IDEAS home Printed from https://ideas.repec.org/a/gam/jjopen/v8y2025i4p40-d1770519.html

Modeling the Mutual Dynamic Correlations of Words in Written Texts Using Multivariate Hawkes Processes

Author

Listed:
  • Hiroshi Ogura

    (Faculty of Arts and Sciences at FUJIYOSHIDA, Showa Medical University, 4562 Kamiyoshida, Fujiyoshida-shi 403-0005, Japan)

  • Yasutaka Hanada

    (Faculty of Arts and Sciences at FUJIYOSHIDA, Showa Medical University, 4562 Kamiyoshida, Fujiyoshida-shi 403-0005, Japan)

  • Keitaro Osakabe

    (Faculty of Arts and Sciences at FUJIYOSHIDA, Showa Medical University, 4562 Kamiyoshida, Fujiyoshida-shi 403-0005, Japan)

  • Masato Kondo

    (Faculty of Arts and Sciences at FUJIYOSHIDA, Showa Medical University, 4562 Kamiyoshida, Fujiyoshida-shi 403-0005, Japan)

Abstract

The occurrence patterns of important words found in six texts (one historical pamphlet and five renowned academic books) are analyzed using both univariate and multivariate Hawkes processes. By treating the occurrence patterns as binary time-series data along the texts, we investigate how effectively univariate and multivariate Hawkes processes capture the characteristics of these word occurrence signals. Through maximum likelihood estimation and subsequent simulations, we found that the multivariate Hawkes process clearly outperforms the univariate Hawkes process in modeling word occurrence signals. Moreover, we found that the multivariate Hawkes process can provide a Hawkes graph, which serves as an intuitive representation of the relationships between concepts appearing in the analyzed text. Furthermore, our study demonstrates that the importance of concepts within a given text can be quantitatively estimated based on the optimized parameter values of the multivariate Hawkes process.

Suggested Citation

  • Hiroshi Ogura & Yasutaka Hanada & Keitaro Osakabe & Masato Kondo, 2025. "Modeling the Mutual Dynamic Correlations of Words in Written Texts Using Multivariate Hawkes Processes," J, MDPI, vol. 8(4), pages 1-26, October.
    • Handle: RePEc:gam:jjopen:v:8:y:2025:i:4:p:40-:d:1770519
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-8800/8/4/40/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2571-8800/8/4/40/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chatzigeorgiou, M. & Constantoudis, V. & Diakonos, F. & Karamanos, K. & Papadimitriou, C. & Kalimeri, M. & Papageorgiou, H., 2017. "Multifractal correlations in natural language written texts: Effects of language family and long word statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 173-182.
    2. Bowsher, Clive G., 2007. "Modelling security market events in continuous time: Intensity based, multivariate point process models," Journal of Econometrics, Elsevier, vol. 141(2), pages 876-912, December.
    3. Steve Y. Yang & Anqi Liu & Jing Chen & Alan Hawkes, 2018. "Applications of a multivariate Hawkes process to joint modeling of sentiment and market return events," Quantitative Finance, Taylor & Francis Journals, vol. 18(2), pages 295-310, February.
    Full references (including those not matched with items on IDEAS)

    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. Jing Chen, 2025. "Editorial A Tribute to Professor Geoffrey Alan Hawkes (19 September 1938–9 November 2023)," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 30(1), pages 1-7, March.
    2. Jiwook Jang & Rosy Oh, 2020. "A Bivariate Compound Dynamic Contagion Process for Cyber Insurance," Papers 2007.04758, arXiv.org.
    3. Rachele Foschi & Francesca Lilla & Cecilia Mancini, 2020. "Warnings about future jumps: properties of the exponential Hawkes model," Working Papers 13/2020, University of Verona, Department of Economics.
    4. Qi Guo & Bruno Remillard & Anatoliy Swishchuk, 2020. "Multivariate General Compound Point Processes in Limit Order Books," Risks, MDPI, vol. 8(3), pages 1-20, September.
    5. Pierre Perron & Eduardo Zorita & Wen Cao & Clifford Hurvich & Philippe Soulier, 2017. "Drift in Transaction-Level Asset Price Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 769-790, September.
    6. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," LIDAM Discussion Papers CORE 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. repec:wyi:journl:002211 is not listed on IDEAS
    8. Kyungsub Lee, 2022. "Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures," Papers 2207.05939, arXiv.org, revised Sep 2024.
    9. Ioane Muni Toke & Nakahiro Yoshida, 2020. "Marked point processes and intensity ratios for limit order book modeling," Papers 2001.08442, arXiv.org.
    10. Anatoliy Swishchuk & Aiden Huffman, 2020. "General Compound Hawkes Processes in Limit Order Books," Risks, MDPI, vol. 8(1), pages 1-25, March.
    11. Ban Zheng & François Roueff & Frédéric Abergel, 2014. "Ergodicity and scaling limit of a constrained multivariate Hawkes process," Post-Print hal-00777941, HAL.
    12. Steffen Volkenand & Günther Filler & Martin Odening, 2020. "Price Discovery and Market Reflexivity in Agricultural Futures Contracts with Different Maturities," Risks, MDPI, vol. 8(3), pages 1-17, July.
    13. Ivan Jericevich & Patrick Chang & Tim Gebbie, 2021. "Simulation and estimation of a point-process market-model with a matching engine," Papers 2105.02211, arXiv.org, revised Aug 2021.
    14. Massil Achab & Emmanuel Bacry & Jean-Franc{c}ois Muzy & Marcello Rambaldi, 2017. "Analysis of order book flows using a nonparametric estimation of the branching ratio matrix," Papers 1706.03411, arXiv.org.
    15. Dassios, Angelos & Zhao, Hongbiao, 2013. "Exact simulation of Hawkes process with exponentially decaying intensity," LSE Research Online Documents on Economics 51370, London School of Economics and Political Science, LSE Library.
    16. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
    17. Thibault Jaisson, 2014. "Market impact as anticipation of the order flow imbalance," Papers 1402.1288, arXiv.org.
    18. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Marked Hawkes process modeling of price dynamics and volatility estimation," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 174-200.
    19. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    20. Boswijk, H. Peter & Laeven, Roger J.A. & Yang, Xiye, 2018. "Testing for self-excitation in jumps," Journal of Econometrics, Elsevier, vol. 203(2), pages 256-266.
    21. Mariko I Ito & Yudai Honma & Takaaki Ohnishi & Tsutomu Watanabe & Kazuyuki Aihara, 2024. "Exogenous and endogenous factors affecting stock market transactions: A Hawkes process analysis of the Tokyo Stock Exchange during the COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 19(4), pages 1-23, April.

    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:gam:jjopen:v:8:y:2025:i:4:p:40-:d:1770519. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.