• East Asian mathematical journal
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• v.40 no.3
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• pp.341-353
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• 2024

This paper aims to provide a general review of Opinion Dynamics (OD) and its related models, along with application examples for special agents. We will discuss special classes of social actors, such as informed actors, opponents, and extremists, in the context of opinion dynamics. Our main objective is to determine the extent to which opinion dynamics, as a mathematical sociology, relates to social reality. To achieve this, we present key elements of mathematical sociology in Opinion Dynamics, which we then apply to real socioeconomic phenomena using modeling assumptions and mathematical formulations.

• Korean System Dynamics Review
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• v.8 no.1
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• pp.151-171
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• 2007

Without exception, diverse LULU(Locally Unwanted Land Use) facilities have been under the location conflict, especially between the public government units and local residents. In spite of repeated trials-and-errors, literally, the location conflict has shown no sign of improvement over time in Korea. As practical means to tackle these issues, this study focuses on divulging explicit and implicit relationships among key factors derived from the location conflict on the LULU facilities. Here, major research variables cover residents' agreement, residents' perception, compensation expectation, and public opinion. As the location conflict on the LULU facilities could be strengthened or resolved by the dynamic feedback system, it applies basic tools geared toward causal loop diagramming. After repeated experiments, the study highlights the fact that the residents' perception, compensation expectation, and public opinion, individually and collectively, exert significant impact on the residents' agreement ratio.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1406-1409
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• 2018

We have frequently encountered the rapid changes that prevalent opinion of the social community is toppled by a new and opposite opinion against the pre-exiting one. To understand this interesting process, mean-field model with infinite-interaction range has been mostly considered in previous studies S. A. Marvel et al., Phys. Rev. Lett. 110, 118702 (2012). However, the mean-field interaction range is lack of reality in the sense that any individual cannot interact with all of the others in the community. Based on it, in the present work, we consider a simple model of opinion consensus so-called basic model on the low-dimensional lattices (d = 1, 2) with finite interaction range. The model consists of four types of subpopulations with different opinions: A, B, AB, and the zealot of A denoted by $A_c$, following the basic model shown in the work by S. A. Marvel et al.. Comparing with their work, we consider the finite range of the interaction, and particularly reconstruct the lattice structure by adding new links when the two individuals have the distance < ${\sigma}$. We explore how the interaction range ${\sigma}$ affects the opinion consensus process on the reconstructed lattice structure. We find that the critical fraction of population for $A_c$ required for the opinion consensus on A shows different behaviors in the small and large interaction ranges. Especially, the critical fraction for $A_c$ increases with the size of ${\sigma}$ in the region of small interaction range, which is counter-intuitive: When the interaction range is increased, not only the number of nodes affected by $A_c$ but also that affected by B grows, which is believed to cause the increasing behavior of the critical fraction for $A_c$. We also present the difference of dynamic process to the opinion consensus between the regions of small and large interaction ranges.

• Korean System Dynamics Review
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• v.10 no.1
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• pp.33-60
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• 2009

This study explores the limitation in making a causal model through an existing case and proposes an alternative plan to improve a theoretical system of causation modeling. To make a dynamic and actual model, several principles are needed such as reality based analysis of system structures and dynamics, consistent expression of causations, conversion of numerical formulas to causal relations, classification and arrangement of variables by size of concept, etc. However, it is hard to find cases to apply these considerations from existing models in System Dynamics. Therefore, this study verifies errors of derived models from literatures and proposes principles and guides that should be considered to make a sound dynamic model on a causal map. It contributes to making an opportunity for exciting public opinion to improve theory about causal maps, yet it has limitation that the study does not advance forward to the experimental step. For future study, it plans to make up by classifying and leveling causal variables, developing a dynamic BSC model.

• Knowledge Management Research
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• v.11 no.2
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• pp.17-35
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• 2010

As the internet has been used widely, many online communities have been appeared. Initially, many users used online communities for communication and information sharing. Recently, users start using online communities for building, maintaining, and extending social networks which they did in offline environments previously. The importance of online community is considered by many scholars and also companies to use it strategically. Therefore many studies have focused on exploring characteristics of online communities. Most of them have emphasized the importance of online community. Few study focuses on dynamics within online community. By using social network analysis (SNA), this study tries to explore dynamics of online community. Specially, By measuring the centrality of online community and tracing its changes, this study investigates how the relationships among participants in online communities have been changed over the time. Findings of this study indicate that, as participants has joined in an online community over the time, an opinion leader is appeared, and her/his power is changed.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.329-340
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• 2015

In the age of media convergence, this study intended to empirically examine the influences of entertainment programs on the formation of public opinion in Twitter using the case of the Healing Camp, an entertainment program of SBS, featured Cheol Soo Ahn, who was a presidential candidate. Through a content analysis this study was able to directly test how public opinion was developed in Twitter and also examine the dynamics in which the messages of traditional media influence the formation of public opinion in twitter by combining Twitter and actual contents of the TV program. The study is expected to contribute to expanding a scope of scholarly attention of social media.

• Asian Journal for Public Opinion Research
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• v.12 no.3
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• pp.184-213
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• 2024

This research investigates the intricate dynamics governing loyalty and recommendation behaviors. The primary objective is to discern the impact of community development on user loyalty and its subsequent influence on product recommendations, using the Indonesian online brand community of the software Micromine as a case study. The technology acceptance model, which argues that adoption is done because of perceived ease, and cognitive dissonance theory, which describes how individuals adjust to reduce discomfort, provide the framework for this study. Utilizing a quantitative methodology, all 300 members of the online Micromine Indonesia community population were surveyed. The findings reveal that community members establish emotional connections through active participation in community forums. Satisfaction with the software's solutions in mining endeavors is prevalent among Micromine community members. Regression analysis showed that a positive attitude about the brand community was positively correlated with both brand loyalty (R² = .83) and the likelihood of recommending the brand (R² = .78). This supports both theories, where brand community members adopt technology and reduce discomfort by supporting community activities.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.155-166
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• 2018

These days, online media, such as blogospheres, online communities, and social networking sites, provides the uncountable user-generated content (UGC) to discover market intelligence and business insight with. The business has been interested in consumers, and constantly requires the approach to identify consumers' opinions and competitive advantage in the competing market. Analyzing consumers' opinion about oneself and rivals can help decision makers to gain in-depth and fine-grained understanding on the human and social behavioral dynamics underlying the competition. In order to accomplish the comparison study for rival products and companies, we attempted to do competitive analysis using text mining with online UGC for two popular and competing ramens, a market leader and a market follower, in the Korean instant noodle market. Furthermore, to overcome the lack of the Korean sentiment lexicon, we developed the domain specific sentiment dictionary of Korean texts. We gathered 19,386 pieces of blogs and forum messages, developed the Korean sentiment dictionary, and defined the taxonomy for categorization. In the context of our study, we employed sentiment analysis to present consumers' opinion and statistical analysis to demonstrate the differences between the competitors. Our results show that the sentiment portrayed by the text mining clearly differentiate the two rival noodles and convincingly confirm that one is a market leader and the other is a follower. In this regard, we expect this comparison can help business decision makers to understand rich in-depth competitive intelligence hidden in the social media.

• Asian Journal for Public Opinion Research
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• v.10 no.1
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• pp.4-22
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• 2022

The purpose of this study is to explore the structure of social discourse on aging in Korea by analyzing newspaper articles on aging. The analysis is composed of three steps: first, data collection and preprocessing; second, identifying the latent topics; and third, observing yearly dynamics of topics. In total, 1,472 newspaper articles that included the word "aging" within the title were collected from 10 major newspapers between 2006 and 2019. The underlying topic structure was analyzed using Latent Dirichlet Allocation (LDA), a topic modeling method widely adopted by text mining academics and researchers. Seven latent topics were generated from the LDA model, defined as social issues, death, private insurance, economic growth, national debt, labor market innovation, and income security. The topic loadings demonstrated a clear increase in public interest on topics such as national debt and labor market innovation in recent years. This study concludes that media discourse on aging has shifted towards more productivity and efficiency related issues, requiring older people to be productive citizens. Such subjectivation connotes a decreased role of the government and society by shifting the responsibility to individuals not being able to adapt successfully as productive citizens within the labor market.

• Journal of Energy Engineering
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• v.17 no.2
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• pp.77-87
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• 2008

Decision-making of the site for the medium and low-level radioactive-waste disposal facilities in 2005 can be estimated as a success. But the limits exposed during the process still remain as problems to be solved. Analyzing the causes of success and failure of the policy and their correlation was expected to provide an effective guideline on future policies. The analysis shows that the transparency of policy makers, the level of community supports and the public relations are decisive factors. System dynamics, a synthetic analyzing tool, is used as a methodology for policy analysis. The result of the system dynamics analysis shows that public confidence is to be the key role to for and against logics when transparency of stakeholder, subsidy and public information are set as adjustable parameters. Public confidence takes a role of leverage that can convert tendency of conclusion by the opinion which influenced by selected parameters.