State of the Art Applications of Social Network Analysis


Book Description

Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user’s- behavior, privacy in social network analysis, mobility from spatio-temporal point of view, agent technology and political parties in parliament. These topics will be of interest to researchers and practitioners from different disciplines including, but not limited to, social sciences and engineering.




Sentiment Analysis in Social Networks


Book Description

The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network analysis - Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network mining - Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics




Social Networks: Analysis and Case Studies


Book Description

The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many opportunities in different application domains. Forming a bridge between theory and applications makes this work appealing to both academics and practitioners as well as graduate students.




Social Network Data Analytics


Book Description

Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.




Serious Games


Book Description

This book constitutes the proceedings of the First Joint International Conference on Serious Games, JCSG 2015, held in Huddersfield, UK, in June 2015. This conference bundles the activities of the International Conference on Serious Games Development and Applications, SGDA, and the Conference on Serious Games, GameDays. The total of 12 full papers and 5 short papers was carefully reviewed and selected from 31 submissions. The book also contains one full invited talk. The papers were organized in topical sections named: games for health; games for learning; games for other purposes; game design and development; and poster and demo papers.




Analyzing Social Networks


Book Description

Written by a stellar team of experts, Analyzing Social Networks is a practical book on how to collect, visualize, analyze and interpret social network data with a particular emphasis on the use of the software tools UCINET and Netdraw. The book includes a clear and detailed introduction to the fundamental concepts of network analyses, including centrality, subgroups, equivalence and network structure, as well as cross-cutting chapters that helpfully show how to apply network concepts to different kinds of networks. Written using simple language and notation with few equations, this book masterfully covers the research process, including: · The initial design stage · Data collection and manipulation · Measuring key variables · Exploration of structure · Hypothesis testing · Interpretation This is an essential resource for students, researchers and practitioners across the social sciences who want to use network analysis as part of their research. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.




Disaster Resilience


Book Description

No person or place is immune from disasters or disaster-related losses. Infectious disease outbreaks, acts of terrorism, social unrest, or financial disasters in addition to natural hazards can all lead to large-scale consequences for the nation and its communities. Communities and the nation thus face difficult fiscal, social, cultural, and environmental choices about the best ways to ensure basic security and quality of life against hazards, deliberate attacks, and disasters. Beyond the unquantifiable costs of injury and loss of life from disasters, statistics for 2011 alone indicate economic damages from natural disasters in the United States exceeded $55 billion, with 14 events costing more than a billion dollars in damages each. One way to reduce the impacts of disasters on the nation and its communities is to invest in enhancing resilience-the ability to prepare and plan for, absorb, recover from and more successfully adapt to adverse events. Disaster Resilience: A National Imperative addresses the broad issue of increasing the nation's resilience to disasters. This book defines "national resilience", describes the state of knowledge about resilience to hazards and disasters, and frames the main issues related to increasing resilience in the United States. It also provide goals, baseline conditions, or performance metrics for national resilience and outlines additional information, data, gaps, and/or obstacles that need to be addressed to increase the nation's resilience to disasters. Additionally, the book's authoring committee makes recommendations about the necessary approaches to elevate national resilience to disasters in the United States. Enhanced resilience allows better anticipation of disasters and better planning to reduce disaster losses-rather than waiting for an event to occur and paying for it afterward. Disaster Resilience confronts the topic of how to increase the nation's resilience to disasters through a vision of the characteristics of a resilient nation in the year 2030. Increasing disaster resilience is an imperative that requires the collective will of the nation and its communities. Although disasters will continue to occur, actions that move the nation from reactive approaches to disasters to a proactive stance where communities actively engage in enhancing resilience will reduce many of the broad societal and economic burdens that disasters can cause.




Applications of Social Network Analysis for Building Community Disaster Resilience


Book Description

Social Network Analysis (SNA) is the identification of the relationships and attributes of members, key actors, and groups that social networks comprise. The National Research Council, at the request of the Department of Homeland Security, held a two-day workshop on the use of SNA for the purpose of building community disaster resilience. The workshop, summarized in this volume, was designed to provide guidance to the DHS on a potential research agenda that would increase the effectiveness of SNA for improving community disaster resilience. The workshop explored the state of the art in SNA and its applications in the identification, construction, and strengthening of networks within U.S. communities. Workshop participants discussed current work in SNA focused on characterizing networks; the theories, principles and research applicable to the design or strengthening of networks; the gaps in knowledge that prevent the application of SNA to the construction of networks; and research areas that could fill those gaps. Elements of a research agenda to support the design, development, and implementation of social networks for the specific purpose of strengthening community resilience against natural and human-made disasters were discussed.




Security and Privacy in Social Networks and Big Data


Book Description

This book constitutes the proceedings of the 9th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2023, which took place in Canterbury, UK, in August 2023. The 10 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 29 submissions. They were organized in topical sections as follows: information abuse and political discourse; attacks; social structure and community; and security and privacy matters. Papers "Data Reconstruction Attack Against Principal Component Analysis" and "Edge local Differential Privacy for Dynamic Graphs" are published Open Access under the CC BY 4.0 License.




Applications of Social Media and Social Network Analysis


Book Description

This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to communities of open source software developers, biometric template generation as well as analysis of user behavior within heterogeneous environments of cultural educational centers. Addressing these challenging applications is what makes this edited volume of interest to researchers and students focused on social media and social network analysis.