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1
Yunhong, Zhang, Liu Qipeng, Ding Lin, and Zhang Siying. "Opinion formation with time-varying bounded confidence related to the node degree." SIMULATION 95, no. 3 (July 3, 2018): 219–29. http://dx.doi.org/10.1177/0037549718784188.
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People like to communicate with others who have similar opinions in daily life. “Open” individuals are willing to accept peers’ opinions, whereas “conservative” individuals are more closed to others’ opinions. Based on this reality, an opinion dynamic model is proposed with a time-varying trust threshold related to the node degree, which refers to the number of individuals that can be communicated directly. Similar opinions within the trust thresholds at the beginning will eventually form a consensus opinion. Individuals who have common neighbors converge to consensus faster than ones who have no common neighbors. The network size impacts the convergent speed of the opinion cluster and the trust threshold cluster. Individuals in small groups are more stressed than in large ones when they try to insist their opinions. A group with half of the individuals categorized as doubting and the other half categorized as trusting exhibits consistent confidence but experiences difficulty in reaching a consensus: “harmony but difference” may be a criterion for unifying a group.
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., Pavani, U. V. Anbazhagu, Bhavadharani ., M. Latha, and J. Senthil. "Opinion Mining Embedding with Applications to Opinions." International Journal of Engineering & Technology 7, no. 3.27 (August 15, 2018): 192. http://dx.doi.org/10.14419/ijet.v7i3.27.17760.
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The main objective of this project, we portray strategies to consequently create and score another estimation vocabulary, called sentimental analysis. Sentimental analysis is the one of the real errands of machine learning processing. Individuals post their own emotions and contemplating any items for an internet business website, (for example, Amazon, Flip card etc).sometime individuals needs to know whether these posts are positive, negative or unbiased. Existing word inserting learning calculations regularly just utilize the settings of words yet disregard the assumption of writings. Now we are applying enclose to word level assumption and stepwise level supposition arrangement, and estimation vocabularies. Information utilized as a part of this study are online item data sets are gathered from amazon.com. Experiments for both sentence-level and word-level are performed.
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Amirjanov, Adil. "The cooperative and competitive mechanisms of a leader’s opinion transmission." International Journal of Modern Physics C 31, no. 09 (August 13, 2020): 2050127. http://dx.doi.org/10.1142/s0129183120501272.
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The paper modeled a leader’s opinion transmission in a population. The proposed model develops the cooperation agent-based continuous model in which the cooperation of individuals is based on the similarity of evolved “tags” which are relative to evolved tag-difference tolerances. In proposed model, an individual’s opinion and the individual’s tolerance are specified as variables in the model. During communication with each other and with a leader, the resources of individuals are incremented, if they are tolerable to the opinions of their opponents. An opinion formation in population is established by a cooperative process — changing individual’s opinion, if the individual is tolerable to the opinions of opponents, and by a competitive process — copying opinions and tolerances of successful individuals who have higher resource. Numerical experiments have proven that the public opinion reached a consensus followed the leader’s opinion.
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ALIZADEH, MEYSAM, CLAUDIO CIOFFI-REVILLA, and ANDREW CROOKS. "THE EFFECT OF IN-GROUP FAVORITISM ON THE COLLECTIVE BEHAVIOR OF INDIVIDUALS' OPINIONS." Advances in Complex Systems 18, no. 01n02 (February 2015): 1550002. http://dx.doi.org/10.1142/s0219525915500022.
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Empirical findings from social psychology show that sometimes people show favoritism toward in-group members in order to reach a global consensus, even against individuals' own preferences (e.g., altruistically or deontically). Here we integrate ideas and findings on in-group favoritism, opinion dynamics, and radicalization using an agent-based model entitled cooperative bounded confidence (CBC). We investigate the interplay of homophily, rejection, and in-group cooperation drivers on the formation of opinion clusters and the emergence of extremist, radical opinions. Our model is the first to explicitly explore the effect of in-group favoritism on the macro-level, collective behavior of opinions. We compare our model against the two-dimentional bounded confidence model with rejection mechanism, proposed by Huet et al. [Adv. Complex Syst.13(3) (2010) 405–423], and find that the number of opinion clusters and extremists is reduced in our model. Moreover, results show that group influence can never dominate homophilous and rejecting encounters in the process of opinion cluster formation. We conclude by discussing implications of our model for research on collective behavior of opinions emerging from individuals' interaction.
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Li, Zhifang, Xiaojie Chen, Han-Xin Yang, and Attila Szolnoki. "Game-theoretical approach for opinion dynamics on social networks." Chaos: An Interdisciplinary Journal of Nonlinear Science 32, no. 7 (July 2022): 073117. http://dx.doi.org/10.1063/5.0084178.
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Opinion dynamics on social networks have received considerable attentions in recent years. Nevertheless, just a few works have theoretically analyzed the condition in which a certain opinion can spread in the whole structured population. In this article, we propose an evolutionary game approach for a binary opinion model to explore the conditions for an opinion’s spreading. Inspired by real-life observations, we assume that an agent’s choice to select an opinion is not random but is based on a score rooted from both public knowledge and the interactions with neighbors. By means of coalescing random walks, we obtain a condition in which opinion [Formula: see text] can be favored to spread on social networks in the weak selection limit. We find that the successfully spreading condition of opinion [Formula: see text] is closely related to the basic scores of binary opinions, the feedback scores on opinion interactions, and the structural parameters including the edge weights, the weighted degrees of vertices, and the average degree of the network. In particular, when individuals adjust their opinions based solely on the public information, the vitality of opinion [Formula: see text] depends exclusively on the difference of basic scores of [Formula: see text] and [Formula: see text]. When there are no negative (positive) feedback interactions between connected individuals, we find that the success of opinion [Formula: see text] depends on the ratio of the obtained positive (negative) feedback scores of competing opinions. To complete our study, we perform computer simulations on fully connected, small-world, and scale-free networks, respectively, which support and confirm our theoretical findings.
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WU, YUE, YONG HU, and XIAO-HAI HE. "PUBLIC OPINION FORMATION MODEL BASED ON OPINION ENTROPY." International Journal of Modern Physics C 24, no. 11 (October 14, 2013): 1350080. http://dx.doi.org/10.1142/s0129183113500800.
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In this paper, we introduce the concept of opinion entropy based on Shannon entropy, which is used to describe the uncertainty of opinions. With opinion entropy, we further present a public opinion formation model, and simulate the process of public opinion formation under various controlled conditions. Simulation results on the Holme–Kim network show that the opinion entropy will reduce to zero, and all individuals will hold the opinion of agreeing with the topic, only by adjusting the cons' opinions with a high control intensity. Controlling the individuals with big degree can bring down the opinion entropy in a short time. Besides, extremists do not easily change their opinion entropy. Compared with previous opinion clusters, opinion entropy provides a quantitative measurement for the uncertainty of opinions. Moreover, the model can be helpful for understanding the dynamics of opinion entropy, and controlling the public opinion.
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Moharir, Sharayu, Ananya S. Omanwar, and Neeraja Sahasrabudhe. "Diffusion of binary opinions in a growing population with heterogeneous behaviour and external influence." Networks and Heterogeneous Media 18, no. 3 (2023): 1288–312. http://dx.doi.org/10.3934/nhm.2023056.
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<abstract><p>We consider a growing population of individuals with binary opinions, namely, 0 or 1, that evolve in discrete time. The underlying interaction network is complete. At every time step, a fixed number of individuals are added to the population. The opinion of the new individuals may or may not depend on the current configuration of opinions in the population. Further, in each time step, a fixed number of individuals are chosen and they update their opinion in three possible ways: they organically switch their opinion with some probability and with some probability they adopt the majority or the minority opinion. We study the asymptotic behaviour of the fraction of individuals with either opinion and characterize conditions under which it converges to a deterministic limit. We analyze the behaviour of the limiting fraction as a function of the probability of new individuals having opinion 1 as well as with respect to the ratio of the number of people being added to the population and the number of people being chosen to update opinions. We also discuss the nature of fluctuations around the limiting fraction and study the transitions in scaling depending on the system parameters. Further, for this opinion dynamics model on a finite time horizon, we obtain optimal external influencing strategies in terms of when to influence to get the maximum expected fraction of individuals with opinion 1 at the end of the finite time horizon.</p></abstract>
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Bradley, R., and C. Wagner. "REALISTIC OPINION AGGREGATION: LEHRER-WAGNER WITH A FINITE SET OF OPINION VALUES." Episteme 9, no. 2 (June 2012): 91–99. http://dx.doi.org/10.1017/epi.2012.2.
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AbstractAn allocation problem is a type of aggregation problem in which the values of individuals' opinions on some set of variables (canonically a set of mutually exclusive and exhaustive possibilities) sum to a constant. This paper shows that for realistic allocation problems, namely ones in which the set of possible opinion values is finite, the only universal aggregation methods that satisfy two commonly invoked conditions are the dictatorial ones. The two conditions are, first, that the aggregate opinion on any variable depends only on the individuals' opinions on that variable and not on their opinions on any other variable and, secondly, that the aggregate opinion minimally preserves unanimous individual opinion. Connections between this result and similar ones in the literature on judgment aggregation are explored and their significance assessed.
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JIA, FAN, and DI XIE. "DEMPSTER–SHAFER EVIDENCE THEORY-BASED UPDATING RULE FOR CONTINUOUS OPINIONS AND DISCRETE ACTIONS." International Journal of Modern Physics C 22, no. 06 (June 2011): 595–606. http://dx.doi.org/10.1142/s0129183111016476.
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The opinion of an individual about a given problem is determined by the quantity and the degree of certainty of knowledge mastered by the individual. The knowledge and information from other individuals might bring some conflicts with the individual's internal knowledge, which would make the individual become uncertain about its opinion. Based on Dempster–Shafer (D–S) evidence theory, a new opinion updating rule is proposed for individuals to form their opinion as the process of reasoning from the internal or the external knowledge in real life. Many computer simulations are conducted under different situations. It is found that the common phenomena such as consensus, fragment opinions can be observed among the individuals on square lattices during the evolution of opinion, and that information is spread from the higher certainty to the lower certainty, and the influence of opinion leaders become weaken during the spread of information, and the range of influence is determined by the threshold of individual acceptance of uncertainty of information.
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Ozpulat, Funda, Fatma Yagmur Bulut, and Merve Kor. "University students' opinions on LGBT individuals." International Journal of New Trends in Social Sciences 1, no. 2 (December 6, 2017): 23–32. http://dx.doi.org/10.18844/ijss.v1i2.2768.
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Bu çalışma, üniversite öğrencilerinin lezbiyen, gay, biseksüel ve transeksüel (LGBT) bireyler hakkındaki görüşlerini saptamayı amaçlayan tanımlayıcı bir araştırmadır. 18 Nisan - 11 Mayıs 2016 tarihleri arasında 600 öğrencinin katılımı ile yürütülen çalışmada veri toplama aracı olarak, araştırmacı tarafından geliştirilen ve 2 bölümden oluşan anket formu kullanılmıştır. Elde edilen veriler SPSS paket programı kullanılarak değerlendirilmiş, verilerin yüzdeler ve sayılarla değerlendirilmesi yanı sıra, Ki-Kare hesaplaması yapılmıştır. Araştırmaya katılanların %68.3’ü kadınlardan oluşmakta, %77.3’ü 17-21 yaş aralığında bulunmaktadır. %81.7’sinin ailesi çekirdek ailedir. Araştırma sonunda, LGBT bireylerin, kendilerini özgürce ifade etmesi, LGBT bireylere devlet tarafından kanunlarca haklar verilmesi, LGBT bireylerin sözlü veya fiziksel şiddete maruz kalmasıyla ilgili ifadelere verilen cevapların katılımcıların cinsiyetine göre değiştiği ve erkeklerin daha yüksek oranlarla olumsuz cevaplar verdikleri saptanmıştır. Anahtar Kelimeler: Üniversite öğrencileri, lezbiyen, gay, biseksüel, transeksüel, katılımcı görüşleri
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Zhang, Yaofeng, and Renbin Xiao. "Modeling and Simulation of Polarization in Internet Group Opinions Based on Cellular Automata." Discrete Dynamics in Nature and Society 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/140984.
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Hot events on Internet always attract many people who usually form one or several opinion camps through discussion. For the problem of polarization in Internet group opinions, we propose a new model based on Cellular Automata by considering neighbors, opinion leaders, and external influences. Simulation results show the following: (1) It is easy to form the polarization for both continuous opinions and discrete opinions when we only consider neighbors influence, and continuous opinions are more effective in speeding the polarization of group. (2) Coevolution mechanism takes more time to make the system stable, and the global coupling mechanism leads the system to consensus. (3) Opinion leaders play an important role in the development of consensus in Internet group opinions. However, both taking the opinion leaders as zealots and taking some randomly selected individuals as zealots are not conductive to the consensus. (4) Double opinion leaders with consistent opinions will accelerate the formation of group consensus, but the opposite opinions will lead to group polarization. (5) Only small external influences can change the evolutionary direction of Internet group opinions.
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Peng, Kaiyan, Zheng Lu, Vanessa Lin, Michael R. Lindstrom, Christian Parkinson, Chuntian Wang, Andrea L. Bertozzi, and Mason A. Porter. "A multilayer network model of the coevolution of the spread of a disease and competing opinions." Mathematical Models and Methods in Applied Sciences 31, no. 12 (November 2021): 2455–94. http://dx.doi.org/10.1142/s0218202521500536.
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During the COVID-19 pandemic, conflicting opinions on physical distancing swept across social media, affecting both human behavior and the spread of COVID-19. Inspired by such phenomena, we construct a two-layer multiplex network for the coupled spread of a disease and conflicting opinions. We model each process as a contagion. On one layer, we consider the concurrent evolution of two opinions — pro-physical-distancing and anti-physical-distancing — that compete with each other and have mutual immunity to each other. The disease evolves on the other layer, and individuals are less likely (respectively, more likely) to become infected when they adopt the pro-physical-distancing (respectively, anti-physical-distancing) opinion. We develop approximations of mean-field type by generalizing monolayer pair approximations to multilayer networks; these approximations agree well with Monte Carlo simulations for a broad range of parameters and several network structures. Through numerical simulations, we illustrate the influence of opinion dynamics on the spread of the disease from complex interactions both between the two conflicting opinions and between the opinions and the disease. We find that lengthening the duration that individuals hold an opinion may help suppress disease transmission, and we demonstrate that increasing the cross-layer correlations or intra-layer correlations of node degrees may lead to fewer individuals becoming infected with the disease.
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Moorthi N, Prasanna, and Mathivanan V. "An improved wrapper-based feature selection for efficient opinion mining." International Journal of Engineering & Technology 7, no. 1.3 (December 31, 2017): 140. http://dx.doi.org/10.14419/ijet.v7i1.3.10659.
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Opinion mining analyses people’s opinions, evaluations, sentiments, attitudes, appraisals and emotions to entities like products, organizations, services, issues, individuals, topics, events and their attributes. It is a large problem space having high feature dimensionality. Feature extraction is important in opinion mining as customers do not usually express product opinions totally, but separately based on individual features. Two tasks should be accomplished in feature-based opinion mining. First, product features on which reviewers expressed opinions must be identified and extracted. Second, opinion orientation or polarities must be determined. Finally, opinion mining summarizes extracted features and opinions. In this work a novel wrapper based feature selection mechanism using concept based feature expansion is proposed. The wrapper based technique uses the principles of evolutionary algorithms.
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Dachi, Adliano Dino, and Khalid Khalid. "Hak Warga Negara dalam Menyampaikan Kebebasan Berpendapat Berdasarkan Peraturan Perundang-Undangan Perspektif Fiqh Siyasah." As-Syar'i: Jurnal Bimbingan & Konseling Keluarga 6, no. 2 (July 14, 2024): 2250–57. http://dx.doi.org/10.47467/as.v6i2.7075.
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Freedom of speech is one of the most important human rights. Freedom of opinion requires individuals to express opinions and opinions without fear of retaliation or punishment from the government or other entities. The important role of freedom of opinion is closely related to human rights in ensuring an open and democratic political system and can help in fighting for other human rights. In this research, it will examine more deeply about freedom of opinion based on laws and regulations that aim to achieve the right of freedom in expressing opinions on something reviewed from Law Number 9 of 1998 concerning Freedom to Express Opinions in Public with the perspective of Fiqh Siyasah and Maqashid Syari'ah. Keywords: Opinion, Human Rights, Fiqh Siyasah
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LIU, JIAN-GUO, ZHI-XI WU, and FENG WANG. "OPINION SPREADING AND CONSENSUS FORMATION ON SQUARE LATTICE." International Journal of Modern Physics C 18, no. 07 (July 2007): 1087–94. http://dx.doi.org/10.1142/s0129183107011145.
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In this paper, we study a model of opinion spreading and consensus formation on a square lattice. Given a two-dimensional square lattice with periodic boundary condition, a total fraction p of the sites are occupied by agents. We take into account the drift ability of the focal agents whose opinions' difference is too large. The dynamics of the model is governed by the following two rules. At each time step, the agents (or individuals) can exchange their opinions with those of their neighbors if the difference between them is smaller than the "bounded confidence" ∊; Otherwise, one can move to a vacancy location if permitted (i.e., there are any empty sites existing among the focal agent's neighborhood). The distribution of opinions over the population evolves toward either a consensus state that all individuals share the same opinion or polarization and fragmentation states where two or more opinions can coexist. The statistical properties of this final state vary considerably as the parameters p and ∊ change. It is shown that, when dispersal abilities of the individuals are considered, the bounded confidence which is required to attain consensus can be remarkably decreased.
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Druckman, James N., and Thomas J. Leeper. "Is Public Opinion Stable? Resolving the Micro/Macro Disconnect in Studies of Public Opinion." Daedalus 141, no. 4 (October 2012): 50–68. http://dx.doi.org/10.1162/daed_a_00173.
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Public opinion matters, both as a central element of democratic theory and as a substantive foundation for political representation. The origins and nature of public opinion have long attracted the attention of social scientists. Yet a number of questions remain; among the more perplexing is whether–and under what conditions–public opinion is stable. The answer depends in large part on whether one looks at aggregations of individual opinions (macro public opinion) or at the individual opinions themselves (micro public opinion). In this essay, we explore the macro/micro divide and offer a framework to determine when opinions are likely to be stable or volatile. This framework reflects both the content of the political environment and the nature of individuals' opinions. Using public opinion dynamics surrounding the Patriot Act as a primary example, we discuss the role of opinion stability in interpreting public opinion and in understanding the normative implications of public preferences.
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Chen, Xi, Panayiotis Tsaparas, Jefrey Lijffijt, and Tijl De Bie. "Opinion dynamics with backfire effect and biased assimilation." PLOS ONE 16, no. 9 (September 1, 2021): e0256922. http://dx.doi.org/10.1371/journal.pone.0256922.
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The democratization of AI tools for content generation, combined with unrestricted access to mass media for all (e.g. through microblogging and social media), makes it increasingly hard for people to distinguish fact from fiction. This raises the question of how individual opinions evolve in such a networked environment without grounding in a known reality. The dominant approach to studying this problem uses simple models from the social sciences on how individuals change their opinions when exposed to their social neighborhood, and applies them on large social networks. We propose a novel model that incorporates two known social phenomena: (i) Biased Assimilation: the tendency of individuals to adopt other opinions if they are similar to their own; (ii) Backfire Effect: the fact that an opposite opinion may further entrench people in their stances, making their opinions more extreme instead of moderating them. To the best of our knowledge, this is the first DeGroot-type opinion formation model that captures the Backfire Effect. A thorough theoretical and empirical analysis of the proposed model reveals intuitive conditions for polarization and consensus to exist, as well as the properties of the resulting opinions.
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Ito, Mariko I., and Akira Sasaki. "Casting votes of antecedents play a key role in successful sequential decision-making." PLOS ONE 18, no. 2 (February 24, 2023): e0282062. http://dx.doi.org/10.1371/journal.pone.0282062.
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Aggregation of opinions often results in high decision-making accuracy, owing to the collective intelligence effect. Studies on group decisions have examined the optimum weights for opinion aggregation to maximise accuracy. In addition to the optimum weights of opinions, the impact of the correlation among opinions on collective intelligence is a major issue in collective decision-making. We investigated how individuals should weigh the opinions of others and their own to maximise their accuracy in sequential decision-making. In our sequential decision-making model, each person makes a primary choice, observes his/her predecessors’ opinions, and makes a final choice, which results in the person’s answer correlating with those of others. We developed an algorithm to find casting voters whose primary choices are determinative of their answers and revealed that decision accuracy is maximised by considering only the abilities of the preceding casting voters. We also found that for individuals with heterogeneous abilities, the order of decision-making has a significant impact on the correlation between their answers and their accuracies. This could lead to a counter-intuitive phenomenon whereby, in sequential decision-making, respondents are, on average, more accurate when less reliable individuals answer earlier and more reliable individuals answer later.
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Chen, Xi, Xiao Zhang, Yong Xie, and Wei Li. "Opinion Dynamics of Social-Similarity-Based Hegselmann–Krause Model." Complexity 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/1820257.
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The existing opinion dynamics models mainly concentrate on the impact of opinions on other opinions and ignore the effect of the social similarity between individuals. Social similarity between an individual and their neighbors will also affect their opinions in real life. Therefore, an opinion evolution model considering social similarity (social-similarity-based HK model, SSHK model for short) is introduced in this paper. Social similarity is calculated using individual properties and is used to measure the social relationship between individuals. By considering the joint effect of confidence bounds and social similarity in this model, the role of neighbors’ selection is changed significantly in the process of the evolution of opinions. Numerical results demonstrate that the new model can not only obtain the salient features of the opinion result, namely, fragmentation, polarization, and consensus, but also achieve consensus more easily under the appropriate similarity threshold. In addition, the improved model with heterogeneous and homogeneous confidence bounds and similarity thresholds are also discussed. We found that the improved heterogeneous SSHK model could acquire opinion consensus results more easily than the homogeneous SSHK model and the classical models when the confidence bound was related to the similarity threshold. This finding provides a new way of thinking and a theoretical basis for the guidance of public opinion in real life.
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Gezha, Vladislav N., and Ivan V. Kozitsin. "The Effects of Individuals’ Opinion and Non-Opinion Characteristics on the Organization of Influence Networks in the Online Domain." Computers 12, no. 6 (June 2, 2023): 116. http://dx.doi.org/10.3390/computers12060116.
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The opinion dynamics literature argues that the way people perceive social influence depends not only on the opinions of interacting individuals, but also on the individuals’ non-opinion characteristics, such as age, education, gender, or place of residence. The current paper advances this line of research by studying longitudinal data that describe the opinion dynamics of a large sample (~30,000) of online social network users, all citizens of one city. Using these data, we systematically investigate the effects of users’ demographic (age, gender) and structural (degree centrality, the number of common friends) properties on opinion formation processes. We revealed that females are less easily influenced than males. Next, we found that individuals that are characterized by similar ages have more chances to reach a consensus. Additionally, we report that individuals who have many common peers find an agreement more often. We also demonstrated that the impacts of these effects are virtually the same, and despite being statistically significant, are far less strong than that of opinion-related features: knowing the current opinion of an individual and, what is even more important, the distance in opinions between this individual and the person that attempts to influence the individual is much more valuable. Next, after conducting a series of simulations with an agent-based model, we revealed that accounting for non-opinion characteristics may lead to not very sound but statistically significant changes in the macroscopic predictions of the populations of opinion camps, primarily among the agents with radical opinions (≈3% of all votes). In turn, predictions for the populations of neutral individuals are virtually the same. In addition, we demonstrated that the accumulative effect of non-opinion features on opinion dynamics is seriously moderated by whether the underlying social network correlates with the agents’ characteristics. After applying the procedure of random shuffling (in which the agents and their characteristics were randomly scattered over the network), the macroscopic predictions have changed by ≈9% of all votes. What is interesting is that the population of neutral agents was again not affected by this intervention.
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Chistikov, Dmitry, Grzegorz Lisowski, Mike Paterson, and Paolo Turrini. "Convergence of Opinion Diffusion is PSPACE-Complete." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 7103–10. http://dx.doi.org/10.1609/aaai.v34i05.6197.
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We analyse opinion diffusion in social networks, where a finite set of individuals is connected in a directed graph and each simultaneously changes their opinion to that of the majority of their influencers. We study the algorithmic properties of the fixed-point behaviour of such networks, showing that the problem of establishing whether individuals converge to stable opinions is PSPACE-complete.
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Yedomonhan, Elodie, Chénangnon Frédéric Tovissodé, and Romain Glèlè Kakaï. "Modeling the effects of Prophylactic behaviors on the spread of SARS-CoV-2 in West Africa." Mathematical Biosciences and Engineering 20, no. 7 (2023): 12955–89. http://dx.doi.org/10.3934/mbe.2023578.
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<abstract><p>Various general and individual measures have been implemented to limit the spread of SARS-CoV-2 since its emergence in China. Several phenomenological and mechanistic models have been developed to inform and guide health policy. Many of these models ignore opinions about certain control measures, although various opinions and attitudes can influence individual actions. To account for the effects of prophylactic opinions on disease dynamics and to avoid identifiability problems, we expand the SIR-Opinion model of Tyson et al. (2020) to take into account the partial detection of infected individuals in order to provide robust modeling of COVID-19 as well as degrees of adherence to prophylactic treatments, taking into account a hybrid modeling technique using Richard's model and the logistic model. Applying the approach to COVID-19 data from West Africa demonstrates that the more people with a strong prophylactic opinion, the smaller the final COVID-19 pandemic size. The influence of individuals on each other and from the media significantly influences the susceptible population and, thus, the dynamics of the disease. Thus, when considering the opinion of susceptible individuals to the disease, the view of the population at baseline influences its dynamics. The results are expected to inform public policy in the context of emerging and re-emerging infectious diseases.</p></abstract>
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Salehi, Sajjad, and Fattaneh Taghiyareh. "Introducing a more realistic model for opinion formation considering instability in social structure." International Journal of Modern Physics C 27, no. 11 (August 29, 2016): 1650136. http://dx.doi.org/10.1142/s0129183116501369.
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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.
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Ye, Yuanjian, Renjie Zhang, Yiqing Zhao, Yuanyuan Yu, Wenxin Du, and Tinggui Chen. "A Novel Public Opinion Polarization Model Based on BA Network." Systems 10, no. 2 (April 9, 2022): 46. http://dx.doi.org/10.3390/systems10020046.
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At present, the polarization of online public opinion is becoming more frequent, and individuals actively participate in attitude interactions more and more frequently. Thus, online views have become the dominant force in current public opinion. However, the rapid fermentation of polarized public opinion makes it very easy for actual topic views to go to extremes. Significantly, negative information seriously affects the healthy development of the social opinion ecology. Therefore, it is beneficial to maintain national credibility, social peace, and stability by exploring the communication structure of online public opinions, analyzing the logical model of extreme public attitudes, and guiding the communication of public opinions in a timely and reasonable manner. Starting from the J–A model and BA network, this paper explores the specific attributes of individuals and opinion network nodes. By incorporating parameters such as individual conformity and the strength of individual online relationships, we established a model of online group attitude polarization, then conducted simulation experiments on the phenomenon of online opinion polarization. Through simulations, we found that individual conformity and the difference in environmental attitude greatly influence the direction of opinion polarization events. In addition, crowd mentality makes individuals spontaneously choose the side of a particular, extreme view, which makes it easier for polarization to form and reach its peak.
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Peralta, Antonio F., János Kertész, and Gerardo Iñiguez. "Opinion formation on social networks with algorithmic bias: dynamics and bias imbalance." Journal of Physics: Complexity 2, no. 4 (November 16, 2021): 045009. http://dx.doi.org/10.1088/2632-072x/ac340f.
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Abstract We investigate opinion dynamics and information spreading on networks under the influence of content filtering technologies. The filtering mechanism, present in many online social platforms, reduces individuals’ exposure to disagreeing opinions, producing algorithmic bias. We derive evolution equations for global opinion variables in the presence of algorithmic bias, network community structure, noise (independent behavior of individuals), and pairwise or group interactions. We consider the case where the social platform shows a predilection for one opinion over its opposite, unbalancing the dynamics in favor of that opinion. We show that if the imbalance is strong enough, it may determine the final global opinion and the dynamical behavior of the population. We find a complex phase diagram including phases of coexistence, consensus, and polarization of opinions as possible final states of the model, with phase transitions of different order between them. The fixed point structure of the equations determines the dynamics to a large extent. We focus on the time needed for convergence and conclude that this quantity varies within a wide range, showing occasionally signatures of critical slowing down and meta-stability.
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Moe, Wendy W., and David A. Schweidel. "Positive, Negative or Not at All? What Drives Consumers to Post (Accurate) Product Reviews?" NIM Marketing Intelligence Review 5, no. 2 (November 1, 2013): 8–12. http://dx.doi.org/10.2478/gfkmir-2014-0011.
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Abstract Online consumer reviews are a convenient, valuable pool of information for potential buyers as well as for marketers. But how reliable is this information? A closer look at the motives behind posted product reviews shows that online opinions should indeed be interpreted with care. The study results reveal that the composition of the customer base can exert a substantial influence on the posted online opinion. Due to selection bias and adjustment effects over time, the content posted may not necessarily reflect the customer base’s overall opinion of the product. Individuals were more likely to submit ratings when they were either very satisfied or not satisfied. In addition, consumers were more likely to post an opinion when the ratings already posted were more positive. Highly engaged consumers who frequently post their opinions tend to be more negative than less-engaged individuals. Even though decision-makers can gain valuable insights from the analysis of this pool of information, they should not rely on this source exclusively.
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Sadeghi, Atiyeh, Sebastian Pape, and David Harborth. "The Impact of Individuals’ Social Environments on Contact Tracing App Use: Survey Study." JMIR Human Factors 10 (May 31, 2023): e45825. http://dx.doi.org/10.2196/45825.
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Background The German Corona-Warn-App (CWA) is a contact tracing app to mitigate the spread of SARS-CoV-2. As of today, it has been downloaded approximately 45 million times. Objective This study aims to investigate the influence of (non)users’ social environments on the usage of the CWA during 2 periods with relatively lower death rates and higher death rates caused by SARS-CoV-2. Methods We conducted a longitudinal survey study in Germany with 833 participants in 2 waves to investigate how participants perceive their peer groups’ opinion about making use of the German CWA to mitigate the risk of SARS-CoV-2. In addition, we asked whether this perceived opinion, in turn, influences the participants with respect to their own decision to use the CWA. We analyzed these questions with generalized estimating equations. Further, 2 related sample tests were performed to test for differences between users of the CWA and nonusers and between the 2 points in time (wave 1 with the highest death rates observable during the pandemic in Germany versus wave 2 with significantly lower death rates). Results Participants perceived that peer groups have a positive opinion toward using the CWA, with more positive opinions by the media, family doctors, politicians, and virologists/Robert Koch Institute and a lower, only slightly negative opinion originating from social media. Users of the CWA perceived their peer groups’ opinions about using the app as more positive than nonusers do. Furthermore, the perceived positive opinion of the media (P=.001) and politicians (P<.001) was significantly lower in wave 2 compared with that in wave 1. The perceived opinion of friends and family (P<.001) as well as their perceived influence (P=.02) among nonusers toward using the CWA was significantly higher in the latter period compared with that in wave 1. The influence of virologists (in Germany primarily communicated via the Robert Koch Institute) had the highest positive effect on using the CWA (B=0.363, P<.001). We only found 1 decreasing effect of the influence of politicians (B=–0.098, P=.04). Conclusions Opinions of peer groups play an important role when it comes to the adoption of the CWA. Our results show that the influence of virologists/Robert Koch Institute and family/friends exerts the strongest effect on participants’ decisions to use the CWA while politicians had a slightly negative influence. Our results also indicate that it is crucial to accompany the introduction of such a contact tracing app with explanations and a media campaign to support its adoption that is backed up by political decision makers and subject matter experts.
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Kumar, Ravindra. "Methods to Perform Opinion Mining and Sentiment Analysis to Detect Factors Affecting Mental Health." International Journal of Engineering and Advanced Technology 11, no. 1 (October 30, 2021): 70–72. http://dx.doi.org/10.35940/ijeat.f3025.1011121.
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Sentimental analysis and opinion extraction are emerging fields at AI. These approaches help organizations to use the opinions, sentiments, and subjectivity of their consumers in decision-making. Sentiments, views, and opinions show the feeling of the consumers towards a given product or service. In recent years, Opinion Mining and Sentiment Analysis has become an important tool to detect the factors affecting mental health. It’s Also true that human biasness is available in giving opinions, but it can be eliminated through the use of algorithms to get better results. However, it is crucial to remember that the developers are human and might pass the biasness to the algorithms during training. The main target of this paper is to give background knowledge on opinion extraction and sentimental analysis and how factors affecting mental health can be collected. The paper aimed to use interested individuals in knowing some of the algorithms in opinions extraction and sentimental analysis. The paper also provides benefits of using sentiment analysis and some of the challenges of using the algorithms.
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Lanchier, N., and N. Taylor. "Galam's bottom-up hierarchical system and public debate model revisited." Advances in Applied Probability 47, no. 3 (September 2015): 668–92. http://dx.doi.org/10.1239/aap/1444308877.
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This paper is concerned with the bottom-up hierarchical system and public debate model proposed by Galam (2008), as well as a spatial version of the public debate model. In all three models, there is a population of individuals who are characterized by one of two competing opinions, say opinion −1 and opinion +1. This population is further divided into groups of common size s. In the bottom-up hierarchical system, each group elects a representative candidate, whereas in the other two models, all the members of each group discuss at random times until they reach a consensus. At each election/discussion, the winning opinion is chosen according to Galam's majority rule: the opinion with the majority of representatives wins when there is a strict majority, while one opinion, say opinion −1, is chosen by default in the case of a tie. For the public debate models we also consider the following natural updating rule that we call proportional rule: the winning opinion is chosen at random with a probability equal to the fraction of its supporters in the group. The three models differ in term of their population structure: in the bottom-up hierarchical system, individuals are located on a finite regular tree, in the nonspatial public debate model, they are located on a complete graph, and in the spatial public debate model, they are located on the d-dimensional regular lattice. For the bottom-up hierarchical system and nonspatial public debate model, Galam studied the probability that a given opinion wins under the majority rule and, assuming that individuals' opinions are initially independent, making the initial number of supporters of a given opinion a binomial random variable. The first objective of this paper is to revisit Galam's result, assuming that the initial number of individuals in favor of a given opinion is a fixed deterministic number. Our analysis reveals phase transitions that are sharper under our assumption than under Galam's assumption, particularly with small population size. The second objective is to determine whether both opinions can coexist at equilibrium for the spatial public debate model under the proportional rule, which depends on the spatial dimension.
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Lanchier, N., and N. Taylor. "Galam's bottom-up hierarchical system and public debate model revisited." Advances in Applied Probability 47, no. 03 (September 2015): 668–92. http://dx.doi.org/10.1017/s0001867800048783.
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This paper is concerned with the bottom-up hierarchical system and public debate model proposed by Galam (2008), as well as a spatial version of the public debate model. In all three models, there is a population of individuals who are characterized by one of two competing opinions, say opinion −1 and opinion +1. This population is further divided into groups of common size s. In the bottom-up hierarchical system, each group elects a representative candidate, whereas in the other two models, all the members of each group discuss at random times until they reach a consensus. At each election/discussion, the winning opinion is chosen according to Galam's majority rule: the opinion with the majority of representatives wins when there is a strict majority, while one opinion, say opinion −1, is chosen by default in the case of a tie. For the public debate models we also consider the following natural updating rule that we call proportional rule: the winning opinion is chosen at random with a probability equal to the fraction of its supporters in the group. The three models differ in term of their population structure: in the bottom-up hierarchical system, individuals are located on a finite regular tree, in the nonspatial public debate model, they are located on a complete graph, and in the spatial public debate model, they are located on the d-dimensional regular lattice. For the bottom-up hierarchical system and nonspatial public debate model, Galam studied the probability that a given opinion wins under the majority rule and, assuming that individuals' opinions are initially independent, making the initial number of supporters of a given opinion a binomial random variable. The first objective of this paper is to revisit Galam's result, assuming that the initial number of individuals in favor of a given opinion is a fixed deterministic number. Our analysis reveals phase transitions that are sharper under our assumption than under Galam's assumption, particularly with small population size. The second objective is to determine whether both opinions can coexist at equilibrium for the spatial public debate model under the proportional rule, which depends on the spatial dimension.
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Bashari, Masoud, and M. R. Akbarzadeh-T. "Modeling Opinion Formation in Social Networks: A Probabilistic Fuzzy Approach." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, no. 01 (February 2020): 99–116. http://dx.doi.org/10.1142/s0218488520500051.
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Opinion formation in social networks is an interesting dynamical process from the perspective of system modeling due to its large scale as well as the variety of structural and parametric uncertainties that it entails. This paper proposes a probabilistic fuzzy opinion formation model for predicting the opinions of communities in the social networks. In this regard, the opinions of a group of individuals about a given topic in a Telegram pilot group, as a popular social network, are collected and presented in the framework of the probabilistic fuzzy model. Based on the obtained data, the parameters of the model are extracted, and the model is tuned. Finally, the variations of the actual opinions throughout time are compared with the model predictions. The numerical results in this study show that, with appropriately tuned parameters, the model successfully represents the opinion formation process, with an average error that approaches zero.
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Banisch, Sven, Felix Gaisbauer, and Eckehard Olbrich. "Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others." Entropy 24, no. 10 (October 18, 2022): 1484. http://dx.doi.org/10.3390/e24101484.
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What are the mechanisms by which groups with certain opinions gain public voice and force others holding a different view into silence? Furthermore, how does social media play into this? Drawing on neuroscientific insights into the processing of social feedback, we develop a theoretical model that allows us to address these questions. In repeated interactions, individuals learn whether their opinion meets public approval and refrain from expressing their standpoint if it is socially sanctioned. In a social network sorted around opinions, an agent forms a distorted impression of public opinion enforced by the communicative activity of the different camps. Even strong majorities can be forced into silence if a minority acts as a cohesive whole. On the other hand, the strong social organisation around opinions enabled by digital platforms favours collective regimes in which opposing voices are expressed and compete for primacy in public. This paper highlights the role that the basic mechanisms of social information processing play in massive computer-mediated interactions on opinions.
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PERONY, NICOLAS, RENÉ PFITZNER, INGO SCHOLTES, CLAUDIO J. TESSONE, and FRANK SCHWEITZER. "ENHANCING CONSENSUS UNDER OPINION BIAS BY MEANS OF HIERARCHICAL DECISION MAKING." Advances in Complex Systems 16, no. 06 (August 2013): 1350020. http://dx.doi.org/10.1142/s0219525913500203.
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We study the role of hierarchical structures in a simple model of collective consensus formation based on the bounded confidence model with continuous individual opinions. For the particular variation of this model considered in this paper, we assume that a bias toward an extreme opinion is introduced whenever two individuals interact and form a common decision. As a simple proxy for hierarchical social structures, we introduce a two-step decision making process in which in the second step groups of like-minded individuals are replaced by representatives once they have reached local consensus, and the representatives in turn form a collective decision in a downstream process. We find that the introduction of such a hierarchical decision making structure can improve consensus formation, in the sense that the eventual collective opinion is closer to the true average of individual opinions than without it. In particular, we numerically study how the size of groups of like-minded individuals being represented by delegate individuals affects the impact of the bias on the final population-wide consensus. These results are of interest for the design of organizational policies and the optimization of hierarchical structures in the context of group decision making.
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Dai, Zexing, Zhiming Fang, and Gang Zhu. "The Robust Asymmetric Minimum Cost Consensus Models with Interval-type Opinions." Information Technology and Control 53, no. 4 (December 21, 2024): 1088–100. https://doi.org/10.5755/j01.itc.53.4.37622.
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Existing consensus models primarily rely on precise opinions from decision-makers in a predefined context, neglecting the dynamics of expert opinion adjustments. To address this limitation, we introduce the interval-type opinions and explores the group decision consensus model under asymmetric adjustment cost from an uncertainty perspective. Then, the robust optimization theory is applied to adress the uncertainty in adjustment costs of decision-making individuals. The robust asymmetric cost consensus model of interval opinions under three uncertain scenarios is built. Finally, the validity of proposed model is verified by numerical calculations, and a sensitivity analysis and comparative study are performed. The results show that: (1) Utilizing interval opinions can significantly reduce consensus costs when compared to precise opinions; (2) Comprehensively comparing the three proposed robust models, the consensus model with budget asymmetric cost has the best performance.
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Xiao, Renbin, Tongyang Yu, and Jundong Hou. "Modeling and Simulation of Opinion Natural Reversal Dynamics with Opinion Leader Based on HK Bounded Confidence Model." Complexity 2020 (March 28, 2020): 1–20. http://dx.doi.org/10.1155/2020/7360302.
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Opinion natural reversals are important and common phenomena in network management. It is a naturally emerging process of opinions characterized by interactions between individuals and the evolution of attitudes themselves. To explore the underlying mechanism of this social phenomenon and to reveal its dynamic traits, we propose here a novel model which takes the effects of natural reversal parameter and opinion interaction on the individual’s view choice behavior into account based on the Hegselmann and Krause (HK) bounded confidence model. Experimental results show that the evolution of individual opinions is not only influenced by the interactions between neighboring individuals but also updated naturally due to individual factors themselves in the absence of interaction, which in turn proves that the proposed model can provide a reasonable description of the entire process of public opinion natural reversal under the Internet environment. Besides, the proportion of group opinion tendency, network topology, identification method, and the influence weight of opinion leader will play significant roles in this process, which further indicates our improved model is very robust and thus can provide some insightful evidence to understand the phenomena of opinion natural reversal.
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Schultze, Thomas, Andreas Mojzisch, and Stefan Schulz-Hardt. "Why dyads heed advice less than individuals do." Judgment and Decision Making 14, no. 3 (May 2019): 349–63. http://dx.doi.org/10.1017/s1930297500004381.
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AbstractFollowing up on a recent debate, we examined advice taking in dyads compared to individuals in a set of three studies (total N = 303 dyads and 194 individuals). Our first aim was to test the replicability of an important previous finding, namely that dyads heed advice less than individuals because they feel more confident in the accuracy of their initial judgments. Second, we aimed to explain dyads’ behavior based on three premises: first, that dyads understand that the added value of an outside opinion diminishes when the initial pre-advice judgment is made by two judges rather than one judge (given that the dyad members’ opinions are independent of each other); second, that they fail to recognize when the assumption of independence of opinions does not hold; and third, that the resistance to advice commonly observed in individuals persists in groups but is neither aggravated nor ameliorated by the group context. The results of our studies show consistently that previous findings on advice taking in dyads are replicable. They also support our hypothesis that groups exhibit a general tendency to heed advice less than individuals, irrespective of whether the accuracy of their initial judgments warrants this behavior. Finally, based on the three assumptions mentioned above, we were able to make accurate predictions about advice taking in dyads, prompting us to postulate a general model of advice taking in groups of arbitrary size.
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Qiang, Xu, Zhao Huiqi, Farhad Ali, and Shah Nazir. "Criterial Based Opinion Leader’s Selection for Decision-Making Using Ant Colony Optimization." Scientific Programming 2021 (July 28, 2021): 1–12. http://dx.doi.org/10.1155/2021/4624334.
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The Internet has already become a medium for people to access information, express their views, and connect with one another through various media and tools as a result of its rapid global development. Web 2.0 has become increasingly important in people’s daily lives. With the passing of time, many online communities, such as blogs, forums, and websites, are becoming more interactive. Individuals can easily express their opinions publicly and see what others say about their opinions. In a social network, an opinion leader is a powerful individual who is an expert in a particular field and has a large number of people who follow his or her comments or ideas. Companies and governments may contact the most powerful people after discovering them in order to influence sales or guide public opinion, respectively. In heterogeneous communication networks, opinion leaders serve as an influencer for the acceptance and dissemination of new products and users in marketing. Others’ drives, values, perceptions, motivations, and actions can be influenced by opinion leaders. These influences have a major effect on other customers’ policymaking processes. Opinion leaders come in a variety of demographic shapes; in general, they are committed, ambitious, and dynamic individuals with excellent academic and social edifications who persuade customers through their expert knowledge. Opinions and values are the most important variables in human experiences in social phenomena. The method of assessing opinions is extremely difficult since people often change their minds when speaking with others. The study of the evolution and formation of opinions in a social group is known as opinion dynamics, and it is based on collective decision-making. The bounded confidence rule is one of the intrinsic interaction principles in the dynamics of human actions. Many models have been created to date to explore the dynamics of leaders’ decision-making. Due to the social network’s high complexity and the randomness and contingency of their behavior, identifying opinion leaders in the network is difficult. Organizations and entrepreneurs must choose which opinion leaders to partner with to gain a deeper understanding of how to communicate with them to promote various goods and services. For the opinion leader’s selection optimization, the proposed framework feature-based opinion leader selection is utilized using the ant colony optimization technique that selects the best opinion leader based on their unique features. The proposed method will address the opinion leader selection problem.
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DI MARE, ALESSANDRO, and VITO LATORA. "OPINION FORMATION MODELS BASED ON GAME THEORY." International Journal of Modern Physics C 18, no. 09 (September 2007): 1377–95. http://dx.doi.org/10.1142/s012918310701139x.
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A way to simulate the basic interactions between two individuals with different opinions, in the context of strategic game theory, is proposed. Various games are considered, which produce different kinds of opinion formation dynamics. First, by assuming that all individuals (players) are equals, we obtain the bounded confidence model of continuous opinion dynamics proposed by Deffuant et al. In such a model a tolerance threshold is defined, such that individuals with difference in opinion larger than the threshold can not interact. Then, we consider that the individuals have different inclinations to change opinion and different abilities in convincing the others. In this way, we obtain the so-called "Stubborn individuals and Orators" (SO) model, a generalization of the Deffuant et al. model, in which the threshold tolerance is different for every couple of individuals. We explore, by numerical simulations, the dynamics of the SO model, and we propose further generalizations that can be implemented.
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Kaur, Gaganpreet, Pratibha ., Amandeep Kaur, and Meenu Khurana. "A Review of Opinion Mining Techniques." ECS Transactions 107, no. 1 (April 24, 2022): 10125–32. http://dx.doi.org/10.1149/10701.10125ecst.
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Opinion mining also known as Sentiment analysis is one of the most recent challenges in Natural Language Processing (NLP). Individuals expressing their opinions on various platforms such as Facebook, Twitter, and Yelp are also a difficult task because innovation has increased exponentially. With the popularity of social media, a massive amount of data namely comments, reviews and opinions have been generated. According to researchers, analysis of sentiments is based on a sentence level, document level, aspect level and user level. The analysis of this data consumes more time and is difficult for processing. As a result, there is a need to create an intelligent system that can classify or determine positive, negative, and neutral opinions. The main goal of this paper is to provide a brief summary of opinion mining using techniques like machine learning, deep learning, transfer learning, and the Hadoop framework.
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Roy, Subhradeep, and Nicole Abaid. "Interactional dynamics of same-sex marriage legislation in the United States." Royal Society Open Science 4, no. 6 (June 2017): 170130. http://dx.doi.org/10.1098/rsos.170130.
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Understanding how people form opinions and make decisions is a complex phenomenon that depends on both personal practices and interactions. Recent availability of real-world data has enabled quantitative analysis of opinion formation, which illuminates phenomena that impact physical and social sciences. Public policies exemplify complex opinion formation spanning individual and population scales, and a timely example is the legalization of same-sex marriage in the United States. Here, we seek to understand how this issue captures the relationship between state-laws and Senate representatives subject to geographical and ideological factors. Using distance-based correlations, we study how physical proximity and state-government ideology may be used to extract patterns in state-law adoption and senatorial support of same-sex marriage. Results demonstrate that proximal states have similar opinion dynamics in both state-laws and senators’ opinions, and states with similar state-government ideology have analogous senators’ opinions. Moreover, senators’ opinions drive state-laws with a time lag. Thus, change in opinion not only results from negotiations among individuals, but also reflects inherent spatial and political similarities and temporal delays. We build a social impact model of state-law adoption in light of these results, which predicts the evolution of state-laws legalizing same-sex marriage over the last three decades.
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Hosek, Adrienne. "Ensuring the Future of the Affordable Care Act on the Health Insurance Marketplaces." Journal of Health Politics, Policy and Law 44, no. 4 (April 12, 2019): 589–630. http://dx.doi.org/10.1215/03616878-7530813.
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AbstractContext: A decade after passage, a majority of Americans now support the Affordable Care Act (ACA), and Republican efforts to repeal it outright have failed. This article investigates whether the policy itself, through its beneficiaries, changed public opinion and sowed the seeds of its defense.Methods: This study used an individual-level panel design to estimate the causal effect of implementation on opinion and electoral outcomes for ACA beneficiaries during the first year of open enrollment.Findings: Individuals who enrolled in plans on the health insurance marketplaces had significantly more positive opinions of the ACA after implementation. Previously uninsured Medicaid enrollees also reported improved opinions, though results were not statistically significant. In contrast, uninsured individuals residing in states that did not expand Medicaid became significantly less supportive of the law. Changes in opinion persisted up to the 2014 midterm elections, and there is evidence that individuals with marketplace insurance became more supportive of Democratic candidates, although not more likely to vote for them.Conclusions: Public support for the ACA was enhanced when its beneficiaries became more positive toward it during implementation. Recent changes to key ACA provisions have the potential to undermine the law's effectiveness, potentially leading to political action as benefits slowly begin to disappear.
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Huma, Zil e., and Zahid Yousaf. "Exploring the Opinion Sharing Patterns among Social Media users in Pakistan." Journal of Peace, Development & Communication V05, no. 03 (October 1, 2021): 42–55. http://dx.doi.org/10.36968/jpdc-v05-i03-04.
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The spiral of silence theory described that when majority opinion is dominant the minority opinion is not expressed. For the last five decades, the theory of the spiral of silence describes social separation due to minority opinions. The fear of isolation has made individuals frightened in exchanging their opinions. The people who have opinions in minority are the main actors feared from isolation. In today’s world, the internet has shown rapid developments in the form of new media, and day by day users are getting attracted to this new technology. This study is an effort to determine the level of effects of the spiral of silence on the young generation of Pakistan. This research focuses on the spiral of silence and the way people are expressing their opinions. This research is quantitative study. A Survey of 1099 respondents has been done through purposive sampling. Opinion sharing is a dependent variable whereas exposure to social media, fear of isolation, willingness to speak, and climate of opinion are independent variables. Regression analysis was applied to check the connection of independent variables with opinion sharing behavior of the social media users. This research uses the spiral of silence theory in relation to the social media usage patterns of its users. The study indicates that the relationship between dependent and independent variables is strong.
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McCaffery, Rosemary, Alyson Lee, Pramod Jauhar, and Jan Scott. "A survey of opinions on the management of individuals who express suicidal ideation while intoxicated with alcohol." Psychiatric Bulletin 26, no. 9 (September 2002): 332–34. http://dx.doi.org/10.1192/pb.26.9.332.
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Aims and MethodIt was noted that approaches to the assessment and management of individuals intoxicated with alcohol who express suicidal ideation varied widely. This study explored what guidance is currently available and sought the opinions of 218 junior and senior psychiatrists.ResultsThe Royal College of Psychiatrists has no specific guidelines on this issue, but the Medical Defence Union and Scottish Central Legal Office gave opinion regarding a psychiatrist's duty of care and clinical responsibilities. This information did not reflect the opinions of the psychiatrists canvassed. There was no consensus among the 65% of clinicians who responded to the survey.Clinical ImplicationsThere is a need for greater clarity and guidance on the management of individuals who are intoxicated and express acute suicidal ideation. Sharing of good practice guidelines and greater integration of local and national policies is needed. It is certainly a topic worthy of inclusion in all induction days for junior psychiatrists.
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Kellstedt, Paul M., Mark D. Ramirez, Arnold Vedlitz, and Sammy Zahran. "Does Political Sophistication Minimize Value Conflict? Evidence from a Heteroskedastic Graded IRT Model of Opinions toward Climate Change." British Journal of Political Science 49, no. 4 (December 4, 2017): 1309–32. http://dx.doi.org/10.1017/s0007123417000369.
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When citizens hold multiple values relevant to their policy opinions, they might experience value conflict, value reconciliation or make a value trade-off. Yet, it is unclear which individuals are able to manage their multiple values in these ways. We posit a sophistication-interaction theory of value pluralism where the most politically sophisticated individuals are able to reconcile the existence of multiple values, thus increasing the stability of their policy opinions. We test this hypothesis using a series of heteroskedastic graded item response theory models of public opinion toward policies related to climate change. We find that people structure their policy preferences toward climate change policies in values toward the environment and the economy, but only the most sophisticated citizens are able to reconcile the potential conflict between these values.
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SHEN, BO, and YUN LIU. "AN OPINION FORMATION MODEL WITH TWO STAGES." International Journal of Modern Physics C 18, no. 08 (August 2007): 1231–42. http://dx.doi.org/10.1142/s0129183107011273.
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The opinion formation process is a general phenomenon in community and society. In recent years, several models of opinion formation have been proposed; however, most models mainly focus on describing views exchange between individuals and interaction between individuals and the environment. In this paper, we present an opinion formation model which takes into account the initial state of opinions and the contacting process with topics. The model involves two stages. The first one is the process in which individuals contact a given topic for the first time and the second one is the social interaction process between individuals. Using the proposed model, we simulate opinion formation process with several sets of parameters. Simulation results indicate that the proposed model may be successfully used for opinion formation simulations. It is also found that the initial state and contacting process have significant influence on opinion formation. Moreover, the model could be helpful for understanding some social phenomena such as quick formation of public opinion about certain topic and the crucial effect of small fluctuations on opinion distribution.
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Porten-Cheé, Pablo, and Christiane Eilders. "The effects of likes on public opinion perception and personal opinion." Communications 45, no. 2 (May 26, 2020): 223–39. http://dx.doi.org/10.1515/commun-2019-2030.
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AbstractDrawing on the spiral of silence theory and heuristic information processing, we contend that individuals use likes as sources for assessing public opinion. We further argue that individuals may even adapt their personal opinions to the tenor reflected in those cues. The assumptions were tested using data from an experiment involving 501 participants, who encountered media items on two issues with or without likes. The findings show that respondents inferred public opinion from the media bias if it was supported by likes, however, only in cases of high levels of fear of social isolation. Respondents further adapted their personal opinion to the media bias if it was supported by likes.
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Martins, André C. R. "Agent Mental Models and Bayesian Rules as a Tool to Create Opinion Dynamics Models." Physics 6, no. 3 (July 31, 2024): 1013–31. http://dx.doi.org/10.3390/physics6030062.
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Traditional models of opinion dynamics provide a simplified approach to understanding human behavior in basic social scenarios. However, when it comes to issues such as polarization and extremism, a more nuanced understanding of human biases and cognitive tendencies are required. This paper proposes an approach to modeling opinion dynamics by integrating mental models and assumptions of individuals agents using Bayesian-inspired methods. By exploring the relationship between human rationality and Bayesian theory, this paper demonstrates the usefulness of these methods in describing how opinions evolve. The analysis here builds upon the basic idea in the Continuous Opinions and Discrete Actions (CODA) model, by applying Bayesian-inspired rules to account for key human behaviors such as confirmation bias, motivated reasoning, and human reluctance to change opinions. Through this, This paper updates rules that are compatible with known human biases. The current work sheds light on the role of human biases in shaping opinion dynamics. I hope that by making the model more realistic this might lead to more accurate predictions of real-world scenarios.
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BANISCH, SVEN, TANYA ARAÚJO, and JORGE LOUÇÃ. "OPINION DYNAMICS AND COMMUNICATION NETWORKS." Advances in Complex Systems 13, no. 01 (February 2010): 95–111. http://dx.doi.org/10.1142/s0219525910002438.
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This paper examines the interplay of opinion exchange dynamics and communication network formation. An opinion formation procedure is introduced which is based on an abstract representation of opinions as k-dimensional bit-strings. Individuals interact if the difference in the opinion strings is below a defined similarity threshold dI. Depending on dI, different behavior of the population is observed: low values result in a state of highly fragmented opinions and higher values yield consensus. The first contribution of this research is to identify the values of parameters dI and k, such that the transition between fragmented opinions and homogeneity takes place. Then, we look at this transition from two perspectives: first by studying the group size distribution and second by analyzing the communication network that is formed by the interactions that take place during the simulation. The emerging networks are classified by statistical means and we find that nontrivial social structures emerge from simple rules for individual communication. Generating networks allows to compare model outcomes with real-world communication patterns.
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Koehne, Jodi, Fred Mannering, and Mark Hallenbeck. "Analysis of Trucker and Motorist Opinions toward Truck-Lane Restrictions." Transportation Research Record: Journal of the Transportation Research Board 1560, no. 1 (January 1996): 73–82. http://dx.doi.org/10.1177/0361198196156000111.
Full textAbstract:
Truck restrictions, which are becoming increasingly popular throughout the United States, are justified on the grounds of improving traffic operations and safety, decreasing pavement wear, and other related factors. Although an abundance of research has been aimed at quantifying the benefits and costs of truck restrictions, little has been done to measure truckers' and motorists' opinions of such restrictions statistically. Truckers' and motorists' opinions of the truck-lane restrictions in force in the Puget Sound region of Washington State are assessed statistically here. The assessment was made by administering separate opinion surveys to truckers and motorists and estimating logit models that give the probability of an individual's being in favor of or opposed to truck-lane restrictions. In addition, a logit model giving the probability that an individual is even aware of the truck-lane restrictions in the Puget Sound region is estimated. The results of these model estimations give a profile of individuals that are most likely to favor or oppose truck-lane restrictions. These profiles provide valuable information for policy analysts and administrators concerned with implementation since they define the opinions of population groups that can make or break truck restriction policies on U.S. highways.
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Kashtan, Clifford. "Alport syndrome: facts and opinions." F1000Research 6 (January 17, 2017): 50. http://dx.doi.org/10.12688/f1000research.9636.1.
Full textAbstract:
In this commentary, I review recent advances in Alport syndrome genetics, diagnostics, and therapeutics. I also offer some opinions regarding strategies to optimize the early identification of affected individuals to promote early therapeutic intervention.