IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v116y2018i2d10.1007_s11192-018-2789-4.html
   My bibliography  Save this article

Detecting automatically generated sentences with grammatical structure similarity

Author

Listed:
  • Nguyen Minh Tien

    (Univ. Grenoble Alpes)

  • Cyril Labbé

    (Univ. Grenoble Alpes)

Abstract

Automatically generated papers have been used to manipulate bibliography indexes on numerous occasions. This paper is interested in different means to generate texts such as recurrent neural network, Markov model, or probabilistic context free grammar, and if it is possible to detect them using a current approach. Then, probabilistic context free grammar (PCFG) is focused on as the one most used. However, even though there have been multiple approaches to detect such types of paper, they are all working at the document level and are unable to detect a small amount of generated text inside a larger body of genuinely written text. Thus, we present the grammatical structure similarity measurement to detect sentences or short fragments of automatically generated text from known PCFG generators. The proposed approach is tested against a pattern checker and various common machine learning methods. Additionally, the ability to detect a modified PCFG generator is also tested.

Suggested Citation

  • Nguyen Minh Tien & Cyril Labbé, 2018. "Detecting automatically generated sentences with grammatical structure similarity," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1247-1271, August.
    • Handle: RePEc:spr:scient:v:116:y:2018:i:2:d:10.1007_s11192-018-2789-4
    DOI: 10.1007/s11192-018-2789-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-018-2789-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-018-2789-4?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Diego Raphael Amancio, 2015. "A Complex Network Approach to Stylometry," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-21, August.
    2. Diego Raphael Amancio, 2015. "Comparing the topological properties of real and artificially generated scientific manuscripts," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1763-1779, December.
    3. Amancio, Diego R. & Oliveira Jr., Osvaldo N. & Costa, Luciano da F., 2012. "Structure–semantics interplay in complex networks and its effects on the predictability of similarity in texts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4406-4419.
    4. Diego Raphael Amancio & Cesar Henrique Comin & Dalcimar Casanova & Gonzalo Travieso & Odemir Martinez Bruno & Francisco Aparecido Rodrigues & Luciano da Fontoura Costa, 2014. "A Systematic Comparison of Supervised Classifiers," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
    5. Paul Ginsparg, 2014. "ArXiv screens spot fake papers," Nature, Nature, vol. 508(7494), pages 44-44, April.
    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. Guillaume Cabanac & Ingo Frommholz & Philipp Mayr, 2018. "Bibliometric-enhanced information retrieval: preface," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1225-1227, August.
    2. Tingting Zhang & Baozhen Lee & Qinghua Zhu, 2019. "Semantic measure of plagiarism using a hierarchical graph model," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 209-239, October.

    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. Tohalino, Jorge V. & Amancio, Diego R., 2018. "Extractive multi-document summarization using multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 526-539.
    2. Dejian Yu & Wanru Wang & Shuai Zhang & Wenyu Zhang & Rongyu Liu, 2017. "Hybrid self-optimized clustering model based on citation links and textual features to detect research topics," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-21, October.
    3. 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.
    4. Ferraz de Arruda, Henrique & Reia, Sandro Martinelli & Silva, Filipi Nascimento & Amancio, Diego Raphael & da Fontoura Costa, Luciano, 2022. "Finding contrasting patterns in rhythmic properties between prose and poetry," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    5. Guillaume Cabanac & Cyril Labbé, 2021. "Prevalence of nonsensical algorithmically generated papers in the scientific literature," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(12), pages 1461-1476, December.
    6. Jennifer A. Byrne & Cyril Labbé, 2017. "Striking similarities between publications from China describing single gene knockdown experiments in human cancer cell lines," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1471-1493, March.
    7. de Arruda, Henrique F. & Marinho, Vanessa Q. & Lima, Thales S. & Amancio, Diego R. & Costa, Luciano da F., 2018. "An image analysis approach to text analytics based on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 110-120.
    8. Woon Peng Goh & Kang-Kwong Luke & Siew Ann Cheong, 2018. "Functional shortcuts in language co-occurrence networks," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-18, September.
    9. Diego Raphael Amancio, 2015. "Comparing the topological properties of real and artificially generated scientific manuscripts," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1763-1779, December.
    10. Silva, Filipi N. & Amancio, Diego R. & Bardosova, Maria & Costa, Luciano da F. & Oliveira, Osvaldo N., 2016. "Using network science and text analytics to produce surveys in a scientific topic," Journal of Informetrics, Elsevier, vol. 10(2), pages 487-502.
    11. Corrêa, Edilson A. & Marinho, Vanessa Q. & Amancio, Diego R., 2020. "Semantic flow in language networks discriminates texts by genre and publication date," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    12. Priscila T M Saito & Rodrigo Y M Nakamura & Willian P Amorim & João P Papa & Pedro J de Rezende & Alexandre X Falcão, 2015. "Choosing the Most Effective Pattern Classification Model under Learning-Time Constraint," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-23, June.
    13. Diego R Amancio, 2015. "Probing the Topological Properties of Complex Networks Modeling Short Written Texts," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-17, February.
    14. Mariane Barros Neiva & Patrick Guidotti & Odemir Martinez Bruno, 2018. "Enhancing LBP by preprocessing via anisotropic diffusion," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 29(08), pages 1-29, August.
    15. Adilson Vital & Diego R. Amancio, 2022. "A comparative analysis of local similarity metrics and machine learning approaches: application to link prediction in author citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(10), pages 6011-6028, October.
    16. Yin, Likang & Deng, Yong, 2018. "Toward uncertainty of weighted networks: An entropy-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 176-186.
    17. de Arruda, Henrique F. & Silva, Filipi N. & Comin, Cesar H. & Amancio, Diego R. & Costa, Luciano da F., 2019. "Connecting network science and information theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 641-648.
    18. Brito, Ana C.M. & Silva, Filipi N. & de Arruda, Henrique F. & Comin, Cesar H. & Amancio, Diego R. & Costa, Luciano da F., 2021. "Classification of abrupt changes along viewing profiles of scientific articles," Journal of Informetrics, Elsevier, vol. 15(2).
    19. Akimushkin, Camilo & Amancio, Diego R. & Oliveira, Osvaldo N., 2018. "On the role of words in the network structure of texts: Application to authorship attribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 49-58.
    20. Diego R. Amancio & Osvaldo N. Oliveira jr & Luciano F. Costa, 2015. "Topological-collaborative approach for disambiguating authors’ names in collaborative networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 465-485, January.

    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:spr:scient:v:116:y:2018:i:2:d:10.1007_s11192-018-2789-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.