19 research outputs found
Socio-Physical Approach to Consensus Building and the Occurrence of Opinion Divisions Based on External Efficacy
The proliferation of public networks has enabled instantaneous and
interactive communication that transcends temporal and spatial constraints. The
vast amount of textual data on the Web has facilitated the study of
quantitative analysis of public opinion, which could not be visualized before.
In this paper, we propose a new theory of opinion dynamics. This theory is
designed to explain consensus building and opinion splitting in opinion
exchanges on social media such as Twitter. With the spread of public networks,
immediate and interactive communication that transcends temporal and spatial
constraints has become possible, and research is underway to quantitatively
analyze the distribution of public opinion, which has not been visualized until
now, using vast amounts of text data. In this paper, we propose a model based
on the Like Bounded Confidence Model, which represents opinions as continuous
quantities. However, the Bounded Confidence mModel assumes that people with
different opinions move without regard to their opinions, rather than ignoring
them. Furthermore, our theory modeled the phenomenon in such a way that it can
incorporate and represent the effects of external external pressure and
dependence on surrounding conditions. This paper is a revised version of a
paper submitted in December 2018(Opinion Dynamics Theory for Analysis of
Consensus Formation and Division of Opinion on the Internet).Comment: Revised Paper:Opinion Dynamics Theory for Analysis of Consensus
Formation and Division of Opinion on the Internet(2018
From Spin States to Social Consensus: Ising Approach to Dimer Configurations in Opinion Formation
The field of opinion dynamics has evolved steadily since the earliest studies
applying magnetic physics methods to better understand social opinion
formation. However, in the real world, complete agreement of opinions is rare,
and biaxial consensus, especially on social issues, is rare. To address this
challenge, Ishii and Kawabata (2018) proposed an extended version of the
Bounded Confidence Model that introduces new parameters indicating dissent and
distrust, as well as the influence of mass media. Their model aimed to capture
more realistic social opinion dynamics by introducing coefficients representing
the degree of trust and distrust, rather than assuming convergence of opinions.
In this paper, we propose a new approach to opinion dynamics based on this
Trust-Distrust Model (TDM), applying the dimer allocation and Ising model. Our
goal is to explore how the interaction between trust and distrust affects
social opinion formation. In particular, we analyze through mathematical models
how various external stimuli, such as mass media, third-party opinions, and
economic and political factors, affect people's opinions. Our approach is to
mathematically represent the dynamics of trust and distrust, which traditional
models have not addressed. This theoretical framework provides new insights
into the polarization of opinions, the process of consensus building, and how
these are reflected in social behavior. In addition to developing the
theoretical framework by applying the dimer configuration, the dimer model and
the Ising model, this paper uses numerical simulations to show how the proposed
model applies to actual social opinion formation. This research aims to
contribute to a deeper understanding of social opinion formation by providing
new perspectives in the fields of social science, physics, and computational
modeling.Comment: Discussion Paper:Theory of opinion distribution in human relations
where trust and distrust mixed(2020
Transitioning To The Digital Generation Case Studies (Previous Digital Point Studies In Japan Cases:1993-2023)
In this paper, we discuss at The 8th International Workshop on Application of
Big Data for Computational Social Science, October 26-29, 2023, Venice, Italy.
To achieve the realization of the Global and Innovation Gateway for All (GIGA)
initiative (2019), proposed in December 2019 by the Primary and Secondary
Education Planning Division of the Elementary and Secondary Education Bureau of
the Ministry of Education, Culture, Sports, Science and Technology, a movement
has emerged to utilize information and communication technology (ICT) in the
field of education. The history of ICT education in Japan dates back to the 100
Schools Project (1994), which aimed to provide network access environments, and
the New 100 Schools Project (1997), which marked the beginning of full-scale
ICT education in Japan. In this paper, we discuss the usage dynamics of
smartphone-based learning applications among young people (analyzing data from
January to September 2020) and their current status. Further, the results are
summarized and future research topics and issues are discussed. The results
show that there are situations in which ICT learning environments can be
effectively utilized and others in which they cannot, depending on the
differences between digital students and analog students who utilize ICT in
their studies; this indicates that we are currently in a transition to a
generation of digital natives. ICT education has both advantages and
disadvantages, and it is expected that it will be used in combination with
conventional educational methods while assessing the characteristics of ICT
education in the future. Of course, there are many challenges. We plan to
discuss how to appeal in this regard at the Workshop.Comment: Part of the 22nd IEEE WIC International Conference on Web
Intelligence and Intelligent Agent Technology WI-IAT2023, Workshop of The 8th
International Workshop on Application of Big Data for Computational Social
Science, WI Artificial Intelligence in the Connected World October 26-29,
2023, Venice, Ital
Discussion of the Effect of Inter-group Sub-groups Using a Consensus Model Incorporating External Effective or Immobile Magnetic Fields
Individuals belong to certain social groups in search of a sense of
belonging, pride, stability, and significance. Perceiving the group to which
one belongs as an "in-group" and other groups as "out-groups" often leads to
harmful and discriminatory attitudes. In-group consciousness reinforces a sense
of unity within the group and promotes commitment to group goals and problem
solving. Identification with the in-group also shapes the social cognitive
framework (norms, values, and beliefs) that determine group behavior. In fact,
identification with an in-group often leads to prejudice, ethnocentrism,
stereotyping, and discrimination, even in the absence of physical conflict or
hostility. Social scientists have conducted thousands of empirical studies to
elucidate the mechanisms behind these prejudices and discriminations and the
social conflicts they generate. These studies are essential to understanding
the processes by which group membership and self-categorization create
prejudice and discrimination, which in turn lead to social conflict. However,
there remain many unanswered questions about howin-groups and out-groups
canmove beyond conflict to build harmony and avoid social conflict. According
to existing research, it is difficult to establish harmonious relationships
between in-groups and out-groups. This study proposes an approach using opinion
dynamics theory and social simulation to examine these issues. We examine the
possibility of simulating the movement of opinions between and within groups
and applying the considerations to cases of social conflict. The model analyzes
the severity of conflict within a society with two groups on the basis of
intragroup and intergroup trust.Comment: Discussion Paper:Theory of opinion distribution in human relations
where trust and distrust mixed(2020
Massive Case Study of Opinion Distribution in a Relationship with Mixed Trust and Distrust
The simulations in this paper are based on the theory of opinion dynamics,
which incorporates both Opinion A and Opinion B, a case that is the inverse of
Opinion A, in human relationships. It was confirmed that aspects of consensus
building depend on the ratio of the trust coefficient to the distrust
coefficient. In this study, the ratio of trust to distrust tended to vary like
a phase transition around 55%, but we wanted to see if the same phenomenon
could be confirmed in large-scale cases. In the previous case studies, this
tendency has been observed from N = 300 to N = 1600 , and we will discuss the
case of N = 10000 with N = 3000. By verifying the extent of the phenomenon on
the social scale, we intend to consider simulation items for consensus
building, such as consideration of the sensitivities of topics in online and
offline opinion formation.Comment: Revised Paper:Theory of opinion distribution in human relations where
trust and distrust mixed(2020
Sociophysics Analysis of the Dynamics of Peoples' Interests in Society
As a method of analyzing and predicting social phenomena using social media as data, we present analyses based on the mathematical model of the hit phenomenon, which is one of the established models of sociophysics. The dynamics of the number of social media posts for movies, events, and a YouTube movie are explained. For entertainment topics, the direct communication strength, “D,” indicates the satisfaction of the current interested people or supporters, whereas the indirect communication strength, “P,” indicates the power to acquire a new support layer. Thus, this is effective not only for the analysis of entertainment and marketing strategy but also for burst analysis on the social media
Significant Role of Trust and Distrust in Social Simulation
This paper introduces the Trust-Distrust Model and its applications, extending the Bounded Confidence Model, a theory of opinion dynamics, to include the relationship between trust and mistrust. In recent years, there has been an increase in the number of cases in which the prerequisites for conventional communication (e.g., the other person’s gender, appearance, tone of voice, etc.) cannot be established without the exchange of personal information. However, in recent years, there has been an increase in the use of personal information, such as letters and pictograms “as cryptographic asset data” for two-way communication. However, there are advantages and disadvantages to using information assets in the form of personalized data, which are excerpts of personal information as described above. In the future, the discussion of trust value in the above data will accelerate in indicators such as personal credit scoring. In this paper, the Trust-Distrust Model will be discussed with respect to theories that also address charismatic people, the effects of advertising, and social divisions. Furthermore, simulations of the Trust-Distrust Model show that 55% agreement is sufficient to build social consensus. By addressing this theory, we hope to use it to discuss and predict social risk in future credit scoring discussions