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| Author | : Xuzhen Zhu |
| Publisher | : Frontiers Media SA |
| Total Pages | : 209 |
| Release | : 2023-03-01 |
| Genre | : Science |
| ISBN | : 2832516149 |
| Author | : Xinchu Fu |
| Publisher | : John Wiley & Sons |
| Total Pages | : 0 |
| Release | : 2014-02-10 |
| Genre | : Mathematics |
| ISBN | : 1118534506 |
Explores the emerging subject of epidemic dynamics on complex networks, including theories, methods, and real-world applications Throughout history epidemic diseases have presented a serious threat to human life, and in recent years the spread of infectious diseases such as dengue, malaria, HIV, and SARS has captured global attention; and in the modern technological age, the proliferation of virus attacks on the Internet highlights the emergent need for knowledge about modeling, analysis, and control in epidemic dynamics on complex networks. For advancement of techniques, it has become clear that more fundamental knowledge will be needed in mathematical and numerical context about how epidemic dynamical networks can be modelled, analyzed, and controlled. This book explores recent progress in these topics and looks at issues relating to various epidemic systems. Propagation Dynamics on Complex Networks covers most key topics in the field, and will provide a valuable resource for graduate students and researchers interested in network science and dynamical systems, and related interdisciplinary fields. Key Features: Includes a brief history of mathematical epidemiology and epidemic modeling on complex networks. Explores how information, opinion, and rumor spread via the Internet and social networks. Presents plausible models for propagation of SARS and avian influenza outbreaks, providing a reality check for otherwise abstract mathematical modeling. Considers various infectivity functions, including constant, piecewise-linear, saturated, and nonlinear cases. Examines information transmission on complex networks, and investigates the difference between information and epidemic spreading.
| Author | : Ranran Bian |
| Publisher | : |
| Total Pages | : 145 |
| Release | : 2019 |
| Genre | : Computer networks |
| ISBN | : |
Nowadays, large amounts of data are being created daily through ngertips with the emergence of abundant social media. With the exponential growth of the Internet over the past decades, there has been a surge of interest in the capability to extract useful data, trends and structures on these social platforms as they act as a gateway for online commercialization and information propagation. Heterogeneous networks model di erent types of objects and relationships among them. Compared to homogeneous networks, heterogeneous networks can fuse information from multiple data sources and social platforms. Therefore, it is natural to model complex objects and their relationships in big social media data with heterogeneous networks. Despite decades of technique development for various data mining tasks, few of them target heterogeneous networks. Heterogeneity is a key element in contemporary social networks which provides diversi ed perception of networks. Therefore, heterogeneous network analysis has become an important topic in data mining in recent years that has been attracting increasing attention from both industry and academia, as they provide more comprehensive and interesting analysis results than their projected homogeneous networks. Motivated by these considerations, this thesis presents a series of new techniques for knowledge discovery in heterogeneous networks. In particular, the methods proposed in this thesis have been applied to a wide range of applications including community discovery, ranking and information retrieval. For dynamic heterogeneous networks, our research presents a more e ective network embedding technique when compared to the existing state-of-the-art methods. Throughout this thesis, we highlight how our methodologies were able to identify more tightly coupled communities in heterogeneous networks, more accurately rank top performing social actors and having the capability to view heterogeneous networks in a dynamic construct.
| Author | : Yizhou Sun |
| Publisher | : Morgan & Claypool Publishers |
| Total Pages | : 162 |
| Release | : 2012 |
| Genre | : Computers |
| ISBN | : 1608458806 |
Investigates the principles and methodologies of mining heterogeneous information networks. Departing from many existing network models that view interconnected data as homogeneous graphs or networks, the semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from the network.
| Author | : C. Lee Giles |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 141 |
| Release | : 2010-08-10 |
| Genre | : Computers |
| ISBN | : 3642149286 |
This work constitutes the proceedings of the Second International Workshop on Advances in Social Network and Analysis, held in Las Vegas, NV, USA in August 2008.
| Author | : Jie Tang |
| Publisher | : Springer Nature |
| Total Pages | : 193 |
| Release | : 2022-06-01 |
| Genre | : Mathematics |
| ISBN | : 3031794621 |
Online social networks have already become a bridge connecting our physical daily life with the (web-based) information space. This connection produces a huge volume of data, not only about the information itself, but also about user behavior. The ubiquity of the social Web and the wealth of social data offer us unprecedented opportunities for studying the interaction patterns among users so as to understand the dynamic mechanisms underlying different networks, something that was previously difficult to explore due to the lack of available data. In this book, we present the architecture of the research for social network mining, from a microscopic point of view. We focus on investigating several key issues in social networks. Specifically, we begin with analytics of social interactions between users. The first kinds of questions we try to answer are: What are the fundamental factors that form the different categories of social ties? How have reciprocal relationships been developed from parasocial relationships? How do connected users further form groups? Another theme addressed in this book is the study of social influence. Social influence occurs when one's opinions, emotions, or behaviors are affected by others, intentionally or unintentionally. Considerable research has been conducted to verify the existence of social influence in various networks. However, few literature studies address how to quantify the strength of influence between users from different aspects. In Chapter 4 and in [138], we have studied how to model and predict user behaviors. One fundamental problem is distinguishing the effects of different social factors such as social influence, homophily, and individual's characteristics. We introduce a probabilistic model to address this problem. Finally, we use an academic social network, ArnetMiner, as an example to demonstrate how we apply the introduced technologies for mining real social networks. In this system, we try to mine knowledge from both the informative (publication) network and the social (collaboration) network, and to understand the interaction mechanisms between the two networks. The system has been in operation since 2006 and has already attracted millions of users from more than 220 countries/regions.
| Author | : Rokia Missaoui |
| Publisher | : Springer |
| Total Pages | : 263 |
| Release | : 2017-04-29 |
| Genre | : Computers |
| ISBN | : 3319534203 |
The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.
| Author | : Mrutyunjaya Panda |
| Publisher | : Springer |
| Total Pages | : 313 |
| Release | : 2014-07-08 |
| Genre | : Technology & Engineering |
| ISBN | : 3319051644 |
With the proliferation of social media and on-line communities in networked world a large gamut of data has been collected and stored in databases. The rate at which such data is stored is growing at a phenomenal rate and pushing the classical methods of data analysis to their limits. This book presents an integrated framework of recent empirical and theoretical research on social network analysis based on a wide range of techniques from various disciplines like data mining, social sciences, mathematics, statistics, physics, network science, machine learning with visualization techniques and security. The book illustrates the potential of multi-disciplinary techniques in various real life problems and intends to motivate researchers in social network analysis to design more effective tools by integrating swarm intelligence and data mining.
| Author | : Rokia Missaoui |
| Publisher | : Springer |
| Total Pages | : 282 |
| Release | : 2015-01-13 |
| Genre | : Computers |
| ISBN | : 331912188X |
This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edited work will appeal to researchers, practitioners and students interested in the latest developments of social network analysis.
| Author | : Ershi Qi |
| Publisher | : Springer |
| Total Pages | : 927 |
| Release | : 2016-01-29 |
| Genre | : Technology & Engineering |
| ISBN | : 9462391807 |
Being the premier forum for the presentation of new advances and research results in the fields of Industrial Engineering, IEEM 2015 aims to provide a high-level international forum for experts, scholars and entrepreneurs at home and abroad to present the recent advances, new techniques and applications face and face, to promote discussion and interaction among academics, researchers and professionals to promote the developments and applications of the related theories and technologies in universities and enterprises, and to establish business or research relations to find global partners for future collaboration in the field of Industrial Engineering. All the goals of the international conference are to fulfill the mission of the series conference which is to review, exchange, summarize and promote the latest achievements in the field of industrial engineering and engineering management over the past year, and to propose prospects and vision for the further development. This volume is the first of the two proceedings volumes from this conference.
