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Opinion Dynamics And Learning In Social Networks
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Book Synopsis Opinion Dynamics and Learning in Social Networks by : Daron Acemoglu
Download or read book Opinion Dynamics and Learning in Social Networks written by Daron Acemoglu and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We provide an overview of recent research on belief and opinion dynamics in social networks. We discuss both Bayesian and non-Bayesian models of social learning and focus on the implications of the form of learning (e.g., Bayesian vs. non-Bayesian), the sources of information (e.g., observation vs. communication), and the structure of social networks in which individuals are situated on three key questions: (1) whether social learning will lead to consensus, i.e., to agreement among individuals starting with different views; (2) whether social learning will effectively aggregate dispersed information and thus weed out incorrect beliefs; (3) whether media sources, prominent agents, politicians and the state will be able to manipulate beliefs and spread misinformation in a society.
Book Synopsis Opinion Dynamics and the Evolution of Social Power in Social Networks by : Mengbin Ye
Download or read book Opinion Dynamics and the Evolution of Social Power in Social Networks written by Mengbin Ye and published by Springer. This book was released on 2019-02-19 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book uses rigorous mathematical analysis to advance opinion dynamics models for social networks in three major directions. First, a novel model is proposed to capture how a discrepancy between an individual’s private and expressed opinions can develop due to social pressures that arise in group situations or through extremists deliberately shaping public opinion. Detailed theoretical analysis of the final opinion distribution is followed by use of the model to study Asch’s seminal experiments on conformity, and the phenomenon of pluralistic ignorance. Second, the DeGroot-Friedkin model for evolution of an individual’s social power (self-confidence) is developed in a number of directions. The key result establishes that an individual’s initial social power is forgotten exponentially fast, even when the network changes over time; eventually, an individual’s social power depends only on the (changing) network structure. Last, a model for the simultaneous discussion of multiple logically interdependent topics is proposed. To ensure that a consensus across the opinions of all individuals is achieved, it turns out that the interpersonal interactions must be weaker than an individual’s introspective cognitive process for establishing logical consistency among the topics. Otherwise, the individual may experience cognitive overload and the opinion system becomes unstable. Conclusions of interest to control engineers, social scientists, and researchers from other relevant disciplines are discussed throughout the thesis with support from both social science and control literature.
Book Synopsis Opinion Dynamics in Social Networks by : Qi Gu
Download or read book Opinion Dynamics in Social Networks written by Qi Gu and published by . This book was released on 2014 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Opinion dynamics is a complex procedure that entails a cognitive process when it deals with how a person integrates influential opinions to form revised opinion. Early research on opinion formation and social influence can be traced back to the eighteenth century. The original research focus was to study the conditions for people to aggregate information and reach consensus. Recently, due to the rise of the World Wide Web more and more studies tend to model opinion dynamics in large-scale social networks via computational methods. Among those works, non-Bayesian rule-of-thumb learning models keep gaining popularity due to their simplicity and computational efficiency. Unlike many non-Bayesian methods that treat individual opinions on various issues as independent beliefs but overlook the connections between knowledge fragments, we leverage from Bayesian approaches to consider opinions as a product inferred from one's knowledge-based system, where new knowledge fragments are acquired through social interaction and learning experiences. We study how an individual evaluates and adopts such knowledge fragments from others sources, both visible and invisible, on the basis of the findings from well-established social theories. A computational framework was developed to model opinion dynamics, in which we applied a probabilistic model named Bayesian Knowledge Bases to represent an individual's knowledge base. Opinion dynamics is studied by modeling opinion formation as a process of knowledge fusion, learning the impact metric that estimates the reliability of knowledge fragments, and identifying influential sources whose impact patterns are hidden. The contributions of this work can be summarized as 1) the development of a domain-independent computational method to model opinion formation by emphasizing the dependencies between knowledge pieces, 2) the capability to model different aspects of opinion dynamics in one entire system, 3) the intuitiveness in representing opinions such that the intents behind the opinion change can be readily captured, 4) the ability to characterize the influences in a social community by realizing and enriching theories of social communication, and 5) the flexibility of application on detecting and tracking hidden influential sources.
Book Synopsis Opinion Dynamics on Social Networks by : Jay Nanavati
Download or read book Opinion Dynamics on Social Networks written by Jay Nanavati and published by . This book was released on 2016 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Annual Reviews of Computational Physics by : Dietrich Stauffer
Download or read book Annual Reviews of Computational Physics written by Dietrich Stauffer and published by World Scientific. This book was released on 2001 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ninth volume of Annual Reviews of Computational Physics has as a special feature a comprehensive compendium of interatomic potentials as used for materials properties. Other articles deal with simulations of magnetic nanostructures, improved Monte Carlo methods (e.g. for nucleation studies in Ising models), fluid dynamics with large mean free paths, the growing field of OC sociophysics, OCO and teaching of undergraduate computational physics (including an introduction to Java)."
Book Synopsis Vector Opinion Dynamics by : Alya Alaali
Download or read book Vector Opinion Dynamics written by Alya Alaali and published by . This book was released on 2008 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Information Diffusion and Opinion Dynamics in Social Networks by : Julio Cesar Louzada Pinto
Download or read book Information Diffusion and Opinion Dynamics in Social Networks written by Julio Cesar Louzada Pinto and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our aim in this Ph. D. thesis is to study the diffusion of information as well as the opinion dynamics of users in social networks. Information diffusion models explore the paths taken by information being transmitted through a social network in order to understand and analyze the relationships between users in such network, leading to a better comprehension of human relations and dynamics. This thesis is based on both sides of information diffusion: first by developing mathematical theories and models to study the relationships between people and information, and in a second time by creating tools to better exploit the hidden patterns in these relationships. The theoretical tools developed in this thesis are opinion dynamics models and information diffusion models, where we study the information flow from users in social networks, and the practical tools developed in this thesis are a novel community detection algorithm and a novel trend detection algorithm. We start by introducing an opinion dynamics model in which agents interact with each other about several distinct opinions/contents. In our framework, agents do not exchange all their opinions with each other, they communicate about randomly chosen opinions at each time. We show, using stochastic approximation algorithms, that under mild assumptions this opinion dynamics algorithm converges as time increases, whose behavior is ruled by how users choose the opinions to broadcast at each time. We develop next a community detection algorithm which is a direct application of this opinion dynamics model: when agents broadcast the content they appreciate the most. Communities are thus formed, where they are defined as groups of users that appreciate mostly the same content. This algorithm, which is distributed by nature, has the remarkable property that the discovered communities can be studied from a solid mathematical standpoint. In addition to the theoretical advantage over heuristic community detection methods, the presented algorithm is able to accommodate weighted networks, parametric and nonparametric versions, with the discovery of overlapping communities a byproduct with no mathematical overhead. In a second part, we define a general framework to model information diffusion in social networks. The proposed framework takes into consideration not only the hidden interactions between users, but as well the interactions between contents and multiple social networks. It also accommodates dynamic networks and various temporal effects of the diffusion. This framework can be combined with topic modeling, for which several estimation techniques are derived, which are based on nonnegative tensor factorization techniques. Together with a dimensionality reduction argument, this techniques discover, in addition, the latent community structure of the users in the social networks. At last, we use one instance of the previous framework to develop a trend detection algorithm designed to find trendy topics in a social network. We take into consideration the interaction between users and topics, we formally define trendiness and derive trend indices for each topic being disseminated in the social network. These indices take into consideration the distance between the real broadcast intensity and the maximum expected broadcast intensity and the social network topology. The proposed trend detection algorithm uses stochastic control techniques in order calculate the trend indices, is fast and aggregates all the information of the broadcasts into a simple one-dimensional process, thus reducing its complexity and the quantity of necessary data to the detection. To the best of our knowledge, this is the first trend detection algorithm that is based solely on the individual performances of topics.
Book Synopsis Boundedly Rational Opinion Dynamics in Directed Social Networks by : Pietro Battiston
Download or read book Boundedly Rational Opinion Dynamics in Directed Social Networks written by Pietro Battiston and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates opinion dynamics and social influence in directed communication networks. We study the properties of a generalized boundedly rational model of opinion formation in which individuals aggregate the information they receive by using weights that are a function of their neighbors' indegree. We then present an experiment designed to test the predictions of the model. We find that both Bayesian updating and boundedly rational updating a la DeMarzo et al. (2003) are rejected by the data. Consistent with our theoretical predictions, the social influence of an agent is positively and significantly affected by the number of individuals she listens to. When forming their opinions, agents do take into account the structure of the communication network, although in a sub-optimal way.
Book Synopsis The Oxford Handbook of the Economics of Networks by : Yann Bramoullé
Download or read book The Oxford Handbook of the Economics of Networks written by Yann Bramoullé and published by Oxford University Press. This book was released on 2016-03-01 with total page 857 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oxford Handbook of the Economics of Networks represents the frontier of research into how and why networks they form, how they influence behavior, how they help govern outcomes in an interactive world, and how they shape collective decision making, opinion formation, and diffusion dynamics. From a methodological perspective, the contributors to this volume devote attention to theory, field experiments, laboratory experiments, and econometrics. Theoretical work in network formation, games played on networks, repeated games, and the interaction between linking and behavior is synthesized. A number of chapters are devoted to studying social process mediated by networks. Topics here include opinion formation, diffusion of information and disease, and learning. There are also chapters devoted to financial contagion and systemic risk, motivated in part by the recent financial crises. Another section discusses communities, with applications including social trust, favor exchange, and social collateral; the importance of communities for migration patterns; and the role that networks and communities play in the labor market. A prominent role of networks, from an economic perspective, is that they mediate trade. Several chapters cover bilateral trade in networks, strategic intermediation, and the role of networks in international trade. Contributions discuss as well the role of networks for organizations. On the one hand, one chapter discusses the role of networks for the performance of organizations, while two other chapters discuss managing networks of consumers and pricing in the presence of network-based spillovers. Finally, the authors discuss the internet as a network with attention to the issue of net neutrality.
Book Synopsis Opinion Fluctuations and Disagreement in Social Networks by : Daron Acemoglu
Download or read book Opinion Fluctuations and Disagreement in Social Networks written by Daron Acemoglu and published by . This book was released on 2010 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study a stochastic gossip model of continuous opinion dynamics in a society consisting of two types of agents: regular agents, who update their beliefs according to information that they receive from their social neighbors; and stubborn agents, who never update their opinions and might represent leaders, political parties or media sources attempting to influence the beliefs in the rest of the society. When the society contains stubborn agents with different opinions, opinion dynamics never lead to a consensus (among the regular agents). Instead, beliefs in the society almost surely fail to converge, and the belief of each regular agent converges in law to a non-degenerate random variable. The model thus generates long-run disagreement and continuous opinion fluctuations. The structure of the social network and the location of stubborn agents within it shape opinion dynamics. When the society is "highly fluid," meaning that the mixing time of the random walk on the graph describing the social network is small relative to (the inverse of) the relative size of the linkages to stubborn agents, the ergodic beliefs of most of the agents concentrate around a certain common value. We also show that under additional conditions, the ergodic beliefs distribution becomes "approximately chaotic," meaning that the variance of the aggregate belief of the society vanishes in the large population limit while individual opinions still fluctuate significantly. Keywords: disagreement, learning, opinion information, social networks, stochastic gossip. JEL Classifications: D83.
Book Synopsis Analytical Approach for Opinion Dynamics on Social Networks by : Weituo Zhang
Download or read book Analytical Approach for Opinion Dynamics on Social Networks written by Weituo Zhang and published by . This book was released on 2012 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis CASoS Engineering Using Opinion Dynamics on Social Networks by :
Download or read book CASoS Engineering Using Opinion Dynamics on Social Networks written by and published by . This book was released on 2011 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Public Response to Alerts and Warnings Using Social Media by : National Research Council
Download or read book Public Response to Alerts and Warnings Using Social Media written by National Research Council and published by National Academies Press. This book was released on 2013-02-04 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following an earlier NRC workshop on public response to alerts and warnings delivered to mobile devices, a related workshop was held on February 28 and 29, 2012 to look at the role of social media in disaster response. This was one of the first workshops convened to look systematically at the use of social media for alerts and warnings-an event that brought together social science researchers, technologists, emergency management professionals, and other experts on how the public and emergency managers use social media in disasters.In addition to exploring how officials monitor social media, as well as the resulting privacy considerations, the workshop focused on such topics as: what is known about how the public responds to alerts and warnings; the implications of what is known about such public responses for the use of social media to provide alerts and warnings to the public; and approaches to enhancing the situational awareness of emergency managers. Public Response to Alerts and Warnings Using Social Media: Report of a Workshop on Current Knowledge and Research Gaps summarizes presentations made by invited speakers, other remarks by workshop participants, and discussions during parallel breakout sessions. It also points to potential topics for future research, as well as possible areas for future research investment, and it describes some of the challenges facing disaster managers who are seeking to incorporate social media into regular practice.
Book Synopsis On Aggregation and Dynamics of Opinions in Complex Networks by : Olle Abrahamsson
Download or read book On Aggregation and Dynamics of Opinions in Complex Networks written by Olle Abrahamsson and published by Linköping University Electronic Press. This book was released on 2024-04-17 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis studies two problems defined on complex networks, of which the first explores a conceivable extension of structural balance theory and the other concerns convergence issues in opinion dynamics. In the first half of the thesis we discuss possible definitions of structural balance conditions in a network with preference orderings as node attributes. The main result is that for the case with three alternatives (A, B, C) we reduce the (3!)3 = 216 possible configurations of triangles to 10 equivalence classes, and use these as measures of balance of a triangle towards possible extensions of structural balance theory. Moreover, we derive a general formula for the number of equivalent classes for preferences on n alternatives. Finally, we analyze a real-world data set and compare its empirical distribution of triangle equivalence classes to a null hypothesis in which preferences are randomly assigned to the nodes. The second half of the thesis concerns an opinion dynamics model in which each agent takes a random Bernoulli distributed action whose probability is updated at each discrete time step, and we prove that this model converges almost surely to consensus. We also provide a detailed critique of a claimed proof of this result in the literature. We generalize the result by proving that the assumption of irreducibility in the original model is not necessary. Furthermore, we prove as a corollary of the generalized result that the almost sure convergence to consensus holds also in the presence of a fully stubborn agent which never changes its opinion. In addition, we show that the model, in both the original and generalized cases, converges to consensus also in rth moment. Avhandlingen studerar två problem definierade på komplexa nätverk, varav det första utforskar en tänkbar utökning av strukturell balansteori och det andra behandlar konvergensfrågor inom opinionsdynamik. I avhandlingens första hälft diskuteras möjliga definitioner på villkor för strukturell balans i ett nätverk med preferensordningar som nodattribut. Huvudresultatet är att för fallet med tre alternativ (A, B, C) så kan de (3!)3 = 216 möjliga konfigurationerna av trianglar reduceras till 10 ekvivalensklasser, vilka används som mått på en triangels balans som ett steg mot möjliga utökningar av strukturell balansteori. Vi härleder även en generell formel för antalet ekvivalensklasser för preferensordningar med n alternativ. Slutligen analyseras en empirisk datamängd och dess empiriska sannolikhetsfördelning av triangel-ekvivalensklasser jämförs med en nollhypotes i vilken preferenser tilldelas noderna slumpmässigt. Den andra hälften av avhandlingen rör en opinionsdynamikmodell där varje agent agerar slumpmässigt enligt en Bernoullifördelning vars sannolikhet uppdateras vid varje diskret tidssteg, och vi bevisar att denna modell konvergerar nästan säkert till konsensus. Vi ger också en detaljerad kritik av ett påstått bevis av detta resultat i litteraturen. Vi generaliserar resultatet genom att visa att antagandet om irreducibilitet i den ursprungliga modellen inte är nödvändigt. Vidare visar vi, som följdsats av det generaliserade resultatet, att den nästan säkra konvergensen till konsensus även håller om en agent är fullständigt envis och aldrig byter åsikt. I tillägg till detta visar vi att modellen, både i det ursprungliga och i det generaliserade fallet, konvergerar till konsensus även i r:te ordningens moment.
Book Synopsis Sentiment Analysis in Social Networks by : Federico Alberto Pozzi
Download or read book Sentiment Analysis in Social Networks written by Federico Alberto Pozzi and published by Morgan Kaufmann. This book was released on 2016-10-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network mining Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics
Book Synopsis Opinion Formation in Dynamic Social Networks by : Joyce Kafui Klu
Download or read book Opinion Formation in Dynamic Social Networks written by Joyce Kafui Klu and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Opinion Mining and Sentiment Analysis by : Bo Pang
Download or read book Opinion Mining and Sentiment Analysis written by Bo Pang and published by Now Publishers Inc. This book was released on 2008 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.
