila & George Dueñas & Alexander Gelbukh, 2020. "Automatic prediction of citability of scientific articles by stylometry of their titles and abstracts," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 3187-3232, December.
    15. Kong, Ling & Wang, Dongbo, 2020. "Comparison of citations and attention of cover and non-cover papers," Journal of Informetrics, Elsevier, vol. 14(4).
    16. Nicole Heßler & Andreas Ziegler, 2022. "Evidence-based recommendations for increasing the citation frequency of original articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3367-3381, June.
    17. Chunli Wei & Jingyi Zhao & Jue Ni & Jiang Li, 2023. "What does open peer review bring to scientific articles? Evidence from PLoS journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2763-2776, May.
    18. Sepideh Fahimifar & Khadijeh Mousavi & Fatemeh Mozaffari & Marcel Ausloos, 2023. "Identification of the most important external features of highly cited scholarly papers through 3 (i.e., Ridge, Lasso, and Boruta) feature selection data mining methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3685-3712, August.
    19. Hou, Li & Wu, Qiang & Xie, Yundong, 2024. "Does open identity of peer reviewers positively relate to citations?," Journal of Informetrics, Elsevier, vol. 18(1).
    20. Lu, Wei & Liu, Zhifeng & Huang, Yong & Bu, Yi & Li, Xin & Cheng, Qikai, 2020. "How do authors select keywords? A preliminary study of author keyword selection behavior," Journal of Informetrics, Elsevier, vol. 14(4).
    21. T. Liskiewicz & G. Liskiewicz & J. Paczesny, 2021. "Factors affecting the citations of papers in tribology journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3321-3336, April.

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    More about this item

    Keywords

    Citation; Title; Search; Scholarly impact;
    All these keywords.

    JEL classification:

    • A2 - General Economics and Teaching - - Economic Education and Teaching of Economics
    • Z1 - Other Special Topics - - Cultural Economics

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