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Can Interactive Dual Fields of Information Explain the Prevalent Phenomena
American Journal of Physics and Applications
Volume 7, Issue 6, November 2019, Pages: 144-155
Received: Dec. 14, 2019; Accepted: Dec. 26, 2019; Published: Jan. 8, 2020
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Author
Teruaki Ohnishi, Institute of Science and Technology for Society, Urayasu, Chiba, Japan
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Abstract
The occurrence of prevalent phenomena is an almost unclear but interesting subject for us. Here we have constructed a dual model of information fields originated from the news media and showed that the quasi-cyclic appearance of prevalence can be explained by such a model. The homogeneous field of information around us was assumed, which is composed of the real field originated from the primary media such as newspapers and the television, and the cyber field from the PC and smart phones. The latter field is of the SNS cyber world affected by the field of real world. The public was assumed to be influenced simultaneously by these two types of fields to result in the enhancement of the awareness of some specific things. To investigate the viability of such a dual model, inputting the data of the real field regarding the global warming (GW) already reported in Japan as an external variable, the feature was derived in what manner the public awareness of GW had varied during the past ~35 years. The high public awareness was found to be realized at around 2009 when the information environment was explosively enhanced in the real world. Such enhancement of the awareness could be explained by the contribution from the cyber field, which was brought by the instability of the field, or a burst, induced by a small perturbation from the real field. A possibility was pointed out that the spontaneous occurrence of quasi-cyclic instability such as the case of our explosive awareness could take place in the interactive dual system of information between the real and cyber fields. We pointed out that the spontaneous occurrence of prevalence in general could be explained also by the similar mechanism as ours.
Keywords
Duality of Information Fields, Quasi-cyclic Prevalence, Public Awareness, SNS, News Media, Global Warming, Burst, Real and Cyber Worlds
To cite this article
Teruaki Ohnishi, Can Interactive Dual Fields of Information Explain the Prevalent Phenomena, American Journal of Physics and Applications. Vol. 7, No. 6, 2019, pp. 144-155. doi: 10.11648/j.ajpa.20190706.12
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Statista, “News sources used in European countries in 2018”, http://www. statista.com/statistics/422687/news-sources-in-europen-countries/, Sept. 19, 2019 (retrieved).
[2]
Pew Research Center, “More Americans get news often from social media than print paper”, https://www.pewresearch.org/fact-tank/2018/12/10/social_media_outpaces_print_ newspapers_in_the_U.S._as_a_news_source”, Sept. 19, 2019 (retrieved).
[3]
Japan Press Research Institute, National polls on the news media, 1st~10th, (2018) (in Japanese).
[4]
NTT Docomo Mobile Society Research Institute, Usage trends of smart and mobile phones deciphered by the data 2018-2019 (Mobile phone social white paper), Chuoukeizaisha, Tokyo, 2018 (in Japanese).
[5]
F. Schweitzer and J. A. Holyst, “Modelling collective opinion formation by means of active Brownian particles,” Eur. Phys. J, B15, 723-732, 2000.
[6]
F. Gargiulo and S. Huet, “Opionion dynamics in a group-based society,” European Physics Letters, 91, 58004, 2010.
[7]
A. Jedrzejewski and K. Sznajd-Weron, “Impact of memory on opinion dynamics,” Physica, A505, 306-315, 2018.
[8]
D. Helbing, “A mathematical model for the behavior of individuals in a social field,” J. Math. Soc. 19, 189-219, 1994.
[9]
J. Neirotti, “Consensus formation times in anisotropic societies,” Phys. Rev., E95, 062305, 2017.
[10]
C. Castellano, S. Fortunato and V. Loreto, “Statistical physics of social dynamics,” Rev. Mod. Phys., 81, 591-646, 2009.
[11]
A. H. Rodriguez and Y. Moreno, “Effect of mass media action on the Axlrod model with social influence,” Phys. Rev., E82, 016111, 2010.
[12]
B. Yun and Y. C. Cho, “Analyzing the effectiveness of public policy advertising on attitude and behavior change,” J. Bus. Econ. Res., 12, 357-370, 2014.
[13]
M. Pineda and G. M. Buendia, “Mass media and heterogeneous bounds of confidence in continuous opinion dynamics,” Physica, A420, 73-84, 2015.
[14]
K. Fan and W. Pedrycz, “Evolution of public opinions in closed societies influenced by broadcast media,” Physica, A 472, 53-66, 2017.
[15]
L. Deng, Y. Liu and Q-A. Zeng, “How information influences on individual opinion evolution,” Physica, A 391, 6409-6417, 2012.
[16]
J. R. Zaller, The nature and origins of mass opinion, Cambridge Univ. Press, NY, USA, 1992.
[17]
T. Ohnishi, “A collective model for the formation of public opinion: an application to nuclear public acceptance”, Mathl. Comput. Modelling, 19, 95-111, 1994.
[18]
T. Ohnishi, “A mathematical model of the activities for public acceptance and the resultant reaction of the public: an application to the nuclear problem,” Mathl. Comput. Modelling, 21, 1-30, 1995.
[19]
K. Kulakowski, “Opinion polarization in Receipt-Accept-Sample model,” Physica, A388, 469-476, 2009.
[20]
S. Biswas, A. Chatterjee and P. Sen, “Disorder induced phase transition in kinetic models of opinion dynamics,” Physica, A391, 3257-3265, 2012.
[21]
T. Ohnishi and K. Shimano, “Public interest immersed in the field of information environment: how has Japanese interest in energy and environmental problems varied?” Reports in Advances of Physical Sciences, 2, 1850005, 2018.
[22]
L. Weng, A. Flammini, A. Vespignani and F. Menczer, “Competition among memes in a world with limited attention,” Science Reports, 2, 335, 2012.
[23]
J. Leskovec, L. Backstrom amd J. Kleinberg, “Meme-tracking and the Dynamics of the News Cycle,” Proceedings 15th ACM SIGKDD Intern. Conf. Knowledge Discovery Data Mining, Paris, June, 2009.
[24]
M. Gentzkow, “Small media, big impact,” Science, 358, 726-727, 2017.
[25]
D. Centola, J. Becker, D. Brackbill and A. Baronchelli, “Experimental evidence for tipping points in social convention,” Science, 360, 1116-1119, 2018.
[26]
C. Doyle, B. K. Szymanski and G. Korniss, “Effects of communication burstiness on consensus formation and tipping points in social dynamics,” Phys. Rev., E95, 062303, 2017.
[27]
S. Pinto, F. Albanese, C. O. Dorso and P. Balenzuela, “Quantifying time-dependent media agenda and public opinion by topic modeling,” Physica, A524, 614-624, 2019.
[28]
M. Gladwell, The tipping point: how little things can make a big difference, Little, Brown and Company, Boston, 2000.
[29]
C. Granell, S. Gomez and A. Arenas, “On the dynamical interplay between awareness and epidemics spreading in multiplex networks,” Phys. Rev. Lett., 111, 128701, 2013.
[30]
R. Wang and Q. A. Wang, “Dual modeling of political opinion networks,” Phys. Rev., E84, 036108, 2011.
[31]
X. Dong, Y. Liu, C. Wu, Y. Lian and D. Tang, “A double-identity rumor spreading model,” Physica, A528, 121479, 2019.
[32]
Y. Yi, Z. Zhang and C. Gan, “The outbreak threshold of information diffusion over social-physical networks,” Physica, A526, 121128, 2019.
[33]
C. Wang, G. Wang, X. Luo and H. Li, “Modeling rumor propagation and mitigation across multiple social networks,” Physica, A535, 122240, 2019.
[34]
) H-W. Lee, N. Malik, F. Shi and P. Mucha, “Social clustering in epidemic spread on coevolving networks,” Phys. Rev., E99, 062301, 2019.
[35]
J. T. Ripberger, “Capturing curiosity: Using Internet search trends to measure public attentiveness,” Policy Studies Journal, 39, 239-259, 2011.
[36]
L. Guggenheim, S. M. Jang, S. Y. Bae and W. R. Neuman, “The dynamics of issue frame competition in traditional and social media,” Annals, AAPSS, 659, 207-224, 2015.
[37]
T. L. Milfont, “The interplay between knowledge, perceived efficacy, and concern about global warming and climate change: A one-year longitudinal study,” Risk Analysis, 32, 1003-1020, 2012.
[38]
A. Malka,. A. Krosnick and G. Langer, “The association of knowledge with concern about global warning: Trusted information sources shape public thinking,” Risk Analysis, 29, 633-647, 2009.
[39]
T. Ohnishi, “A mathematical model for the occurrence of historical events,” J. Phys.: Conf. Ser., 936, 012024, 2017.
[40]
NHK Archives, https://www.nhk.or.jp/archives/document/, Sept. 5, 2019 (retrieved in Japanese).
[41]
Oya Soichi Library Magazine Article Index Search, “Web OYA-bunko”, http://www.oya-bunko,or.jp/, Aug. 16, 2019 (retrieved in Japanese).
[42]
Google Trends, http;//www.google.com/trends, and Google Insights, http:/www.google.com/insights/search/, Aug. 16, 2019 (retrieved).
[43]
United Nations, Statistical Yearbook: sixty-first issue, New York, 2018.
[44]
National Institute of Environmental Studies, Japan, Report of public opinion survey on environmental awareness, Tokyo, 2016 (in Japanese).
[45]
G. King, B. Schneer and A. White, “How the news media activate public expression and influence national agendas,” Science, 358, 776-780, 2017.
[46]
Pew Research Center, “Social Media Update 2016,” https://www.pewinter net.org/2016/11/11/social-media-update-2016/, Aug. 30, 2019 (retrieved).
[47]
National Diet Library, Japan, “Database WARP,” http://warp.da.ndl.go.jp/, Aug. 29, 2019 (retrieved in Japanese).
[48]
T. Kimezawa and Y, Murayama, “Preservation of database on website-accessibility survey for Dnavi and sustainability of online databases,” J. Inf. Sci. Tech. Assoc., Japan, 67, 459-464, 2017 (in Japanese).
[49]
E. Rogers, Diffusion of Innovation, Free Press, New York: 1995.
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