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Non-alphanumeric characters in titles of scientific publications: An analysis of their occurrence and correlation with citation impact

Author

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  • Buter, R.K.
  • van Raan, A.F.J.

Abstract

We investigated the occurrence of non-alphanumeric characters in a randomized subset of over almost 650,000 titles of scientific publications from the Web of Science database. Additionally, for almost 500,000 of these publications we correlated occurrence with impact, using the field-normalised citation metric CPP/FCSm. We compared occurrence and correlation with impact both at in general and for specific disciplines and took into account the variation within sets by (non-parametrically) bootstrapping the calculation of impact values. We also compared use and impact of individual characters in the 30 fields in which non-alphanumeric characters occur most frequently, by using heatmaps that clustered and reordered fields and characters. We conclude that the use of some non-alphanumeric characters, such as the hyphen and colon, is common in most titles and that not including such characters generally correlates negatively with impact. Specific disciplines on the other hand, may show either a negative, absent, or positive correlation. We also found that thematically related science fields use non-alphanumeric characters in comparable numbers, but that impact associated with such characters shows a less strong thematic relation. Overall, it appears that authors cannot influence success of publications by including non-alphanumeric characters in fields where this is not already commonplace.

Suggested Citation

  • Buter, R.K. & van Raan, A.F.J., 2011. "Non-alphanumeric characters in titles of scientific publications: An analysis of their occurrence and correlation with citation impact," Journal of Informetrics, Elsevier, vol. 5(4), pages 608-617.
  • Handle: RePEc:eee:infome:v:5:y:2011:i:4:p:608-617 DOI: 10.1016/j.joi.2011.05.008
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    References listed on IDEAS

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    1. van Eck, N.J.P. & Waltman, L., 2008. "Generalizing the h- and g-indices," ERIM Report Series Research in Management ERS-2008-049-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
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    5. Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
    6. Kuan, Chung-Huei & Huang, Mu-Hsuan & Chen, Dar-Zen, 2011. "Ranking patent assignee performance by h-index and shape descriptors," Journal of Informetrics, Elsevier, vol. 5(2), pages 303-312.
    7. Cabrerizo, F.J. & Alonso, S. & Herrera-Viedma, E. & Herrera, F., 2010. "q2-Index: Quantitative and qualitative evaluation based on the number and impact of papers in the Hirsch core," Journal of Informetrics, Elsevier, vol. 4(1), pages 23-28.
    8. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2010. "The h index research output measurement: Two approaches to enhance its accuracy," Journal of Informetrics, Elsevier, vol. 4(3), pages 407-414.
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    Citations

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    Cited by:

    1. Lakshmi Balachandran Nair & Michael Gibbert, 2016. "What makes a ‘good’ title and (how) does it matter for citations? A review and general model of article title attributes in management science," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1331-1359, June.
    2. Ruiz-Castillo, Javier & Costas, Rodrigo, 2014. "The skewness of scientific productivity," Journal of Informetrics, Elsevier, vol. 8(4), pages 917-934.
    3. Iman Tahamtan & Askar Safipour Afshar & Khadijeh Ahamdzadeh, 2016. "Factors affecting number of citations: a comprehensive review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1195-1225, June.
    4. Ajiferuke, Isola & Famoye, Felix, 2015. "Modelling count response variables in informetric studies: Comparison among count, linear, and lognormal regression models," Journal of Informetrics, Elsevier, vol. 9(3), pages 499-513.
    5. repec:spr:scient:v:103:y:2015:i:1:d:10.1007_s11192-015-1530-9 is not listed on IDEAS
    6. Matthias Gnewuch & Klaus Wohlrabe, 2017. "Title characteristics and citations in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1573-1578, March.
    7. Uddin, Shahadat & Khan, Arif, 2016. "The impact of author-selected keywords on citation counts," Journal of Informetrics, Elsevier, vol. 10(4), pages 1166-1177.
    8. Letchford, Adrian & Preis, Tobias & Moat, Helen Susannah, 2016. "The advantage of simple paper abstracts," Journal of Informetrics, Elsevier, vol. 10(1), pages 1-8.
    9. repec:spr:scient:v:103:y:2015:i:3:d:10.1007_s11192-015-1562-1 is not listed on IDEAS
    10. Mike Thelwall, 2017. "Avoiding obscure topics and generalising findings produces higher impact research," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 307-320, January.
    11. James M. Cook & Dawn Plourde, 2016. "Do scholars follow Betteridge’s Law? The use of questions in journal article titles," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1119-1128, September.

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