IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v10y2016i1p1-8.html
   My bibliography  Save this article

The advantage of simple paper abstracts

Author

Listed:
  • Letchford, Adrian
  • Preis, Tobias
  • Moat, Helen Susannah

Abstract

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.

Suggested Citation

  • Letchford, Adrian & Preis, Tobias & Moat, Helen Susannah, 2016. "The advantage of simple paper abstracts," Journal of Informetrics, Elsevier, vol. 10(1), pages 1-8.
    • Handle: RePEc:eee:infome:v:10:y:2016:i:1:p:1-8
    DOI: 10.1016/j.joi.2015.11.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157715300766
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2015.11.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Matthew E Falagas & Angeliki Zarkali & Drosos E Karageorgopoulos & Vangelis Bardakas & Michael N Mavros, 2013. "The Impact of Article Length on the Number of Future Citations: A Bibliometric Analysis of General Medicine Journals," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-8, February.
    2. Delia Mocanu & Andrea Baronchelli & Nicola Perra & Bruno Gonçalves & Qian Zhang & Alessandro Vespignani, 2013. "The Twitter of Babel: Mapping World Languages through Microblogging Platforms," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
    3. Márton Mestyán & Taha Yasseri & János Kertész, 2013. "Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    4. Hamid R. Jamali & Mahsa Nikzad, 2011. "Article title type and its relation with the number of downloads and citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 653-661, August.
    5. Duncan J. Watts, 2007. "A twenty-first century science," Nature, Nature, vol. 445(7127), pages 489-489, February.
    6. Daniel E. Acuna & Stefano Allesina & Konrad P. Kording, 2012. "Predicting scientific success," Nature, Nature, vol. 489(7415), pages 201-202, September.
    7. 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.
    8. Petersen, Alexander M. & Succi, Sauro, 2013. "The Z-index: A geometric representation of productivity and impact which accounts for information in the entire rank-citation profile," Journal of Informetrics, Elsevier, vol. 7(4), pages 823-832.
    9. Taha Yasseri & Robert Sumi & András Rung & András Kornai & János Kertész, 2012. "Dynamics of Conflicts in Wikipedia," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-12, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guan, Jiancheng & Yan, Yan & Zhang, Jing Jing, 2017. "The impact of collaboration and knowledge networks on citations," Journal of Informetrics, Elsevier, vol. 11(2), pages 407-422.
    2. JingJing Zhang & Jiancheng Guan, 2017. "Scientific relatedness and intellectual base: a citation analysis of un-cited and highly-cited papers in the solar energy field," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 141-162, January.
    3. Yan Yan & Shanwu Tian & Jingjing Zhang, 2020. "The impact of a paper’s new combinations and new components on its citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 895-913, February.
    4. Andrea Fronzetti Colladon & Ciriaco Andrea D’Angelo & Peter A. Gloor, 2020. "Predicting the future success of scientific publications through social network and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 357-377, July.
    5. Stefano Mammola & Elena Piano & Alberto Doretto & Enrico Caprio & Dan Chamberlain, 2022. "Measuring the influence of non-scientific features on citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4123-4137, July.
    6. Uddin, Shahadat & Khan, Arif, 2016. "The impact of author-selected keywords on citation counts," Journal of Informetrics, Elsevier, vol. 10(4), pages 1166-1177.
    7. Stefano Mammola & Diego Fontaneto & Alejandro Martínez & Filipe Chichorro, 2021. "Impact of the reference list features on the number of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 785-799, January.
    8. Naomi Moy & Ho Fai Chan & Benno Torgler, 2018. "How much is too much? The effects of information quantity on crowdfunding performance," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-15, March.
    9. Chan, Ho Fai & Bodiuzzman, Sohel Md & Torgler, Benno, 2020. "The power of social cues in the battle for attention: Evidence from an online platform for scholarly commentary," Journal of Informetrics, Elsevier, vol. 14(4).
    10. Kayvan Kousha & Mike Thelwall, 2024. "Factors associating with or predicting more cited or higher quality journal articles: An Annual Review of Information Science and Technology (ARIST) paper," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 75(3), pages 215-244, March.
    11. Jorge A. V. Tohalino & Laura V. C. Quispe & Diego R. Amancio, 2021. "Analyzing the relationship between text features and grants productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4255-4275, May.
    12. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    13. Peng, Wen & Yue, Mingliang & Sun, Mingyue & Ma, Tingcan, 2024. "Revision and academic impact: A case study of bioRxiv preprint papers," Journal of Informetrics, Elsevier, vol. 18(1).
    14. Tohalino, Jorge A.V. & Amancio, Diego R., 2022. "On predicting research grants productivity via machine learning," Journal of Informetrics, Elsevier, vol. 16(2).
    15. Anqi Ma & Yu Liu & Xiujuan Xu & Tao Dong, 2021. "A deep-learning based citation count prediction model with paper metadata semantic features," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6803-6823, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. Maxime Lenormand & Miguel Picornell & Oliva G Cantú-Ros & Antònia Tugores & Thomas Louail & Ricardo Herranz & Marc Barthelemy & Enrique Frías-Martínez & José J Ramasco, 2014. "Cross-Checking Different Sources of Mobility Information," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    5. Kong, Ling & Wang, Dongbo, 2020. "Comparison of citations and attention of cover and non-cover papers," Journal of Informetrics, Elsevier, vol. 14(4).
    6. Daniele Barchiesi & Helen Susannah Moat & Christian Alis & Steven Bishop & Tobias Preis, 2015. "Quantifying International Travel Flows Using Flickr," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-8, July.
    7. Lutz Bornmann & Klaus Wohlrabe, 2025. "Pattern, Perception, and Performance: Tripartite Phrases in Academic Paper Titles," CESifo Working Paper Series 11671, CESifo.
    8. Bramoullé, Yann & Ductor, Lorenzo, 2018. "Title length," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 311-324.
    9. Shota Saito & Yoshito Hirata & Kazutoshi Sasahara & Hideyuki Suzuki, 2015. "Tracking Time Evolution of Collective Attention Clusters in Twitter: Time Evolving Nonnegative Matrix Factorisation," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-17, September.
    10. Sato, Ryoma & Yamada, Makoto & Kashima, Hisashi, 2022. "Poincare: Recommending Publication Venues via Treatment Effect Estimation," Journal of Informetrics, Elsevier, vol. 16(2).
    11. James Hartley, 2015. "Inaccuracies in titles," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 329-330, April.
    12. Jiawei Wang, 2024. "Quantifying cohesion in high citation research article titles: a cross-disciplinary and diachronic investigation," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(9), pages 5075-5102, September.
    13. William S. Pearson, 2021. "Quoted speech in linguistics research article titles: patterns of use and effects on citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3421-3442, April.
    14. Dehu Yin & Xi Zhang & Hongke Zhao & Li Tang, 2024. "Predicting scholar potential: a deep learning model on social capital features," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(12), pages 7851-7879, December.
    15. Gianna Kexin Jiang & Yajun Jiang, 2023. "More diversity, more complexity, but more flexibility: research article titles in TESOL Quarterly, 1967–2022," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 3959-3980, July.
    16. 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.
    17. Zahedi, Zohreh & Haustein, Stefanie, 2018. "On the relationships between bibliographic characteristics of scientific documents and citation and Mendeley readership counts: A large-scale analysis of Web of Science publications," Journal of Informetrics, Elsevier, vol. 12(1), pages 191-202.
    18. 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).
    19. William S. Pearson, 2020. "Research article titles in written feedback on English as a second language writing," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 997-1019, May.
    20. Huu Dat Tran & Pham Phuong Uyen Diep & Nabila Mushtarin, 2024. "“Insert witty catchphrase here!”: do title elements influence engagement and citation?— examining highly-cited research articles in media, communication, and related disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 6675-6691, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:infome:v:10:y:2016:i:1:p:1-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.