IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v377y2007i1p253-268.html
   My bibliography  Save this article

Statistical physics of media processes: Mediaphysics

Author

Listed:
  • Kuznetsov, Dmitri V.
  • Mandel, Igor

Abstract

The processes of mass communications in complicated social or sociobiological systems such as marketing, economics, politics, animal populations, etc. as a subject for the special scientific subbranch—“mediaphysics”—are considered in its relation with sociophysics. A new statistical physics approach to analyze these phenomena is proposed. A keystone of the approach is an analysis of population distribution between two or many alternatives: brands, political affiliations, or opinions. Relative distances between a state of a “person's mind” and the alternatives are measures of propensity to buy (to affiliate, or to have a certain opinion). The distribution of population by those relative distances is time dependent and affected by external (economic, social, marketing, natural) and internal (influential propagation of opinions, “word of mouth”, etc.) factors, considered as fields. Specifically, the interaction and opinion-influence field can be generalized to incorporate important elements of Ising-spin-based sociophysical models and kinetic-equation ones. The distributions were described by a Schrödinger-type equation in terms of Green's functions. The developed approach has been applied to a real mass-media efficiency problem for a large company and generally demonstrated very good results despite low initial correlations of factors and the target variable.

Suggested Citation

  • Kuznetsov, Dmitri V. & Mandel, Igor, 2007. "Statistical physics of media processes: Mediaphysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 253-268.
    • Handle: RePEc:eee:phsmap:v:377:y:2007:i:1:p:253-268
    DOI: 10.1016/j.physa.2006.10.098
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437106011253
    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.2006.10.098?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. Fang Wu & Bernardo A. Huberman, 2004. "Social Structure and Opinion Formation," Computational Economics 0407002, University Library of Munich, Germany.
    2. Katarzyna Sznajd-Weron, 2005. "Sznajd model and its applications," HSC Research Reports HSC/05/04, Hugo Steinhaus Center, Wroclaw University of Technology.
    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. Stan Lipovetsky, 2023. "Quantum-like Data Modeling in Applied Sciences: Review," Stats, MDPI, vol. 6(1), pages 1-9, February.
    2. Lipovetsky, Stan, 2018. "Quantum paradigm of probability amplitude and complex utility in entangled discrete choice modeling," Journal of choice modelling, Elsevier, vol. 27(C), pages 62-73.

    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. Weron, Tomasz & Kowalska-Pyzalska, Anna & Weron, Rafał, 2018. "The role of educational trainings in the diffusion of smart metering platforms: An agent-based modeling approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 591-600.
    2. Hang-Hyun Jo & Jeoung-Yoo Kim, 2012. "Competitive Targeted Marketing," ISER Discussion Paper 0834, Institute of Social and Economic Research, Osaka University.
    3. Guzmán-Vargas, L. & Hernández-Pérez, R., 2006. "Small-world topology and memory effects on decision time in opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 372(2), pages 326-332.
    4. Dahlan, Rolan Mauludy & Situngkir, Hokky, 2010. "Evolution of Consumers’ Preferences due to Innovation," MPRA Paper 24159, University Library of Munich, Germany.
    5. Jędrzejewski, Arkadiusz & Sznajd-Weron, Katarzyna, 2018. "Impact of memory on opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 306-315.
    6. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    7. Gündüç, Semra & Eryiğit, Recep, 2015. "The role of persuasion power on the consensus formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 426(C), pages 16-24.
    8. Angelo Mondaini Calvão & Nuno Crokidakis & Celia Anteneodo, 2015. "Stylized Facts in Brazilian Vote Distributions," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-20, September.
    9. Kei Katahira & Yu Chen & Gaku Hashimoto & Hiroshi Okuda, 2019. "Development of an agent-based speculation game for higher reproducibility of financial stylized facts," Papers 1902.02040, arXiv.org.
    10. Katsuma Mitsutsuji & Susumu Yamakage, 2020. "The dual attitudinal dynamics of public opinion: an agent-based reformulation of L. F. Richardson’s war-moods model," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 439-461, April.
    11. Otto, Ilona M. & Wiedermann, Marc & Cremades, Roger & Donges, Jonathan F. & Auer, Cornelia & Lucht, Wolfgang, 2020. "Human agency in the Anthropocene," Ecological Economics, Elsevier, vol. 167(C).
    12. Ding, Fei & Liu, Yun & Shen, Bo & Si, Xia-Meng, 2010. "An evolutionary game theory model of binary opinion formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1745-1752.
    13. Catherine A. Glass & David H. Glass, 2021. "Social Influence of Competing Groups and Leaders in Opinion Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 799-823, October.
    14. Kowalska-Pyzalska, Anna & Maciejowska, Katarzyna & Suszczyński, Karol & Sznajd-Weron, Katarzyna & Weron, Rafał, 2014. "Turning green: Agent-based modeling of the adoption of dynamic electricity tariffs," Energy Policy, Elsevier, vol. 72(C), pages 164-174.
    15. Hernan Mondani & Petter Holme & Fredrik Liljeros, 2014. "Fat-Tailed Fluctuations in the Size of Organizations: The Role of Social Influence," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-9, July.
    16. Shang, Lihui & Zhao, Mingming & Ai, Jun & Su, Zhan, 2021. "Opinion evolution in the Sznajd model on interdependent chains," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    17. Kułakowski, Krzysztof, 2009. "Opinion polarization in the Receipt–Accept–Sample model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(4), pages 469-476.
    18. Diao, Su-Meng & Liu, Yun & Zeng, Qing-An & Luo, Gui-Xun & Xiong, Fei, 2014. "A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 220-228.
    19. Fan, Kangqi & Pedrycz, Witold, 2016. "Opinion evolution influenced by informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 431-441.
    20. Song, Xiao & Shi, Wen & Tan, Gary & Ma, Yaofei, 2015. "Multi-level tolerance opinion dynamics in military command and control networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 322-332.

    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:377:y:2007:i:1:p:253-268. 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.