The advantage of simple paper abstracts

Article English OPEN
Letchford, Adrian ; Preis, Tobias ; Moat, Helen Susannah (2015)
  • Publisher: Elsevier BV
  • Journal: Journal of Informetrics, volume 10, issue 1, pages 1-8 (issn: 1751-1577)
  • Related identifiers: doi: 10.1016/j.joi.2015.11.001, doi: 10.1016/j.joi.2015.11.001
  • Subject: Applied Mathematics | Computer Science Applications | Statistics and Probability | Modelling and Simulation | Management Science and Operations Research | T1

Each year, researchers publish an immense number of scientific papers. While some receive many citations, others receive none. Here we investigate whether any of this variance can be explained by the choice of words in a paper's abstract. We find that doubling the word frequency of an average abstract increases citations by 0.70%. We also find that journals which publish papers whose abstracts are shorter and contain more frequently used words receive slightly more citations per paper. Specifically, adding a 5 letter word to an abstract decreases the number of citations by 0.02%. These results are consistent with the hypothesis that the style in which a paper's abstract is written bears some relation to its scientific impact.\ud
  • References (45)
    45 references, page 1 of 5

    Google Ngram Viewer. URL: http://storage.googleapis.com/books/ngrams/books/datasetsv2.html. 2012.

    Acuna, D. E., Allesina, S., & Kording, K. P. (2012). Future impact: Predicting scientific success. Nature, 489, 201-202.

    Alanyali, M., Moat, H. S., & Preis, T. (2013). Quantifying the relationship between financial news and the stock market. Scientific Reports, 3, 3578.

    Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8.

    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, 5(4), 608-617.

    Ciulla, F., Mocanu, D., Baronchelli, A., Gon c¸alves, B., Perra, N., & Vespignani, A. (2012). Beating the news using social media: The case study of American Idol. European Physical Journal Data Science, 1, 8.

    Conte, R., Gilbert, N., Bonelli, G., Cioffi-Revilla, C., Deffuant, G., Kertész, J., Loreto, V., Moat, S., Nadal, J. P., Sanchez, A., Nowak, A., Flache, A., San Miguel, M., & Helbing, D. (2012). Manifesto of computational social science. European Physical Journal Special Topics, 214(1), 325-346.

    Curme, C., Preis, T., Stanley, H. E., & Moat, H. S. (2014). Quantifying the semantics of search behavior before stock market moves. Proceedings of the National Academy of Sciences of the United States of America, 111(32), 11600-11605.

    van Dijk, D., Manor, O., & Carey, L. B. (2014). Publication metrics and success on the academic job market. Current Biology, 24(11), R516-R517.

    Falagas, M. E., Zarkali, A., Karageorgopoulos, D. E., Bardakas, V., & Mavros, M. N. (2013). The Impact of Article Length on the Number of Future Citations: A Bibliometric Analysis of General Medicine Journals. PLOS ONE, 8(2), e49476.

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