Download or read book Community detection and mining in social media written by Lei Tang and published by Springer Nature. This book was released on 2022-06-01 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade has witnessed the emergence of participatory Web and social media, bringing people together in many creative ways. Millions of users are playing, tagging, working, and socializing online, demonstrating new forms of collaboration, communication, and intelligence that were hardly imaginable just a short time ago. Social media also helps reshape business models, sway opinions and emotions, and opens up numerous possibilities to study human interaction and collective behavior in an unparalleled scale. This lecture, from a data mining perspective, introduces characteristics of social media, reviews representative tasks of computing with social media, and illustrates associated challenges. It introduces basic concepts, presents state-of-the-art algorithms with easy-to-understand examples, and recommends effective evaluation methods. In particular, we discuss graph-based community detection techniques and many important extensions that handle dynamic, heterogeneous networks in social media. We also demonstrate how discovered patterns of communities can be used for social media mining. The concepts, algorithms, and methods presented in this lecture can help harness the power of social media and support building socially-intelligent systems. This book is an accessible introduction to the study of \emph{community detection and mining in social media}. It is an essential reading for students, researchers, and practitioners in disciplines and applications where social media is a key source of data that piques our curiosity to understand, manage, innovate, and excel. This book is supported by additional materials, including lecture slides, the complete set of figures, key references, some toy data sets used in the book, and the source code of representative algorithms. The readers are encouraged to visit the book website for the latest information. Table of Contents: Social Media and Social Computing / Nodes, Ties, and Influence / Community Detection and Evaluation / Communities in Heterogeneous Networks / Social Media Mining

Download or read book Parallel Problem Solving from Nature PPSN X written by Günter Rudolph and published by Springer Science & Business Media. This book was released on 2008-09-10 with total page 1183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Parallel Problem Solving from Nature, PPSN 2008, held in Dortmund, Germany, in September 2008. The 114 revised full papers presented were carefully reviewed and selected from 206 submissions. The conference covers a wide range of topics, such as evolutionary computation, quantum computation, molecular computation, neural computation, artificial life, swarm intelligence, artificial ant systems, artificial immune systems, self-organizing systems, emergent behaviors, and applications to real-world problems. The paper are organized in topical sections on formal theory, new techniques, experimental analysis, multiobjective optimization, hybrid methods, and applications.

Download or read book Social Computing and Behavioral Modeling written by Huan Liu and published by Springer Science & Business Media. This book was released on 2009-04-05 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social computing is concerned with the study of social behavior and social c- text based on computational systems. Behavioral modeling reproduces the social behavior, and allows for experimenting, scenario planning, and deep understa- ing of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies provides an unprecedented environment of various - cial activities. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, and prediction. Numerous interdisciplinary and inter- pendent systems are created and used to represent the various social and physical systems for investigating the interactions between groups, communities, or nati- states. This requires joint efforts to take advantage of the state-of-the-art research from multiple disciplines, social computing, and behavioral modeling in order to document lessons learned and develop novel theories, experiments, and methodo- gies in terms of social, physical, psychological, and governmental mechanisms. The goal is to enable us to experiment, create, and recreate an operational environment with a better understanding of the contributions from each individual discipline, forging joint interdisciplinary efforts. This is the second international workshop on Social Computing, Behavioral ModelingandPrediction. The submissions were from Asia, Australia, Europe, and America. Since SBP09 is a single-track workshop, we could not accept all the good submissions. The accepted papers cover a wide range of interesting topics.

Download or read book Graph Theoretic Approaches for Analyzing Large Scale Social Networks written by Meghanathan, Natarajan and published by IGI Global. This book was released on 2017-07-13 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis has created novel opportunities within the field of data science. The complexity of these networks requires new techniques to optimize the extraction of useful information. Graph Theoretic Approaches for Analyzing Large-Scale Social Networks is a pivotal reference source for the latest academic research on emerging algorithms and methods for the analysis of social networks. Highlighting a range of pertinent topics such as influence maximization, probabilistic exploration, and distributed memory, this book is ideally designed for academics, graduate students, professionals, and practitioners actively involved in the field of data science.

Download or read book Social Network Analysis Community Detection and Evolution written by Rokia Missaoui and published by Springer. This book was released on 2015-01-13 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Models and Theories in Social Systems written by Cristina Flaut and published by Springer. This book was released on 2018-10-12 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concisely presents a broad range of models and theories on social systems. Because of the huge spectrum of topics involving social systems, various issues related to Mathematics, Statistics, Teaching, Social Science, and Economics are discussed. In an effort to introduce the subject to a wider audience, this volume, part of the series “Studies in Systems, Decision and Control”, equally addresses the needs of mathematicians, statisticians, sociologists and philosophers. The studies examined here are divided into four parts. The first part, “Perusing the Minds Behind Scientific Discoveries”, traces the winding path of Syamal K. Sen and Ravi P. Agarwal’s scholarship throughout history, and most importantly, the thought processes that allowed each of them to master their subject. The second part covers “Theories in Social Systems” and the third discusses “Models in Social Systems”, while the fourth and final part is dedicated to “Mathematical Methods in the Social Sciences”. Given its breadth of coverage, the book will offer inquisitive readers a valuable point of departure for exploring these rich, vast, and ever-expanding fields of knowledge.

Download or read book Social Media Mining written by Reza Zafarani and published by Cambridge University Press. This book was released on 2014-04-28 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrates social media, social network analysis, and data mining to provide an understanding of the potentials of social media mining.

Download or read book Deep South written by Allison Davis and published by Univ of South Carolina Press. This book was released on 2009 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: First published in 1941, Deep South is the cooperative effort of a team of social anthropologists to document the economic, racial, and cultural character of the Jim Crow South through a study of a representative rural Mississippi community. Researchers Allison Davis, Burleigh B. Gardner, and Mary R. Gardner lived among the people of Natchez, Mississippi, as they investigated how class and caste informed daily life in a typical southern community. This Southern Classics edition of their study offers contemporary students of history a provocative collection of primary material gathered by conscientious and well-trained participant-observers, who found then, as now, intertwined social and economic inequalities at the root of racial tensions. Expanding on earlier studies of community stratification by social class, researchers in the Deep South Project introduced the additional concept of caste, which parsed a community through rigid social ranks assigned at birth and unalterable through life, a concept readily identifiable in the racial divisions of the Jim Crow South. As African American researchers, Davis and his wife, Elizabeth, along with his assistant St. Clair Drake, were able to gain unrivaled access to the black community in rural Mississippi, unavailable to their white counterparts. Through their interviews and experiences, the authors vividly capture the nuances in caste-enforcing systems of tenant-landlord relations, local government, and law enforcement. But the chief achievement of Deep South is its rich analysis of how the southern economic system, and sharecropping in particular, functioned to maintain rigid caste divisions along racial lines. In the new introduction to this edition, Jennifer Jensen Wallach situates this germinal study within the field of social anthropology and against the backdrop of similar community studies of the era. She also details the subsequent careers of this distinguished team of researchers.

Download or read book Small Worlds written by Duncan J. Watts and published by Princeton University Press. This book was released on 2018-06-05 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Everyone knows the small-world phenomenon: soon after meeting a stranger, we are surprised to discover that we have a mutual friend, or we are connected through a short chain of acquaintances. In his book, Duncan Watts uses this intriguing phenomenon--colloquially called "six degrees of separation"--as a prelude to a more general exploration: under what conditions can a small world arise in any kind of network? The networks of this story are everywhere: the brain is a network of neurons; organisations are people networks; the global economy is a network of national economies, which are networks of markets, which are in turn networks of interacting producers and consumers. Food webs, ecosystems, and the Internet can all be represented as networks, as can strategies for solving a problem, topics in a conversation, and even words in a language. Many of these networks, the author claims, will turn out to be small worlds. How do such networks matter? Simply put, local actions can have global consequences, and the relationship between local and global dynamics depends critically on the network's structure. Watts illustrates the subtleties of this relationship using a variety of simple models---the spread of infectious disease through a structured population; the evolution of cooperation in game theory; the computational capacity of cellular automata; and the sychronisation of coupled phase-oscillators. Watts's novel approach is relevant to many problems that deal with network connectivity and complex systems' behaviour in general: How do diseases (or rumours) spread through social networks? How does cooperation evolve in large groups? How do cascading failures propagate through large power grids, or financial systems? What is the most efficient architecture for an organisation, or for a communications network? This fascinating exploration will be fruitful in a remarkable variety of fields, including physics and mathematics, as well as sociology, economics, and biology.

Download or read book Community Structure of Complex Networks written by Hua-Wei Shen and published by Springer Science & Business Media. This book was released on 2013-01-06 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Community structure is a salient structural characteristic of many real-world networks. Communities are generally hierarchical, overlapping, multi-scale and coexist with other types of structural regularities of networks. This poses major challenges for conventional methods of community detection. This book will comprehensively introduce the latest advances in community detection, especially the detection of overlapping and hierarchical community structures, the detection of multi-scale communities in heterogeneous networks, and the exploration of multiple types of structural regularities. These advances have been successfully applied to analyze large-scale online social networks, such as Facebook and Twitter. This book provides readers a convenient way to grasp the cutting edge of community detection in complex networks. The thesis on which this book is based was honored with the “Top 100 Excellent Doctoral Dissertations Award” from the Chinese Academy of Sciences and was nominated as the “Outstanding Doctoral Dissertation” by the Chinese Computer Federation.

Download or read book Discovery Science written by João Gama and published by Springer. This book was released on 2009-10-07 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the twelfth International Conference, on Discovery Science, DS 2009, held in Porto, Portugal, in October 2009. The 35 revised full papers presented were carefully selected from 92 papers. The scope of the conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their applications.

Download or read book Advances in Network Clustering and Blockmodeling written by Patrick Doreian and published by John Wiley & Sons. This book was released on 2020-02-03 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of the developments and advances in the field of network clustering and blockmodeling over the last 10 years This book offers an integrated treatment of network clustering and blockmodeling, covering all of the newest approaches and methods that have been developed over the last decade. Presented in a comprehensive manner, it offers the foundations for understanding network structures and processes, and features a wide variety of new techniques addressing issues that occur during the partitioning of networks across multiple disciplines such as community detection, blockmodeling of valued networks, role assignment, and stochastic blockmodeling. Written by a team of international experts in the field, Advances in Network Clustering and Blockmodeling offers a plethora of diverse perspectives covering topics such as: bibliometric analyses of the network clustering literature; clustering approaches to networks; label propagation for clustering; and treating missing network data before partitioning. It also examines the partitioning of signed networks, multimode networks, and linked networks. A chapter on structured networks and coarsegrained descriptions is presented, along with another on scientific coauthorship networks. The book finishes with a section covering conclusions and directions for future work. In addition, the editors provide numerous tables, figures, case studies, examples, datasets, and more. Offers a clear and insightful look at the state of the art in network clustering and blockmodeling Provides an excellent mix of mathematical rigor and practical application in a comprehensive manner Presents a suite of new methods, procedures, algorithms for partitioning networks, as well as new techniques for visualizing matrix arrays Features numerous examples throughout, enabling readers to gain a better understanding of research methods and to conduct their own research effectively Written by leading contributors in the field of spatial networks analysis Advances in Network Clustering and Blockmodeling is an ideal book for graduate and undergraduate students taking courses on network analysis or working with networks using real data. It will also benefit researchers and practitioners interested in network analysis.

Download or read book Intelligent Systems Design and Applications written by Ajith Abraham and published by Springer. This book was released on 2019-04-13 with total page 1114 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent research on Intelligent Systems and Nature Inspired Computing. It presents 212 selected papers from the 18th International Conference on Intelligent Systems Design and Applications (ISDA 2018) and the 10th World Congress on Nature and Biologically Inspired Computing (NaBIC), which was held at VIT University, India. ISDA-NaBIC 2018 was a premier conference in the field of Computational Intelligence and brought together researchers, engineers and practitioners whose work involved intelligent systems and their applications in industry and the “real world.” Including contributions by authors from over 40 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.

Download or read book From Security to Community Detection in Social Networking Platforms written by Panagiotis Karampelas and published by Springer. This book was released on 2019-04-09 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on novel and state-of-the-art scientific work in the area of detection and prediction techniques using information found generally in graphs and particularly in social networks. Community detection techniques are presented in diverse contexts and for different applications while prediction methods for structured and unstructured data are applied to a variety of fields such as financial systems, security forums, and social networks. The rest of the book focuses on graph-based techniques for data analysis such as graph clustering and edge sampling. The research presented in this volume was selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. This book will appeal to practitioners, researchers and students in the field.

Download or read book Principles of Social Networking written by Anupam Biswas and published by Springer Nature. This book was released on 2021-08-18 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new and innovative current discoveries in social networking which contribute enough knowledge to the research community. The book includes chapters presenting research advances in social network analysis and issues emerged with diverse social media data. The book also presents applications of the theoretical algorithms and network models to analyze real-world large-scale social networks and the data emanating from them as well as characterize the topology and behavior of these networks. Furthermore, the book covers extremely debated topics, surveys, future trends, issues, and challenges.

Download or read book Complex Networks Their Applications IX written by Rosa M. Benito and published by Springer Nature. This book was released on 2020-12-19 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the IX International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks and technological networks.

Download or read book Scalable Community Detection for Social Networks written by Arnau Prat Pérez and published by . This book was released on 2016 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many applications can be modeled intuitively as graphs, where nodes represent the entities and the edges the relationships between them. This way, we are able to better understand them and how they interact. One particularity of these graphs is that their entities are organized in modules called communities. A community is informally defined as a set of nodes more densely connected internally than externally. For instance, in the case of a social network, persons with similar characteristics are grouped forming communities. Community detection has become a hot topic in the research community during the last years, due to its amount of applications. For instance, in social networks, communities give information about the persons forming them, by just looking at the relationships linking them. This is used in directing marketing campaigns, recomendation systems or in link prediction. Because of the relevance of the problem, many community detection algorithms exist, which follow different strategies. Most of them are based on the well known modularity metric, though other techniques based on random walks and epidemics spreading also exist. The problem of existing algorithms is that they have been designed to be generic, completely ignoring the particularities of the graphs belonging to different domains. As a result and under certain circumstances, these algorithms tend to find groups of nodes with a lack of a community structure. This thesis, overcomes this issues by proposing a novel community detection algorithm design methodology, called Domain Specific Community detection. This methodology is based on defining a set of structural properties communities of a given domain should fulfill, as well a set of behavioral properties to be fulfilled by a community detection algorithm or metric. Based on this methodology, we propose a set of properties for the specific domain of social networks, consisting of three structural properties (Internal structure sensitive, Bridges resistant and Cut-Vertex resistant) and three behavioral properties (Scale independent, Adaptive and Lineal community cohesion). Based on the aforementioned properties, we design a novel community detection metric, called the Weighted Community Clustering (WCC), which takes the presence of a triangle as an indicator of a strong relation between two persons in a social network. We formally prove that WCC fulfills the proposed properties, thus guaranteeting that communities resulting from maximizing WCC have a minimum degree of quality. Moreover, we prove this last statement by performing an empirical analysis on communities from real graphs, showing that WCC is able to correclty rank these well. In this thesis we also propose an algorithm called Scalable Community Detection (SCD), based on the maximization of WCC. SCD is also designed with parallelism in mind, in order to take advantage of current many-core architectures. We show that SCD is to detect communities with an unprecedented quality, being its execution time faster than most of existing proposals, being able to process billion edge graphs in a few hours This thesis also includes a statistical study about the structural characteristics of the meta-groups found in several real graphs, comparing these to graph from two different synthetic graph generators. We show that communities produced by a synthetic graph generator commonly used in community detection research are very dissimilar to those found in real graphs. Finally, this thesis includes a study on how to implement a triangle counting algorithm on a modern many core architecture, more concretely the Intel Single Chip Cloud Computer (Intel SCC).