Information Diffusion And Opinion Dynamics In Social Networks

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Information Diffusion and Opinion Dynamics in Social Networks

Author : Julio Cesar Louzada Pinto
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (936 download)

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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.

Advances in Information Retrieval

Author : Pavel Serdyukov
Publisher : Springer
ISBN 13 : 3642369731
Total Pages : 919 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Advances in Information Retrieval by : Pavel Serdyukov

Download or read book Advances in Information Retrieval written by Pavel Serdyukov and published by Springer. This book was released on 2013-03-12 with total page 919 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 35th European Conference on IR Research, ECIR 2013, held in Moscow, Russia, in March 2013. The 55 full papers, 38 poster papers and 10 demonstrations presented in this volume were carefully reviewed and selected from 287 submissions. The papers are organized in the following topical sections: user aspects; multimedia and cross-media IR; data mining; IR theory and formal models; IR system architectures; classification; Web; event detection; temporal IR, and microblog search. Also included are 4 tutorial and 2 workshop presentations.

Python for Graph and Network Analysis

Author : Mohammed Zuhair Al-Taie
Publisher : Springer
ISBN 13 : 3319530046
Total Pages : 214 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Python for Graph and Network Analysis by : Mohammed Zuhair Al-Taie

Download or read book Python for Graph and Network Analysis written by Mohammed Zuhair Al-Taie and published by Springer. This book was released on 2017-03-20 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community. They will be able to analyse militant and revolutionary networks and candidate networks during elections. For instance, they will learn how the Ebola virus spread through communities. Practically, the book is suitable for courses on social network analysis in all disciplines that use social methodology. In the study of social networks, social network analysis makes an interesting interdisciplinary research area, where computer scientists and sociologists bring their competence to a level that will enable them to meet the challenges of this fast-developing field. Computer scientists have the knowledge to parse and process data while sociologists have the experience that is required for efficient data editing and interpretation. Social network analysis has successfully been applied in different fields such as health, cyber security, business, animal social networks, information retrieval, and communications.

Opinion Dynamics and the Evolution of Social Power in Social Networks

Author : Mengbin Ye
Publisher : Springer
ISBN 13 : 3030106063
Total Pages : 209 pages
Book Rating : 4.0/5 (31 download)

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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.

The Dynamics of Information Diffusion on On-line Social Networks

Author : Shaomei Wu
Publisher :
ISBN 13 :
Total Pages : 133 pages
Book Rating : 4.:/5 (913 download)

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Book Synopsis The Dynamics of Information Diffusion on On-line Social Networks by : Shaomei Wu

Download or read book The Dynamics of Information Diffusion on On-line Social Networks written by Shaomei Wu and published by . This book was released on 2013 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there has been a long history of studying the diffusion of information in various social science fields, existing theories are mostly built on direct observations in small networks or survey responses from large samples. As a result, it is hard to verify or refute these theories empirically on a large scale. In recent years, the abundance of digital records of online interactions has provided us for the first time both explicit network structure and detailed dynamics, supporting global-scale, quantitative study of diffusion in the real world. Using these large scale datasets collected from social media sites, we are able to dissect and study the process of information diffusion in its three components: people, information, and network. This thesis mainly addresses a few long-standing questions about each component, including: "who influences whom?", "how do different types of information spread?", and "how does the network structure impact the diffusion process?" In our search of answers for these questions, we realize that these three components are interconnected, constantly interacting with each other in real-world diffusion processes. Thus our results on each component should not be taken in isolation but be viewed interdependently. To understand who influences whom in today's hybrid communication environment, we study people's influence on social media based on their role in the global media ecosystem. By categorizing Twitter accounts into elite (i.e. celebrities, media outlets, organizations, and bloggers) and ordinary users, we find a striking concentration of attention on a minority of elite users, and significant homophily within elite categories. On the other hand, following the definition of "opinion leaders" in the classical "two-step flow" theory, we find a large population of opinion leaders who serve as a layer of intermediaries between the elite users and the masses. The next question we ask is the role of content in the diffusion process. In contrast to previous research on the virality of information, we switch our focus to the persistence of information, trying to understand why certain content keeps on spreading in social media for a long time while most does not. First, we see an interaction effect, from both people and content, on the lifespan of information. As a result, there is a significant difference in lifespan, for information broadcast by different categories of users. Second, we find a strong association between the linguistic style of content and its temporal dynamics: rapidly-fading information contains significantly more words related to negative emotion, actions, and more complicated cognitive processes, whereas persistent information contains more words related to positive emotion, leisure, and lifestyle. In the end, we conduct a longitudinal study of the local and global structure of several large social networks, asking how and where disengagement happens in the social graph. We find that, although there is a significant correlation in both arrival and departure among friends, the dynamics of departure behave differently from the dynamics of arrival. In particular, for the majority of users with a sufficient number (e.g., greater than 20) of friends, departure is best predicted by the overall fraction of active friends within a user's neighborhood, independent of the size of the neighborhood. We also find that active users tend to belong to a core that is densifying and is significantly denser than the inactive users, and the inactive set of users exhibit a higher density and lower conductance than the degree distribution alone can explain. These two aspects suggest that nodes at the fringe are more likely to depart and subsequent departures are correlated among neighboring nodes in tightly-knit communities.

Opinion Dynamics and Learning in Social Networks

Author : Daron Acemoglu
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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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.

Diffusion in Social Networks

Author : Paulo Shakarian
Publisher : Springer
ISBN 13 : 3319231057
Total Pages : 110 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Diffusion in Social Networks by : Paulo Shakarian

Download or read book Diffusion in Social Networks written by Paulo Shakarian and published by Springer. This book was released on 2015-09-16 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the leading models of social network diffusion that are used to demonstrate the spread of disease, ideas, and behavior. It introduces diffusion models from the fields of computer science (independent cascade and linear threshold), sociology (tipping models), physics (voter models), biology (evolutionary models), and epidemiology (SIR/SIS and related models). A variety of properties and problems related to these models are discussed including identifying seeds sets to initiate diffusion, game theoretic problems, predicting diffusion events, and more. The book explores numerous connections between social network diffusion research and artificial intelligence through topics such as agent-based modeling, logic programming, game theory, learning, and data mining. The book also surveys key empirical results in social network diffusion, and reviews the classic and cutting-edge research with a focus on open problems.

Proceedings of International Conference on Artificial Intelligence and Applications

Author : Poonam Bansal
Publisher : Springer Nature
ISBN 13 : 9811549923
Total Pages : 604 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Proceedings of International Conference on Artificial Intelligence and Applications by : Poonam Bansal

Download or read book Proceedings of International Conference on Artificial Intelligence and Applications written by Poonam Bansal and published by Springer Nature. This book was released on 2020-07-01 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers high-quality papers presented at the International Conference on Artificial Intelligence and Applications (ICAIA 2020), held at Maharaja Surajmal Institute of Technology, New Delhi, India, on 6–7 February 2020. The book covers areas such as artificial neural networks, fuzzy systems, computational optimization technologies and machine learning.

Modeling Information Diffusion in Online Social Networks with Partial Differential Equations

Author : Haiyan Wang
Publisher : Springer Nature
ISBN 13 : 3030388522
Total Pages : 153 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Modeling Information Diffusion in Online Social Networks with Partial Differential Equations by : Haiyan Wang

Download or read book Modeling Information Diffusion in Online Social Networks with Partial Differential Equations written by Haiyan Wang and published by Springer Nature. This book was released on 2020-03-16 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book lies at the interface of mathematics, social media analysis, and data science. Its authors aim to introduce a new dynamic modeling approach to the use of partial differential equations for describing information diffusion over online social networks. The eigenvalues and eigenvectors of the Laplacian matrix for the underlying social network are used to find communities (clusters) of online users. Once these clusters are embedded in a Euclidean space, the mathematical models, which are reaction-diffusion equations, are developed based on intuitive social distances between clusters within the Euclidean space. The models are validated with data from major social media such as Twitter. In addition, mathematical analysis of these models is applied, revealing insights into information flow on social media. Two applications with geocoded Twitter data are included in the book: one describing the social movement in Twitter during the Egyptian revolution in 2011 and another predicting influenza prevalence. The new approach advocates a paradigm shift for modeling information diffusion in online social networks and lays the theoretical groundwork for many spatio-temporal modeling problems in the big-data era.

Online Social Networks

Author : Valerio Arnaboldi
Publisher : Elsevier
ISBN 13 : 0128030429
Total Pages : 118 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Online Social Networks by : Valerio Arnaboldi

Download or read book Online Social Networks written by Valerio Arnaboldi and published by Elsevier. This book was released on 2015-09-25 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online Social Networks: Human Cognitive Constraints in Facebook and Twitter provides new insights into the structural properties of personal online social networks and the mechanisms underpinning human online social behavior. As the availability of digital communication data generated by social media is revolutionizing the field of social networks analysis, the text discusses the use of large- scale datasets to study the structural properties of online ego networks, to compare them with the properties of general human social networks, and to highlight additional properties. Users will find the data collected and conclusions drawn useful during design or research service initiatives that involve online and mobile social network environments. Provides an analysis of the structural properties of ego networks in online social networks Presents quantitative evidence of the Dunbar’s number in online environments Discusses original structural and dynamic properties of human social network through OSN analysis

Dynamics of Social Network Evolution and Information Diffusion

Author : Daniel Mauricio Romero
Publisher :
ISBN 13 :
Total Pages : 198 pages
Book Rating : 4.:/5 (858 download)

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Book Synopsis Dynamics of Social Network Evolution and Information Diffusion by : Daniel Mauricio Romero

Download or read book Dynamics of Social Network Evolution and Information Diffusion written by Daniel Mauricio Romero and published by . This book was released on 2012 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Millions of interactions between people take place on the Web everyday. In this work, we utilize data obtained by tracking these interactions on social media sites to study two important aspects of social networks: the way in which connections between people form and evolve over time, and the dynamics of information diffusion on the network. We introduce novel methodologies, algorithms, and mathematical models to analyze observations from rich datasets. Our results validate known sociological theories of link formation and information diffusion at large scale and suggest new ones. We study the formation of links in the network of interactions among people in social media sites from the premise that these networks are inherently different from offline social networks. Online interaction networks are not purely social, but a combination of social and information networks. We introduce mechanisms of link formation that are motivated from sociological theories of social network formation, and are generalized to social-information networks. Furthermore, we study how the communication patterns of connected users of social media sites change as a response to new connections arriving to the network and compare our results to the predictions that various sociological theories would suggest. There is an intuitive sense in which the network of interactions among people is related to how information spreads on the network. In this work, we show that this relationship is present in both directions. That is, the structure of the network can determine whether information spreads through the network, and the kind of information users are exposed to can determine the connections among the users. Furthermore, we show that the dynamics of information diffusion can change significantly depending on the topic, which suggests the mechanisms that control information diffusion are context dependent.

Opinion Dynamics in Social Networks

Author : Qi Gu
Publisher :
ISBN 13 :
Total Pages : 268 pages
Book Rating : 4.:/5 (88 download)

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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.

Opinion Dynamics on Social Networks

Author : Jay Nanavati
Publisher :
ISBN 13 :
Total Pages : 95 pages
Book Rating : 4.:/5 (974 download)

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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:

Vector Opinion Dynamics

Author : Alya Alaali
Publisher :
ISBN 13 :
Total Pages : 8 pages
Book Rating : 4.:/5 (27 download)

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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:

Information and Influence Propagation in Social Networks

Author : Wei Chen
Publisher : Springer Nature
ISBN 13 : 3031018508
Total Pages : 161 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Information and Influence Propagation in Social Networks by : Wei Chen

Download or read book Information and Influence Propagation in Social Networks written by Wei Chen and published by Springer Nature. This book was released on 2022-05-31 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models against any available real datasets consisting of a social network and propagation traces that occurred in the past? These are just some questions studied by researchers in this area. Information propagation models find applications in viral marketing, outbreak detection, finding key blog posts to read in order to catch important stories, finding leaders or trendsetters, information feed ranking, etc. A number of algorithmic problems arising in these applications have been abstracted and studied extensively by researchers under the garb of influence maximization. This book starts with a detailed description of well-established diffusion models, including the independent cascade model and the linear threshold model, that have been successful at explaining propagation phenomena. We describe their properties as well as numerous extensions to them, introducing aspects such as competition, budget, and time-criticality, among many others. We delve deep into the key problem of influence maximization, which selects key individuals to activate in order to influence a large fraction of a network. Influence maximization in classic diffusion models including both the independent cascade and the linear threshold models is computationally intractable, more precisely #P-hard, and we describe several approximation algorithms and scalable heuristics that have been proposed in the literature. Finally, we also deal with key issues that need to be tackled in order to turn this research into practice, such as learning the strength with which individuals in a network influence each other, as well as the practical aspects of this research including the availability of datasets and software tools for facilitating research. We conclude with a discussion of various research problems that remain open, both from a technical perspective and from the viewpoint of transferring the results of research into industry strength applications.

Dynamic Logics of Networks

Author : Zoé Laure Christoff
Publisher :
ISBN 13 : 9789402800814
Total Pages : 0 pages
Book Rating : 4.8/5 (8 download)

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Book Synopsis Dynamic Logics of Networks by : Zoé Laure Christoff

Download or read book Dynamic Logics of Networks written by Zoé Laure Christoff and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This thesis uses logical tools to investigate a number of basic features of social networks and their evolution over time, including flow of information and spread of opinions. Part I contains the preliminaries, including an introduction to the basic phenomena in social networks that call for a logical analysis of information and reasoning, a review of background material from logic and social network theory, plus an outline of the thesis. Part II presents logical models of collective failures, and illuminates how and when sound individual microbehavior can lead to counterproductive collective macrobehavior. Part III abstracts from specific case studies to investigate the general logic of diffusion phenomena in social networks, as well as the interaction of information and diffusion dynamics. Finally, Part IV presents a summary of our findings, and some ongoing work and perspectives for future research. We discuss modal logics and related formalisms for studying network behavior under various graph properties and rules of influence. We also discuss the natural transition from network evolution by fixed rules as studied in this thesis to the study of network games where agents have choices and goals. Overall, this thesis applies tools from current logics of information update and agency to social network analysis and opinion flow over time, offering both tools for detailed modeling of specific scenarios and a better understanding of the general laws of reasoning that underlie information and diffusion dynamics in social settings."--Samenvatting auteur.

The Oxford Handbook of Political Communication

Author : Kate Kenski
Publisher : Oxford University Press
ISBN 13 : 0199793484
Total Pages : 977 pages
Book Rating : 4.1/5 (997 download)

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Book Synopsis The Oxford Handbook of Political Communication by : Kate Kenski

Download or read book The Oxford Handbook of Political Communication written by Kate Kenski and published by Oxford University Press. This book was released on 2017-06-23 with total page 977 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its development shaped by the turmoil of the World Wars and suspicion of new technologies such as film and radio, political communication has become a hybrid field largely devoted to connecting the dots among political rhetoric, politicians and leaders, voters' opinions, and media exposure to better understand how any one aspect can affect the others. In The Oxford Handbook of Political Communication Kate Kenski and Kathleen Hall Jamieson bring together leading scholars, including founders of the field of political communication Elihu Katz, Jay Blumler, Doris Graber, Max McCombs, and Thomas Paterson,to review the major findings about subjects ranging from the effects of political advertising and debates and understandings and misunderstandings of agenda setting, framing, and cultivation to the changing contours of social media use in politics and the functions of the press in a democratic system. The essays in this volume reveal that political communication is a hybrid field with complex ancestry, permeable boundaries, and interests that overlap with those of related fields such as political sociology, public opinion, rhetoric, neuroscience, and the new hybrid on the quad, media psychology. This comprehensive review of the political communication literature is an indispensible reference for scholars and students interested in the study of how, why, when, and with what effect humans make sense of symbolic exchanges about sharing and shared power. The sixty-two chapters in The Oxford Handbook of Political Communication contain an overview of past scholarship while providing critical reflection of its relevance in a changing media landscape and offering agendas for future research and innovation.