Social Data Analytics

Social Data Analytics
Author: Krish Krishnan,Shawn P. Rogers
Publsiher: Newnes
Total Pages: 158
Release: 2014-11-10
ISBN 10: 0123977800
ISBN 13: 9780123977809
Language: EN, FR, DE, ES & NL

Social Data Analytics Book Review:

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

Social Network Data Analytics
Author: Charu C. Aggarwal
Publsiher: Springer Science & Business Media
Total Pages: 502
Release: 2011-03-18
ISBN 10: 1441984623
ISBN 13: 9781441984623
Language: EN, FR, DE, ES & NL

Social Network Data Analytics Book Review:

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.

Challenges and Applications of Data Analytics in Social Perspectives

Challenges and Applications of Data Analytics in Social Perspectives
Author: Sathiyamoorthi, V.,Elci, Atilla
Publsiher: IGI Global
Total Pages: 324
Release: 2020-12-04
ISBN 10: 179982568X
ISBN 13: 9781799825685
Language: EN, FR, DE, ES & NL

Challenges and Applications of Data Analytics in Social Perspectives Book Review:

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.

Big Data Analytics

Big Data Analytics
Author: Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien
Publsiher: CRC Press
Total Pages: 316
Release: 2018-12-12
ISBN 10: 1351622595
ISBN 13: 9781351622592
Language: EN, FR, DE, ES & NL

Big Data Analytics Book Review:

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.

Social Big Data Analytics

Social Big Data Analytics
Author: Bilal Abu-Salih,Pornpit Wongthongtham,Dengya Zhu,Kit Yan Chan,Amit Rudra
Publsiher: Springer
Total Pages: 218
Release: 2021-03-11
ISBN 10: 9789813366510
ISBN 13: 9813366516
Language: EN, FR, DE, ES & NL

Social Big Data Analytics Book Review:

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 book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.

Social Big Data Analytics

Social Big Data Analytics
Author: Bilal Abu-Salih
Publsiher: Springer Nature
Total Pages: 329
Release: 2021
ISBN 10: 9813366524
ISBN 13: 9789813366527
Language: EN, FR, DE, ES & NL

Social Big Data Analytics Book Review:

Mobility Analytics for Spatio Temporal and Social Data

Mobility Analytics for Spatio Temporal and Social Data
Author: Christos Doulkeridis,George A. Vouros,Qiang Qu,Shuhui Wang
Publsiher: Springer
Total Pages: 177
Release: 2018-02-01
ISBN 10: 3319735217
ISBN 13: 9783319735214
Language: EN, FR, DE, ES & NL

Mobility Analytics for Spatio Temporal and Social Data Book Review:

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.

Data Science and Social Research

Data Science and Social Research
Author: N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino
Publsiher: Springer
Total Pages: 300
Release: 2017-11-17
ISBN 10: 3319554778
ISBN 13: 9783319554778
Language: EN, FR, DE, ES & NL

Data Science and Social Research Book Review:

This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices.

Social Media Data Extraction and Content Analysis

Social Media Data Extraction and Content Analysis
Author: Hai-Jew, Shalin
Publsiher: IGI Global
Total Pages: 493
Release: 2016-08-01
ISBN 10: 1522506497
ISBN 13: 9781522506492
Language: EN, FR, DE, ES & NL

Social Media Data Extraction and Content Analysis Book Review:

In today’s society, the utilization of social media platforms has become an abundant forum for individuals to post, share, tag, and, in some cases, overshare information about their daily lives. As significant amounts of data flood these venues, it has become necessary to find ways to collect and evaluate this information. Social Media Data Extraction and Content Analysis explores various social networking platforms and the technologies being utilized to gather and analyze information being posted to these venues. Highlighting emergent research, analytical techniques, and best practices in data extraction in global electronic culture, this publication is an essential reference source for researchers, academics, and professionals.

Big Data Analytics in the Social and Ubiquitous Context

Big Data Analytics in the Social and Ubiquitous Context
Author: Martin Atzmueller,Alvin Chin,Frederik Janssen,Immanuel Schweizer,Christoph Trattner
Publsiher: Springer
Total Pages: 187
Release: 2016-01-06
ISBN 10: 3319290096
ISBN 13: 9783319290096
Language: EN, FR, DE, ES & NL

Big Data Analytics in the Social and Ubiquitous Context Book Review:

The 9 papers presented in this book are revised and significantly extended versions of papers submitted to three related workshops: The 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and the First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, which were held on September 15, 2014, in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2014) in Nancy, France; and the 5th International Workshop on Modeling Social Media (MSM 2014) that was held on April 8, 2014 in conjunction with ACM WWW in Seoul, Korea.

Social Media Data Mining and Analytics

Social Media Data Mining and Analytics
Author: Gabor Szabo,Gungor Polatkan,P. Oscar Boykin,Antonios Chalkiopoulos
Publsiher: John Wiley & Sons
Total Pages: 352
Release: 2018-09-19
ISBN 10: 111882489X
ISBN 13: 9781118824894
Language: EN, FR, DE, ES & NL

Social Media Data Mining and Analytics Book Review:

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 Network Analytics

Social Network Analytics
Author: Nilanjan Dey,Samarjeet Borah,Rosalina Babo,Amira S. Ashour
Publsiher: Academic Press
Total Pages: 267
Release: 2018-11-16
ISBN 10: 0128156414
ISBN 13: 9780128156414
Language: EN, FR, DE, ES & NL

Social Network Analytics Book Review:

Social Network Analytics: Computational Research Methods and Techniques focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, it includes a variety of applications from several domains, such as scientific research, and the business and industrial sectors. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, the big data analytics of social networks, multidimensional scaling, and more. As analyzing social network data is rapidly gaining interest in the scientific research community because of the importance of the information and insights that can be culled from the wealth of data inherent in the various aspects of the network, this book provides insights on measuring the relationships and flows between people, groups, organizations, computers, URLs, and more. Examines a variety of data analytic techniques that can be applied to social networks Discusses various methods of visualizing, modeling and tracking network patterns, organization, growth and change Covers the most recent research on social network analysis and includes applications to a number of domains

Social Media Analytics Strategy

Social Media Analytics Strategy
Author: Alex Gonçalves
Publsiher: Apress
Total Pages: 306
Release: 2017-11-12
ISBN 10: 1484231023
ISBN 13: 9781484231029
Language: EN, FR, DE, ES & NL

Social Media Analytics Strategy Book Review:

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

Learning Social Media Analytics with R

Learning Social Media Analytics with R
Author: Raghav Bali,Dipanjan Sarkar,Tushar Sharma
Publsiher: Packt Publishing Ltd
Total Pages: 394
Release: 2017-05-26
ISBN 10: 1787125467
ISBN 13: 9781787125469
Language: EN, FR, DE, ES & NL

Learning Social Media Analytics with R Book Review:

Tap into the realm of social media and unleash the power of analytics for data-driven insights using R About This Book A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms. Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering. Who This Book Is For It is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise. What You Will Learn Learn how to tap into data from diverse social media platforms using the R ecosystem Use social media data to formulate and solve real-world problems Analyze user social networks and communities using concepts from graph theory and network analysis Learn to detect opinion and sentiment, extract themes, topics, and trends from unstructured noisy text data from diverse social media channels Understand the art of representing actionable insights with effective visualizations Analyze data from major social media channels such as Twitter, Facebook, Flickr, Foursquare, Github, StackExchange, and so on Learn to leverage popular R packages such as ggplot2, topicmodels, caret, e1071, tm, wordcloud, twittR, Rfacebook, dplyr, reshape2, and many more In Detail The Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how analytics can be leveraged to derive insights from it. This data can be analyzed to gain valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers frame business problems and solve them using social data. The book will also cover several practical real-world use cases on social media using R and its advanced packages to utilize data science methodologies such as sentiment analysis, topic modeling, text summarization, recommendation systems, social network analysis, classification, and clustering. This will enable readers to learn different hands-on approaches to obtain data from diverse social media sources such as Twitter and Facebook. It will also show readers how to establish detailed workflows to process, visualize, and analyze data to transform social data into actionable insights. Style and approach This book follows a step-by-step approach with detailed strategies for understanding, extracting, analyzing, visualizing, and modeling data from several major social network platforms such as Facebook, Twitter, Foursquare, Flickr, Github, and StackExchange. The chapters cover several real-world use cases and leverage data science, machine learning, network analysis, and graph theory concepts along with the R ecosystem, including popular packages such as ggplot2, caret,dplyr, topicmodels, tm, and so on.

Big Data and Social Media Analytics

Big Data and Social Media Analytics
Author: Mehmet Çakırtaş,Mehmet Kemal Ozdemir
Publsiher: Springer
Total Pages: 245
Release: 2021-07-15
ISBN 10: 9783030670436
ISBN 13: 3030670430
Language: EN, FR, DE, ES & NL

Big Data and Social Media Analytics Book Review:

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

Cognitive Social Mining Applications in Data Analytics and Forensics
Author: Haldorai, Anandakumar,Ramu, Arulmurugan
Publsiher: IGI Global
Total Pages: 326
Release: 2018-12-14
ISBN 10: 1522575235
ISBN 13: 9781522575238
Language: EN, FR, DE, ES & NL

Cognitive Social Mining Applications in Data Analytics and Forensics Book Review:

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.

On the Design Development and Use of the Social Data Analytics Tool SODATO

On the Design  Development and Use of the Social Data Analytics Tool  SODATO
Author: Abid Hussain
Publsiher: Unknown
Total Pages: 329
Release: 2016
ISBN 10: 9788793339873
ISBN 13: 8793339879
Language: EN, FR, DE, ES & NL

On the Design Development and Use of the Social Data Analytics Tool SODATO Book Review:

Python Social Media Analytics

Python Social Media Analytics
Author: Siddhartha Chatterjee,Michal Krystyanczuk
Publsiher: Packt Publishing Ltd
Total Pages: 312
Release: 2017-07-28
ISBN 10: 1787126757
ISBN 13: 9781787126756
Language: EN, FR, DE, ES & NL

Python Social Media Analytics Book Review:

Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more Analyze and extract actionable insights from your social data using various Python tools A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What You Will Learn Understand the basics of social media mining Use PyMongo to clean, store, and access data in MongoDB Understand user reactions and emotion detection on Facebook Perform Twitter sentiment analysis and entity recognition using Python Analyze video and campaign performance on YouTube Mine popular trends on GitHub and predict the next big technology Extract conversational topics on public internet forums Analyze user interests on Pinterest Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.

Social Network Analytics for Contemporary Business Organizations

Social Network Analytics for Contemporary Business Organizations
Author: Bansal, Himani,Shrivastava, Gulshan,Nguyen, Gia Nhu,Stanciu, Loredana-Mihaela
Publsiher: IGI Global
Total Pages: 321
Release: 2018-03-23
ISBN 10: 1522550984
ISBN 13: 9781522550983
Language: EN, FR, DE, ES & NL

Social Network Analytics for Contemporary Business Organizations Book Review:

Social technology is quickly becoming a vital tool in our personal, educational, and professional lives. Its use must be further examined in order to determine the role of social media technology in organizational settings to promote business development and growth. Social Network Analytics for Contemporary Business Organizations is a critical scholarly resource that analyzes the application of social media in business applications. Featuring coverage on a broad range of topics, such as business management, dynamic networks, and online interaction, this book is geared towards professionals, researchers, academics, students, managers, and practitioners actively involved in the business industry.

The Behavioral and Social Sciences

The Behavioral and Social Sciences
Author: National Research Council,Division of Behavioral and Social Sciences and Education,Commission on Behavioral and Social Sciences and Education,Committee on Basic Research in the Behavioral and Social Sciences
Publsiher: National Academies Press
Total Pages: 304
Release: 1988-02-01
ISBN 10: 0309037492
ISBN 13: 9780309037495
Language: EN, FR, DE, ES & NL

The Behavioral and Social Sciences Book Review:

This volume explores the scientific frontiers and leading edges of research across the fields of anthropology, economics, political science, psychology, sociology, history, business, education, geography, law, and psychiatry, as well as the newer, more specialized areas of artificial intelligence, child development, cognitive science, communications, demography, linguistics, and management and decision science. It includes recommendations concerning new resources, facilities, and programs that may be needed over the next several years to ensure rapid progress and provide a high level of returns to basic research.