IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v6y2012i4p600-610.html
   My bibliography  Save this article

Estimating the diffusion models of crisis information in micro blog

Author

Listed:
  • Wei, Jiuchang
  • Bu, Bing
  • Liang, Liang

Abstract

The study tries to construct the diffusion models of crisis information in micro blog. We propose three information release patterns in micro blog according to the duration of crisis information released, namely concentrated release, continuous release, and pulse release. Based on Logistic function, three respective diffusion models are constructed. We choose three crisis events to test the diffusion models using the variables of the number of micro blogs with the crisis information (NMCI) and the increment of NMCI. The estimate results show that the diffusion of crisis information in micro blogs can be described by Logistic function, and the growth curve of NMCI is S-shaped.

Suggested Citation

  • Wei, Jiuchang & Bu, Bing & Liang, Liang, 2012. "Estimating the diffusion models of crisis information in micro blog," Journal of Informetrics, Elsevier, vol. 6(4), pages 600-610.
    • Handle: RePEc:eee:infome:v:6:y:2012:i:4:p:600-610
    DOI: 10.1016/j.joi.2012.06.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S175115771200048X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2012.06.005?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. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    2. Jiuchang Wei & Dingtao Zhao & Liang Liang, 2009. "Estimating the growth models of news stories on disasters," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(9), pages 1741-1755, September.
    3. Paul D. Allison, 1980. "Estimation and Testing for a Markov Model of Reinforcement," Sociological Methods & Research, , vol. 8(4), pages 434-453, May.
    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. Xu, Jia & Wei, Jiuchang & Zhao, Dingtao, 2016. "Influence of social media on operational efficiency of national scenic spots in china based on three-stage DEA model," International Journal of Information Management, Elsevier, vol. 36(3), pages 374-388.
    2. Kim, Taekyung, 2014. "Observation on copying and pasting behavior during the Tohoku earthquake: Retweet pattern changes," International Journal of Information Management, Elsevier, vol. 34(4), pages 546-555.
    3. Vera Ivanyuk, 2021. "Formulating the Concept of an Investment Strategy Adaptable to Changes in the Market Situation," Economies, MDPI, vol. 9(3), pages 1-19, June.
    4. Jun, Seung-Pyo & Sung, Tae-Eung & Park, Hyun-Woo, 2017. "Forecasting by analogy using the web search traffic," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 37-51.
    5. Guanghui Yuan & Zhiqiang Liu & Yaqiong Wang & Dongping Pu, 2023. "Market Demand Optimization Model Based on Information Perception Control," Mathematics, MDPI, vol. 11(3), pages 1-16, February.
    6. Xianwen Wang & Wenli Mao & Shenmeng Xu & Chunbo Zhang, 2014. "Usage history of scientific literature: Nature metrics and metrics of Nature publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1923-1933, 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. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    2. Yuri Peers & Dennis Fok & Philip Hans Franses, 2012. "Modeling Seasonality in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 351-364, March.
    3. Constanza Fosco, 2012. "Spatial Difusion and Commuting Flows," Documentos de Trabajo en Economia y Ciencia Regional 30, Universidad Catolica del Norte, Chile, Department of Economics, revised Sep 2012.
    4. Guseo, Renato, 2016. "Diffusion of innovations dynamics, biological growth and catenary function," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 1-10.
    5. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    6. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    7. Najmeh Madadi & Azanizawati Ma’aram & Kuan Yew Wong, 2017. "A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1300992-130, January.
    8. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    9. Wedad Elmaghraby & Altan Gülcü & P{i}nar Keskinocak, 2008. "Designing Optimal Preannounced Markdowns in the Presence of Rational Customers with Multiunit Demands," Manufacturing & Service Operations Management, INFORMS, vol. 10(1), pages 126-148, June.
    10. Vakratsas, Demetrios & Kolsarici, Ceren, 2008. "A dual-market diffusion model for a new prescription pharmaceutical," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 282-293.
    11. Ruiz-Conde, Enar & Wieringa, Jaap E. & Leeflang, Peter S.H., 2014. "Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 49-63.
    12. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    13. Hariharan, Vijay Ganesh & Talukdar, Debabrata & Kwon, Changhyun, 2015. "Optimal targeting of advertisement for new products with multiple consumer segments," International Journal of Research in Marketing, Elsevier, vol. 32(3), pages 263-271.
    14. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    15. Trichy V. Krishnan & Frank M. Bass & Dipak C. Jain, 1999. "Optimal Pricing Strategy for New Products," Management Science, INFORMS, vol. 45(12), pages 1650-1663, December.
    16. Michal Grajek, 2002. "Identification of Network Externalities in Markets for Non-Durables," CIG Working Papers FS IV 02-32, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
    17. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    18. Nikolaos E. Petridis & Georgios Digkas & Leonidas Anastasakis, 2020. "Factors affecting innovation and imitation of ICT in the agrifood sector," Annals of Operations Research, Springer, vol. 294(1), pages 501-514, November.
    19. Li, Feng & Du, Timon C. & Wei, Ying, 2020. "Enhancing supply chain decisions with consumers’ behavioral factors: An illustration of decoy effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    20. Guseo, Renato & Schuster, Reinhard, 2021. "Modelling dynamic market potential: Identifying hidden automata networks in the diffusion of pharmaceutical drugs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).

    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:6:y:2012:i:4:p:600-610. 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.