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Yucheng Dong - One of the best experts on this subject based on the ideXlab platform.

  • Impact of Social Network Structures on Uncertain Opinion Formation
    IEEE Transactions on Computational Social Systems, 2019
    Co-Authors: Min Zhan, Haiming Liang, Yucheng Dong, Shui Yu
    Abstract:

    When people express their Opinions about a certain issue, they often give uncertain Opinions rather than exact Opinions. Particularly, these uncertain Opinions will evolve in social networks. Therefore, in this paper, we focus on investigating uncertain Opinion Formation with social networks under bounded confidence. Specifically, we define the uncertain Opinions by numerical interval Opinions, whose ranges are between zero and one, and the larger width of numerical interval Opinions means the more uncertainty of the Opinions. Meanwhile, we describe social network structures by ER random graphs with different agents' scales and network connected probabilities. Then, we present the detailed simulation experiments to reveal the strong impact of social network structures on uncertain Opinion Formation. Simulation results show that: 1) larger agents' scales will yield the smaller ratios of agents expressing the uncertain Opinions and larger average widths of uncertain Opinions; 2) the average stable time starts increasing and then decreases with the increase in the network connected probabilities; and 3) larger network connected probabilities will yield less Opinion clusters and the smaller ratios of the extremely small clusters in all clusters. The obtained results are helpful for the government and public Opinion management departments to understand and manage uncertain public Opinion evolution effectively.

  • SMC - Social Network Uncertain Opinion Formation Model in the Framework of Bounded Confidence
    2018 IEEE International Conference on Systems Man and Cybernetics (SMC), 2018
    Co-Authors: Min Zhan, Yucheng Dong
    Abstract:

    In this study, we propose a social network uncertain Opinion Formation model in the framework of bounded confidence to investigate the process of forming collective Opinions in a group of interaction agents under uncertain and social networks context. By taking different uncertain Opinions and different uncertainty tolerances into account, the simulations analysis conducted on data describing users' relationships in social media platforms in Opinion Formation from two aspects: different social networks connection probability and the numbers of agents. Based on simulation analysis, we provide the explanations of the observations obtained.

  • Dynamics of Uncertain Opinion Formation: An Agent-Based Simulation
    Journal of Artificial Societies and Social Simulation, 2016
    Co-Authors: Haiming Liang, Yucheng Dong
    Abstract:

    Opinion Formation describes the dynamics of Opinions in a group of interaction agents and is a powerful tool for predicting the evolution and diffusion of the Opinions. The existing Opinion Formation studies assume that the agents express their Opinions by using the exact number, i.e., the exact Opinions. However, when people express their Opinions, sentiments, and support emotions regarding different issues, such as politics, products, and events, they often cannot provide the exact Opinions but express uncertain Opinions. Furthermore, due to the differences in culture backgrounds and characters of agents, people who encounter uncertain Opinions often show different uncertainty tolerances. The goal of this study is to investigate the dynamics of uncertain Opinion Formation in the framework of bounded confidence. By taking different uncertain Opinions and different uncertainty tolerances into account, we use an agent-based simulation to investigate the influences of uncertain Opinions in Opinion Formation from two aspects: the ratios of the agents that express uncertain Opinions and the widths of the uncertain Opinions, and also provide the explanations of the observations obtained.

  • Dynamics of linguistic Opinion Formation in bounded confidence model
    Information Fusion, 2016
    Co-Authors: Yucheng Dong, Xia Chen, Haiming Liang
    Abstract:

    Abstract Opinion dynamics is a fusion process of individual Opinions based on the established fusion rules. The existing Opinion dynamics models assume that agents express and receive their Opinions in a numerical way. In this paper, we focus on the Opinion Formation in linguistic environment (i.e., linguistic Opinion Formation), and propose a linguistic Opinion dynamics (LOD) model in the framework of the bounded confidence and the 2-tuples linguistic model with numerical scales. In the LOD model, agents express and receive the Opinions by using the simple terms in a linguistic term set with finite granularity at each time. Based on the LOD model, we present some theoretical analyses to reveal the conditions to form a consensus or splits in the linguistic Opinion Formation. Furthermore, we design some simulations to investigate the effects of the bounded confidence and the uniformities of linguistic term sets on the linguistic Opinion Formation. The simulation results show that: (i) with the increase in the bounded confidence and the uniformities of linguistic term sets, the opportunity for reaching a consensus will increase, and the time for reaching a consensus will become shorter in the dynamics of linguistic Opinion Formation; (ii) there exists a critical point in the evolution of linguistic Opinions, which is called agreed confidence in this paper, and a consensus among the agents will be reached if the value of the bounded confidence is equal or greater than the agreed confidence.

  • IFSA-EUSFLAT - Uncertain Opinion Formation based on the bounded confidence model.
    Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology, 2015
    Co-Authors: Haiming Liang, Yucheng Dong
    Abstract:

    Opinion Formation is well used to investigate a consensus or several clusters among the Opinions of a group of interaction agents. This study proposes several bounded confidence models to discuss the uncertain Opinion Formation. In the proposed models, the agents’ various tolerances (zero-tolerance, partial tolerance and complete tolerance) on the uncertain Opinions are firstly identified. Then, the relevant communication regimes are given to determine the confidence set, and the updated Opinions are further calculated. Finally, we explore the influences of various types of agents and self-support on the average number of clusters through simulation analysis.

Stefan Bornholdt - One of the best experts on this subject based on the ideXlab platform.

  • Opinion Formation model for markets with a social temperature and fear
    2012
    Co-Authors: Sebastian M. Krause, Stefan Bornholdt
    Abstract:

    In the spirit of behavioral finance, we study the process of Opinion Formation among investors using a variant of the 2D Voter Model with a tunable social temperature. Further, a feedback acting on the temperature is introduced, such that social temperature reacts to market imbalances and thus becomes time dependent. In this toy market model, social temperature represents nervousness of agents towards market imbalances representing speculative risk. We use the knowledge about the discontinuous Generalized Voter Model phase transition to determine critical fixed points. The system exhibits metastable phases around these fixed points characterized by structured lattice states, with intermittent excursions away from the fixed points. The statistical mechanics of the model is characterized and its relation to dynamics of Opinion Formation among investors in real markets is discussed.

  • Opinion Formation model for markets with a social temperature and fear.
    Physical Review E, 2012
    Co-Authors: Sebastian M. Krause, Stefan Bornholdt
    Abstract:

    In the spirit of behavioral finance, we study the process of Opinion Formation among investors using a variant of the two-dimensional voter model with a tunable social temperature. Further, a feedback acting on the temperature is introduced, such that social temperature reacts to market imbalances and thus becomes time dependent. In this toy market model, social temperature represents nervousness of agents toward market imbalances representing speculative risk. We use the knowledge about the discontinuous generalized voter model phase transition to determine critical fixed points. The system exhibits metastable phases around these fixed points characterized by structured lattice states, with intermittent excursions away from the fixed points. The statistical mechanics of the model is characterized, and its relation to dynamics of Opinion Formation among investors in real markets is discussed.

Fattaneh Taghiyareh - One of the best experts on this subject based on the ideXlab platform.

  • Effect of Segregation on Opinion Formation in Scale-Free Social Networks: An Agent-based Approach
    International Journal of Engineering, 2021
    Co-Authors: A. Mansouri, Fattaneh Taghiyareh
    Abstract:

    We consider the effect of segregation on Opinion Formation in social networks with and without influential leaders in scale-free random networks, which is found in many social and natural phenomena. We have used agent-based modeling and simulation, focusing on the social impact model of Opinion Formation. Two simulation scenarios of this Opinion Formation model have been considered: (1) the original scenario which randomly assigns persuasion strengths to the agents, and (2) a centrality-based scenario, which assigns persuasion strengths proportional to the agents’ centralities. In the latter scenario, hubs are considered more influential leaders who are more connected to others and have higher persuasion strengths than others. The simulation results show a correlation between segregation and change of population Opinion in the original model, but no correlation between both variables in the centrality-based scenario. The results lead us to conclude that with strong influential leaders in society, the effect of segregation in Opinion Formation is neglectable.

  • Improving Opinion Formation Models on Social Media Through Emotions
    2019 5th International Conference on Web Research (ICWR), 2019
    Co-Authors: Alireza Mansouri, Fattaneh Taghiyareh, Javad Hatami
    Abstract:

    Opinion Formation models describe the Opinion dynamics of interacting people. Social media are drastically increasing and have become one of the most critical media for people interactions. According to psychological researches, one’s emotion diffuses across interacting people. Furthermore, emotion affects people’s Opinion. The emotion contagion also happens through social media via the users’ posts and affects the readers. Therefore, emotion is an essential element in Opinion Formation models in a social network which has attracted little attention. In this paper, we show how considering emotion in Opinion Formation model for online social networks improves the model. We have used a dataset containing some debates from the CreateDebate.com website. Two classifiers, with and without considering emotions, have been implemented based on the social impact model of Opinion Formation to predict the stances of the users’ next post in the dataset and the results have been compared with the dataset. The experiment results lead us to conclude that considering emotions improves the accuracy and precision of the social impact model of Opinion Formation in social media.

  • Toward an emotional Opinion Formation model through agent-based modeling
    2017 7th International Conference on Computer and Knowledge Engineering (ICCKE), 2017
    Co-Authors: Alireza Mansouri, Fattaneh Taghiyareh
    Abstract:

    In the last few decades, many Opinion Formation models have been proposed to describe how Opinion interactions among individuals result in different distributions of Opinions within social systems. Emotion plays a key role when people try to influence others' Opinions, but applying emotion to Opinion Formation models has attracted little attention. In this paper, we discuss how emotion can affect Opinion Formation in social systems. We have used the agent-based modeling and simulation approach due to the complexity of the system. For emotion modeling, we have used the circumplex model of affect, a dimensional model comprised of two dimensions: valence and arousal. The idea has been applied to the Deffuant basic Opinion Formation model, which is a continuous Opinion, nonlinear, and discrete time model. The simulation results of the model show how output parameters of the same Opinion Formation model such as convergence time, Opinion distribution, the number of resulting clusters, and the trend of Opinions approaching the final distribution of Opinions are affected by the emotional behavior of individuals. Therefore, the results lead us to conclude that considering emotional behavior alongside Opinion interaction rules could produce more realistic Opinion Formation models.

  • Introducing a more realistic model for Opinion Formation considering instability in social structure
    International Journal of Modern Physics C, 2016
    Co-Authors: Sajjad Salehi, Fattaneh Taghiyareh
    Abstract:

    Opinion Formation is a process through which interactions of individuals and dynamism of their Opinions in effect of neighbors are modeled. In this paper, in an effort to model the Opinion Formation more realistically, we have introduced a model that considers the role of network structure in Opinion dynamics. In this model, each individual changes his Opinion in a way so as to decrease its difference with the Opinion of trusted neighbors while he intensifies his dissention with the untrusted ones. Considering trust/distrust relations as a signed network, we have defined a structural indicator which shows the degree of instability in social structure and is calculated based on the structural balance theory. It is also applied as feedback to the Opinion Formation process affecting its dynamics. Our simulation results show Formation of a set of clusters containing individuals holding Opinions having similar values. Also, the Opinion value of each individual is far from the ones of distrusted neighbors. Since this model considers distrust and instability of relations in society, it can offer a more realistic model of Opinion Formation.

  • IST - An agent based positional model for Opinion Formation in social networks
    2016 8th International Symposium on Telecommunications (IST), 2016
    Co-Authors: Sajjad Salehi, Fattaneh Taghiyareh
    Abstract:

    Opinion leaders are individuals who have high confidence about their Opinions and high ability to impact on Opinion of other individuals named followers. In this paper we are going to introduce an agent based Opinion Formation model considering the leadership ability of social members. This ability is defined based on the position of agents in social structure. So each agent has a social status considering leadership ability. In our proposed model Opinion of each agent can be modified based on the Opinion of agents with higher status. By applying this model on two complete and scale free graphs, we have investigated the effect of Opinion leader in Opinion Formation process. The results of our work can be applicable in competitive environments that different parties try to change the social Opinion.

Marie-therese Wolfram - One of the best experts on this subject based on the ideXlab platform.

  • Opinion Formation in a Heterogenous Society
    New Economic Windows, 2011
    Co-Authors: Marie-therese Wolfram
    Abstract:

    Opinion Formation and Opinion leadership has attracted a lot of research among sociologists and physicists in the last decades. The first concept of Opinion leadership goes back to Lazarsfeld et al. [8] in 1944. Larzarsfeld et al. found out that during the presidential elections in 1940 interpersonal communication showed greater influence than direct media effects. In their theory of two-step flow communication Opinion leaders, who are activemedia users, select, modify and transmit inFormation from the media to the less active part of the community. In later models sociologists gained a different view of Opinion leadership by introducing the notion of public individuation. Public individuation describes how people want to differentiate and act differently from other people, see [9]. This attitude is a necessary prerequisite for an Opinion leader, since she or he has to stand out against the masses. Characteristic features of Opinion leaders are their high self esteem and confidence as well as their ability to withstand criticism. Although new technologies like the internet, blogs or instant messaging changed the way of communication and inFormation dissemination globally, Opinion leadership still plays a critical role in Opinion Formation processes.

  • Boltzmann and Fokker–Planck equations modelling Opinion Formation in the presence of strong leaders
    Proceedings of the Royal Society A: Mathematical Physical and Engineering Sciences, 2009
    Co-Authors: Bertram Düring, Peter A. Markowich, Jan-frederik Pietschmann, Marie-therese Wolfram
    Abstract:

    We propose a mathematical model for Opinion Formation in a society that is built of two groups, one group of `ordinary? people and one group of `strong Opinion leaders?. Our approach is based on an Opinion Formation model introduced in Toscani (Toscani 2006 Commun. Math. Sci.4, 481?496) and borrows ideas from the kinetic theory of mixtures of rarefied gases. Starting from microscopic interactions among individuals, we arrive at a macroscopic description of the Opinion Formation process that is characterized by a system of Fokker?Planck-type equations. We discuss the steady states of this system, extend it to incorporate emergence and decline of Opinion leaders and present numerical results.

  • Boltzmann and Fokker-Planck Equations Modelling Opinion Formation in the Presence of Strong Leaders
    SSRN Electronic Journal, 2009
    Co-Authors: Bertram Düring, Peter A. Markowich, Jan-frederik Pietschmann, Marie-therese Wolfram
    Abstract:

    We propose a mathematical model for Opinion Formation in a society which is built of two groups, one group of 'ordinary' people and one group of 'strong Opinion leaders'. Our approach is based on an Opinion Formation model introduced in Toscani (2006) and borrows ideas from the kinetic theory of mixtures of rarefied gases. Starting from microscopic interactions among individuals, we arrive at a macroscopic description of the Opinion Formation process which is characterized by a system of Fokker-Planck type equations. We discuss the steady states of this system, extend it to incorporate emergence and decline of Opinion leaders, and present numerical results.

Francisco J. Vázquez - One of the best experts on this subject based on the ideXlab platform.

  • A Dynamic Model of Public Opinion Formation
    Journal of Public Economic Theory, 2011
    Co-Authors: Francisco Fatas-villafranca, Dulce Saura, Francisco J. Vázquez
    Abstract:

    In this paper, we seek to shed new light on the social process of public Opinion Formation. Drawing on previous contributions in cognition studies and political science, we propose and analyze a model in which heterogeneous agents (citizens) collectively learn and modify their Opinions about a specific policy issue. The assumption of nonrationality on the part of agents gives core values, enduring general needs, social interaction, and the combination of the citizens´ intuition and occasional deliberate reasoning a key role in the dynamics of public Opinion Formation.