IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v404y2014icp142-149.html
   My bibliography  Save this article

Model for Twitter dynamics: Public attention and time series of tweeting

Author

Listed:
  • Ko, J.
  • Kwon, H.W.
  • Kim, H.S.
  • Lee, K.
  • Choi, M.Y.

Abstract

We present a simple mathematical model for the Twitter dynamics, and use the model to extract the information-sharing tendencies on two time scales, day and hour, about three contenders in the 2012 presidential election in South Korea. Comparison of the model results with actual data demonstrates that the information-sharing tendency on the day scale provides a good measure for the general public attention to the contenders, whereas the tendency on the hour scale reflects the daily cycle of twitter users. In addition, it is attempted to reproduce the time evolution of tweeting by taking the numbers of the articles on the online newspapers as the external driving to tweet, the validity of which is discussed.

Suggested Citation

  • Ko, J. & Kwon, H.W. & Kim, H.S. & Lee, K. & Choi, M.Y., 2014. "Model for Twitter dynamics: Public attention and time series of tweeting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 142-149.
    • Handle: RePEc:eee:phsmap:v:404:y:2014:i:c:p:142-149
    DOI: 10.1016/j.physa.2014.02.034
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437114001435
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2014.02.034?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. Bernard J. Jansen & Mimi Zhang & Kate Sobel & Abdur Chowdury, 2009. "Twitter power: Tweets as electronic word of mouth," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(11), pages 2169-2188, November.
    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. Yao, Weiyi & Jiao, Pengfei & Wang, Wenjun & Sun, Yueheng, 2019. "Understanding human reposting patterns on Sina Weibo from a global perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 374-383.
    2. Skaza, Jonathan & Blais, Brian, 2017. "Modeling the infectiousness of Twitter hashtags," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 289-296.
    3. Georgios Magkonis & Karen Jackson, 2019. "Identifying Networks in Social Media: The case of #Grexit," Networks and Spatial Economics, Springer, vol. 19(1), pages 319-330, March.

    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. Smith, Andrew N. & Fischer, Eileen & Yongjian, Chen, 2012. "How Does Brand-related User-generated Content Differ across YouTube, Facebook, and Twitter?," Journal of Interactive Marketing, Elsevier, vol. 26(2), pages 102-113.
    2. Xuan Yang & Xiao Li & Daning Hu & Harry Jiannan Wang, 2021. "Differential impacts of social influence on initial and sustained participation in open source software projects," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(9), pages 1133-1147, September.
    3. Bertrand Jayles & Clément Sire & Ralf H J M Kurvers, 2021. "Crowd control: Reducing individual estimation bias by sharing biased social information," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-28, November.
    4. Jalees, Tariq & Tariq, Huma & Zaman, Syed Imran & Alam Kazmi, Syed Hasnain, 2015. "Social Media in Virtual Marketing," MPRA Paper 69868, University Library of Munich, Germany, revised 10 Apr 2015.
    5. Langley, David J. & Hoeve, Maarten C. & Ortt, J. Roland & Pals, Nico & van der Vecht, Bob, 2014. "Patterns of Herding and their Occurrence in an Online Setting," Journal of Interactive Marketing, Elsevier, vol. 28(1), pages 16-25.
    6. Ines Küster & Asuncion Hernández, 2012. "Brand impact on purchase intention. An approach in social networks channel," Economics and Business Letters, Oviedo University Press, vol. 1(2), pages 1-9.
    7. Aleksandar Bradic, 2012. "The Role of Social Feedback in Financing of Technology Ventures," Papers 1301.2196, arXiv.org.
    8. Lashgari, Maryam, 2014. "Social Media Technology Deployment in B2B: A Case Study," INDEK Working Paper Series 2014/9, Royal Institute of Technology, Department of Industrial Economics and Management.
    9. Xuzhen Zhu & Jinming Ma & Xin Su & Hui Tian & Wei Wang & Shimin Cai, 2019. "Information Spreading on Weighted Multiplex Social Network," Complexity, Hindawi, vol. 2019, pages 1-15, November.
    10. Li, Xin & Xie, Qianqian & Jiang, Jiaojiao & Zhou, Yuan & Huang, Lucheng, 2019. "Identifying and monitoring the development trends of emerging technologies using patent analysis and Twitter data mining: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 687-705.
    11. Moro, Sérgio & Rita, Paulo & Vala, Bernardo, 2016. "Predicting social media performance metrics and evaluation of the impact on brand building: A data mining approach," Journal of Business Research, Elsevier, vol. 69(9), pages 3341-3351.
    12. Kim Holmberg & Mike Thelwall, 2014. "Disciplinary differences in Twitter scholarly communication," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1027-1042, November.
    13. Shu-Hsun Ho & Yu-Ling Lin & Robert Carlson Patrick, 2015. "Participant Motivations In A Social Media Community Page," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 9(4), pages 67-75.
    14. Mohammed Abdul-Rahman & Wale Alade & Shahnawaz Anwer, 2023. "A Composite Resilience Index (CRI) for Developing Resilience and Sustainability in University Towns," Sustainability, MDPI, vol. 15(4), pages 1-27, February.
    15. Yang Xiao & Beiqun Li & Zaiwu Gong, 2018. "Real-time identification of urban rainstorm waterlogging disasters based on Weibo big data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(2), pages 833-842, November.
    16. Pablo Gomez‐Carrasco & Giovanna Michelon, 2017. "The Power of Stakeholders' Voice: The Effects of Social Media Activism on Stock Markets," Business Strategy and the Environment, Wiley Blackwell, vol. 26(6), pages 855-872, September.
    17. Charitha Harshani Perera & Rajkishore Nayak & Long Thang Van Nguyen, 2019. "Role of social word-of-mouth on emotional brand attachment and brand choice intention: A study on private educational institutes in Vietnam," Proceedings of Business and Management Conferences 8611115, International Institute of Social and Economic Sciences.
    18. Geoffrey Barbier & Reza Zafarani & Huiji Gao & Gabriel Fung & Huan Liu, 2012. "Maximizing benefits from crowdsourced data," Computational and Mathematical Organization Theory, Springer, vol. 18(3), pages 257-279, September.
    19. I Made Wijaya Kusuma & I Gusti Ayu Wimba & Putu Yudy Wijaya, 2022. "The role of brand image and brand trust through electronic word of mouth in creating parent’s interest to sending children to school," Technium Social Sciences Journal, Technium Science, vol. 35(1), pages 477-489, September.
    20. Suddaby, Roy & Saxton, Gregory D. & Gunz, Sally, 2015. "Twittering change: The institutional work of domain change in accounting expertise," Accounting, Organizations and Society, Elsevier, vol. 45(C), pages 52-68.

    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:phsmap:v:404:y:2014:i:c:p:142-149. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.