Modeling Information Diffusion In Social Networks

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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.

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.

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.

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

Models and Methods in Social Network Analysis

Author : Peter J. Carrington
Publisher :
ISBN 13 : 9780521809597
Total Pages : 328 pages
Book Rating : 4.8/5 (95 download)

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Book Synopsis Models and Methods in Social Network Analysis by : Peter J. Carrington

Download or read book Models and Methods in Social Network Analysis written by Peter J. Carrington and published by . This book was released on 2005-02-07 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.

Learning from Multiple Social Networks

Author : Liqiang Nie
Publisher : Springer Nature
ISBN 13 : 3031023005
Total Pages : 102 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Learning from Multiple Social Networks by : Liqiang Nie

Download or read book Learning from Multiple Social Networks written by Liqiang Nie and published by Springer Nature. This book was released on 2022-05-31 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the proliferation of social network services, more and more social users, such as individuals and organizations, are simultaneously involved in multiple social networks for various purposes. In fact, multiple social networks characterize the same social users from different perspectives, and their contexts are usually consistent or complementary rather than independent. Hence, as compared to using information from a single social network, appropriate aggregation of multiple social networks offers us a better way to comprehensively understand the given social users. Learning across multiple social networks brings opportunities to new services and applications as well as new insights on user online behaviors, yet it raises tough challenges: (1) How can we map different social network accounts to the same social users? (2) How can we complete the item-wise and block-wise missing data? (3) How can we leverage the relatedness among sources to strengthen the learning performance? And (4) How can we jointly model the dual-heterogeneities: multiple tasks exist for the given application and each task has various features from multiple sources? These questions have been largely unexplored to date. We noticed this timely opportunity, and in this book we present some state-of-the-art theories and novel practical applications on aggregation of multiple social networks. In particular, we first introduce multi-source dataset construction. We then introduce how to effectively and efficiently complete the item-wise and block-wise missing data, which are caused by the inactive social users in some social networks. We next detail the proposed multi-source mono-task learning model and its application in volunteerism tendency prediction. As a counterpart, we also present a mono-source multi-task learning model and apply it to user interest inference. We seamlessly unify these models with the so-called multi-source multi-task learning, and demonstrate several application scenarios, such as occupation prediction. Finally, we conclude the book and figure out the future research directions in multiple social network learning, including the privacy issues and source complementarity modeling. This is preliminary research on learning from multiple social networks, and we hope it can inspire more active researchers to work on this exciting area. If we have seen further it is by standing on the shoulders of giants.

Computational Data and Social Networks

Author : Sriram Chellappan
Publisher : Springer Nature
ISBN 13 : 303066046X
Total Pages : 551 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Computational Data and Social Networks by : Sriram Chellappan

Download or read book Computational Data and Social Networks written by Sriram Chellappan and published by Springer Nature. This book was released on 2021-01-03 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Computational Data and Social Networks, CSoNet 2020, held in Dallas, TX, USA, in December 2020. The 20 full papers were carefully reviewed and selected from 83 submissions. Additionally the book includes 22 special track papers and 3 extended abstracts. The selected papers are devoted to topics such as Combinatorial Optimization and Learning; Computational Methods for Social Good Applications; NLP and Affective Computing; Privacy and Security; Blockchain; Fact-Checking, Fake News and Malware Detection in Online Social Networks; and Information Spread in Social and Data Networks.

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.

Multi-Agent Systems and Agreement Technologies

Author : Nick Bassiliades
Publisher : Springer Nature
ISBN 13 : 3030664120
Total Pages : 612 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Multi-Agent Systems and Agreement Technologies by : Nick Bassiliades

Download or read book Multi-Agent Systems and Agreement Technologies written by Nick Bassiliades and published by Springer Nature. This book was released on 2021-01-04 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the revised post-conference proceedings of the 17th European Conference on Multi-Agent Systems, EUMAS 2020, and the 7th International Conference on Agreement Technologies, AT 2020, which were originally planned to be held as a joint event in Thessaloniki, Greece, in April 2020. Due to COVID-19 pandemic the conference was postponed to September 2020 and finally became a fully virtual conference. The 38 full papers presented in this volume were carefully reviewed and selected from a total of 53 submissions. The papers report on both early and mature research and cover a wide range of topics in the field of autonomous agents and multi-agent systems.

Intelligent Data Communication Technologies and Internet of Things

Author : D. Jude Hemanth
Publisher : Springer Nature
ISBN 13 : 3030340805
Total Pages : 797 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Intelligent Data Communication Technologies and Internet of Things by : D. Jude Hemanth

Download or read book Intelligent Data Communication Technologies and Internet of Things written by D. Jude Hemanth and published by Springer Nature. This book was released on 2019-11-10 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the emerging advances in distributed communication systems, big data, intelligent computing and Internet of Things, presenting state-of-the-art research in frameworks, algorithms, methodologies, techniques and applications associated with data engineering and wireless distributed communication technologies. In addition, it discusses potential topics like performance analysis, wireless communication networks, data security and privacy, human computer interaction, 5G Networks, and smart automated systems, which will provide insights for the evolving data communication technologies. In a nutshell, this proceedings book compiles novel and high-quality research that offers innovative solutions for communications in IoT networks.

Advances in Artificial Intelligence, Software and Systems Engineering

Author : Tareq Ahram
Publisher : Springer
ISBN 13 : 3030204545
Total Pages : 681 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Advances in Artificial Intelligence, Software and Systems Engineering by : Tareq Ahram

Download or read book Advances in Artificial Intelligence, Software and Systems Engineering written by Tareq Ahram and published by Springer. This book was released on 2019-06-10 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses emerging issues resulting from the integration of artificial intelligence systems in our daily lives. It focuses on the cognitive, visual, social and analytical aspects of computing and intelligent technologies, highlighting ways to improve the acceptance, effectiveness, and efficiency of said technologies. Topics such as responsibility, integration and training are discussed throughout. The book also reports on the latest advances in systems engineering, with a focus on societal challenges and next-generation systems and applications for meeting them. The book is based on two AHFE 2019 Affiliated Conferences – on Artificial Intelligence and Social Computing, and on Service, Software, and Systems Engineering –, which were jointly held on July 24–28, 2019, in Washington, DC, USA.

Knowledge-Based Intelligent Information and Engineering Systems

Author : Ignac Lovrek
Publisher : Springer Science & Business Media
ISBN 13 : 3540855645
Total Pages : 1079 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Knowledge-Based Intelligent Information and Engineering Systems by : Ignac Lovrek

Download or read book Knowledge-Based Intelligent Information and Engineering Systems written by Ignac Lovrek and published by Springer Science & Business Media. This book was released on 2008-08-18 with total page 1079 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation The three volume set LNAI 5177, LNAI 5178, and LNAI 5179, constitutes the refereed proceedings of the 12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008, held in Zagreb, Croatia, in September 2008. The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems; fuzzy and neuro-fuzzy systems; evolutionary computation; machine learning and classical AI; agent systems; knowledge based and expert systems; intelligent vision and image processing; knowledge management, ontologies, and data mining; Web intelligence, text and multimedia mining and retrieval; and intelligent robotics and control.

Data Science for Fake News

Author : Deepak P
Publisher : Springer Nature
ISBN 13 : 3030626962
Total Pages : 302 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Data Science for Fake News by : Deepak P

Download or read book Data Science for Fake News written by Deepak P and published by Springer Nature. This book was released on 2021-04-29 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of fake news detection, both through a variety of tutorial-style survey articles that capture advancements in the field from various facets and in a somewhat unique direction through expert perspectives from various disciplines. The approach is based on the idea that advancing the frontier on data science approaches for fake news is an interdisciplinary effort, and that perspectives from domain experts are crucial to shape the next generation of methods and tools. The fake news challenge cuts across a number of data science subfields such as graph analytics, mining of spatio-temporal data, information retrieval, natural language processing, computer vision and image processing, to name a few. This book will present a number of tutorial-style surveys that summarize a range of recent work in the field. In a unique feature, this book includes perspective notes from experts in disciplines such as linguistics, anthropology, medicine and politics that will help to shape the next generation of data science research in fake news. The main target groups of this book are academic and industrial researchers working in the area of data science, and with interests in devising and applying data science technologies for fake news detection. For young researchers such as PhD students, a review of data science work on fake news is provided, equipping them with enough know-how to start engaging in research within the area. For experienced researchers, the detailed descriptions of approaches will enable them to take seasoned choices in identifying promising directions for future research.

Agent-Based Modeling and Network Dynamics

Author : Akira Namatame
Publisher : Oxford University Press
ISBN 13 : 0191074993
Total Pages : 294 pages
Book Rating : 4.1/5 (91 download)

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Book Synopsis Agent-Based Modeling and Network Dynamics by : Akira Namatame

Download or read book Agent-Based Modeling and Network Dynamics written by Akira Namatame and published by Oxford University Press. This book was released on 2016-01-28 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: While the significance of networks in various human behavior and activities has a history as long as human's existence, network awareness is a recent scientific phenomenon. The neologism network science is just one or two decades old. Nevertheless, with this limited time, network thinking has substantially reshaped the recent development in economics, and almost all solutions to real-world problems involve the network element. This book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The authors begin with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling's segregation model and Axelrod's spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The text also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. It reviews a number of pioneering and representative models in this family. Upon the given foundation, the second part reviews three primary forms of network dynamics, such as diffusions, cascades, and influences. These primary dynamics are further extended and enriched by practical networks in goods-and-service markets, labor markets, and international trade. At the end, the book considers two challenging issues using agent-based models of networks: network risks and economic growth.

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Author : Inderjit S. Dhillon
Publisher :
ISBN 13 : 9781450321747
Total Pages : 1534 pages
Book Rating : 4.3/5 (217 download)

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Book Synopsis Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining by : Inderjit S. Dhillon

Download or read book Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining written by Inderjit S. Dhillon and published by . This book was released on 2013 with total page 1534 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Social and Economic Networks

Author : Matthew O. Jackson
Publisher : Princeton University Press
ISBN 13 : 140083399X
Total Pages : 519 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Social and Economic Networks by : Matthew O. Jackson

Download or read book Social and Economic Networks written by Matthew O. Jackson and published by Princeton University Press. This book was released on 2010-11-01 with total page 519 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks of relationships help determine the careers that people choose, the jobs they obtain, the products they buy, and how they vote. The many aspects of our lives that are governed by social networks make it critical to understand how they impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do. In Social and Economic Networks, Matthew Jackson offers a comprehensive introduction to social and economic networks, drawing on the latest findings in economics, sociology, computer science, physics, and mathematics. He provides empirical background on networks and the regularities that they exhibit, and discusses random graph-based models and strategic models of network formation. He helps readers to understand behavior in networked societies, with a detailed analysis of learning and diffusion in networks, decision making by individuals who are influenced by their social neighbors, game theory and markets on networks, and a host of related subjects. Jackson also describes the varied statistical and modeling techniques used to analyze social networks. Each chapter includes exercises to aid students in their analysis of how networks function. This book is an indispensable resource for students and researchers in economics, mathematics, physics, sociology, and business.