Social Data Analytics Book

Social Data Analytics


  • Author : Krish Krishnan
  • Publisher : Newnes
  • Release Date : 2014-11-10
  • Genre: Computers
  • Pages : 158
  • ISBN 10 : 9780123977809

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Social Data Analytics Excerpt :

Social Data Analytics is the first practical guide for professionals who want to employ social data for analytics and business intelligence (BI). This book provides a comprehensive overview of the technologies and platforms and shows you how to access and analyze the data. You'll explore the five major types of social data and learn from cases and platform examples to help you make the most of sentiment, behavioral, social graph, location, and rich media data. A four-step approach to the social BI process will help you access, evaluate, collaborate, and share social data with ease. You'll learn everything you need to know to monitor social media and get an overview of the leading vendors in a crowded space of BI applications. By the end of this book, you will be well prepared for your organization’s next social data analytics project. Provides foundational understanding of new and emerging technologies—social data, collaboration, big data, advanced analytics Includes case studies and practical examples of success and failures Will prepare you to lead projects and advance initiatives that will benefit you and your organization

Social Network Data Analytics Book

Social Network Data Analytics


  • Author : Charu C. Aggarwal
  • Publisher : Springer Science & Business Media
  • Release Date : 2011-03-18
  • Genre: Computers
  • Pages : 502
  • ISBN 10 : 9781441984623

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Social Network Data Analytics Excerpt :

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.

Data Analytics for the Social Sciences Book

Data Analytics for the Social Sciences


  • Author : G. David Garson
  • Publisher : Routledge
  • Release Date : 2021-11-30
  • Genre: Psychology
  • Pages : 704
  • ISBN 10 : 9781000467086

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Data Analytics for the Social Sciences Excerpt :

Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.

Social Media Data Mining and Analytics Book

Social Media Data Mining and Analytics


  • Author : Gabor Szabo
  • Publisher : John Wiley & Sons
  • Release Date : 2018-09-19
  • Genre: Computers
  • Pages : 352
  • ISBN 10 : 9781118824894

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Social Media Data Mining and Analytics Excerpt :

Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.

Social Data Analytics Book

Social Data Analytics


  • Author : Amin Beheshti
  • Publisher : CRC Press
  • Release Date : 2022-08-01
  • Genre: Business & Economics
  • Pages : 250
  • ISBN 10 : 9781000644609

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Social Data Analytics Excerpt :

This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on concepts, techniques and methods for organizing, curating, processing, analyzing, and visualizing big social data: from text to image and video analytics. It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery. The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts, problems, methods, tools and techniques involved in modern social data analytics. It also provides real-world applications of social data analytics, including: Sales and Marketing, Influence Maximization, Situational Awareness, customer success and Segmentation, and performance analysis of the industry. It provides a deep knowledge in social data analytics by comprehensively classifying the current state of research, by describing in-depth techniques and methods, and by highlighting future research directions. Lecturers will find a wealth of material to choose from for a variety of courses, ranging from undergraduate courses in data science to graduate courses in data analytics.

Challenges and Applications of Data Analytics in Social Perspectives Book

Challenges and Applications of Data Analytics in Social Perspectives


  • Author : Sathiyamoorthi, V.
  • Publisher : IGI Global
  • Release Date : 2020-12-04
  • Genre: Computers
  • Pages : 324
  • ISBN 10 : 9781799825685

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Challenges and Applications of Data Analytics in Social Perspectives Excerpt :

With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.

Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics Book

Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics


  • Author : Atsushi Nara
  • Publisher : Springer
  • Release Date : 2021-11-04
  • Genre: Social Science
  • Pages : 283
  • ISBN 10 : 3030830098

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Empowering Human Dynamics Research with Social Media and Geospatial Data Analytics Excerpt :

This book discusses theoretical backgrounds, techniques and methodologies, and applications of the current state-of-the-art human dynamics research utilizing social media and geospatial big data. It describes various forms of social media and big data with location information, theory development, data collection and management techniques, and analytical methodologies to conduct human dynamics research including geographic information systems (GIS), spatiotemporal data analytics, text mining and semantic analysis, machine learning, trajectory data analysis, and geovisualization. The book also covers applied interdisciplinary research examples ranging from disaster management, public health, urban geography, and spatiotemporal information diffusion. By providing theoretical foundations, solid empirical research backgrounds, techniques, and methodologies as well as application examples from diverse interdisciplinary fields, this book will be a valuable resource to students, researchers and practitioners who utilize or plan to employ social media and big data in their work.

Big Data Analytics Book

Big Data Analytics


  • Author : Mrutyunjaya Panda
  • Publisher : CRC Press
  • Release Date : 2018-12-12
  • Genre: Business & Economics
  • Pages : 316
  • ISBN 10 : 9781351622592

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Big Data Analytics Excerpt :

Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

Big Data Analytics in Cognitive Social Media and Literary Texts Book

Big Data Analytics in Cognitive Social Media and Literary Texts


  • Author : Sanjiv Sharma
  • Publisher : Springer Nature
  • Release Date : 2021-11-11
  • Genre: Language Arts & Disciplines
  • Pages : 300
  • ISBN 10 : 9789811647291

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Big Data Analytics in Cognitive Social Media and Literary Texts Excerpt :

This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.

Social Big Data Analytics Book

Social Big Data Analytics


  • Author : Bilal Abu-Salih
  • Publisher : Springer Nature
  • Release Date : 2021-03-10
  • Genre: Business & Economics
  • Pages : 218
  • ISBN 10 : 9789813366527

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Social Big Data Analytics Excerpt :

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This boo

Mobility Analytics for Spatio Temporal and Social Data Book

Mobility Analytics for Spatio Temporal and Social Data


  • Author : Christos Doulkeridis
  • Publisher : Springer
  • Release Date : 2018-01-05
  • Genre: Computers
  • Pages : 177
  • ISBN 10 : 9783319735214

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Mobility Analytics for Spatio Temporal and Social Data Excerpt :

This book constitutes the refereed post-conference proceedings of the First International Workshop on Mobility Analytics for Spatio-Temporal and Social Data, MATES 2017, held in Munich, Germany, in September 2017. The 6 revised full papers and 2 short papers included in this volume were carefully reviewed and selected from 13 submissions. Also included are two keynote speeches. The papers intend to raise awareness of real-world problems in critical domains which require novel data management solutions. They are organized in two thematic sections: social network analytics and applications, and spatio-temporal mobility analytics.

Big Data and Social Media Analytics Book

Big Data and Social Media Analytics


  • Author : Mehmet Çakırtaş
  • Publisher : Springer Nature
  • Release Date : 2021-07-05
  • Genre: Mathematics
  • Pages : 245
  • ISBN 10 : 9783030670443

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Big Data and Social Media Analytics Excerpt :

This edited book provides techniques which address various aspects of big data collection and analysis from social media platforms and beyond. It covers efficient compression of large networks, link prediction in hashtag graphs, visual exploration of social media data, identifying motifs in multivariate data, social media surveillance to enhance search and rescue missions, recommenders for collaborative filtering and safe travel plans to high risk destinations, analysis of cyber influence campaigns on YouTube, impact of location on business rating, bibliographical and co-authorship network analysis, and blog data analytics. All these trending topics form a major part of the state of the art in social media and big data analytics. Thus, this edited book may be considered as a valuable source for readers interested in grasping some of the most recent advancements in this high trending domain.

Cognitive Social Mining Applications in Data Analytics and Forensics Book

Cognitive Social Mining Applications in Data Analytics and Forensics


  • Author : Haldorai, Anandakumar
  • Publisher : IGI Global
  • Release Date : 2018-12-14
  • Genre: Computers
  • Pages : 326
  • ISBN 10 : 9781522575238

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Cognitive Social Mining Applications in Data Analytics and Forensics Excerpt :

Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data. Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.

Social Media Analytics Strategy Book

Social Media Analytics Strategy


  • Author : Alex Gonçalves
  • Publisher : Apress
  • Release Date : 2017-11-12
  • Genre: Business & Economics
  • Pages : 306
  • ISBN 10 : 9781484231029

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Social Media Analytics Strategy Excerpt :

This book shows you how to use social media analytics to optimize your business performance. The tools discussed will prepare you to create and implement an effective digital marketing strategy. From understanding the data and its sources to detailed metrics, dashboards, and reports, this book is a robust tool for anyone seeking a tangible return on investment from social media and digital marketing. Social Media Analytics Strategy speaks to marketers who do not have a technical background and creates a bridge into the digital world. Comparable books are either too technical for marketers (aimed at software developers) or too basic and do not take strategy into account. They also lack an overview of the entire process around using analytics within a company project. They don’t go into the everyday details and also don’t touch upon common mistakes made by marketers. This book highlights patterns of common challenges experienced by marketers from entry level to directors and C-level executives. Social media analytics are explored and explained using real-world examples and interviews with experienced professionals and founders of social media analytics companies. What You’ll Learn Get a clear view of the available data for social media marketing and how to access all of it Make use of data and information behind social media networks to your favor Know the details of social media analytics tools and platforms so you can use any tool in the market Apply social media analytics to many different real-world use cases Obtain tips from interviews with professional marketers and founders of social media analytics platforms Understand where social media is heading, and what to expect in the future Who This Book Is For Marketing professionals, social media marketing specialists, analysts up to directors and C-level executives, marketing students, and teachers of social media analytics/social media marketing

Big Data Analytics for Sustainable Computing Book

Big Data Analytics for Sustainable Computing


  • Author : Haldorai, Anandakumar
  • Publisher : IGI Global
  • Release Date : 2019-09-20
  • Genre: Computers
  • Pages : 263
  • ISBN 10 : 9781522597520

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Big Data Analytics for Sustainable Computing Excerpt :

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.