Social Data Analytics

Produk Detail:
  • Author : Krish Krishnan
  • Publisher : Newnes
  • Pages : 158 pages
  • ISBN : 0123977800
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Social Data Analytics

Download or Read online Social Data Analytics full in PDF, ePub and kindle. this book written by Krish Krishnan and published by Newnes which was released on 10 November 2014 with total page 158 pages. We cannot guarantee that Social Data Analytics book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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 Data Analytics

Social Data Analytics
  • Author : Krish Krishnan,Shawn P. Rogers
  • Publisher : Newnes
  • Release : 10 November 2014
GET THIS BOOK Social Data Analytics

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

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
  • Publisher : Springer
  • Release : 01 February 2018
GET THIS BOOK Mobility Analytics for Spatio Temporal and Social Data

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

Data Science and Social Research II

Data Science and Social Research II
  • Author : Paolo Mariani,Mariangela Zenga
  • Publisher : Springer
  • Release : 26 November 2020
GET THIS BOOK Data Science and Social Research II

The peer-reviewed contributions gathered in this book address methods, software and applications of statistics and data science in the social sciences. The data revolution in social science research has not only produced new business models, but has also provided policymakers with better decision-making support tools. In this volume, statisticians, computer scientists and experts on social research discuss the opportunities and challenges of the social data revolution in order to pave the way for addressing new research problems. The respective contributions

Data Science and Social Research

Data Science and Social Research
  • Author : N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino
  • Publisher : Springer
  • Release : 17 November 2017
GET THIS BOOK Data Science and Social Research

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

Python Social Media Analytics

Python Social Media Analytics
  • Author : Siddhartha Chatterjee,Michal Krystyanczuk
  • Publisher : Packt Publishing Ltd
  • Release : 28 July 2017
GET THIS BOOK Python Social Media Analytics

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

Learning Social Media Analytics with R

Learning Social Media Analytics with R
  • Author : Raghav Bali,Dipanjan Sarkar,Tushar Sharma
  • Publisher : Packt Publishing Ltd
  • Release : 26 May 2017
GET THIS BOOK Learning Social Media Analytics with R

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

Big Data and Social Science

Big Data and Social Science
  • Author : Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane
  • Publisher : CRC Press
  • Release : 15 September 2016
GET THIS BOOK Big Data and Social Science

Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of

Challenges and Applications of Data Analytics in Social Perspectives

Challenges and Applications of Data Analytics in Social Perspectives
  • Author : Sathiyamoorthi, V.,Elci, Atilla
  • Publisher : IGI Global
  • Release : 04 December 2020
GET THIS BOOK Challenges and Applications of Data Analytics in Social Perspectives

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

Learning Social Media Analytics with R

Learning Social Media Analytics with R
  • Author : Raghav Bali,Dipanjan Sarkar,Tushar Sharma
  • Publisher : Unknown
  • Release : 26 May 2017
GET THIS BOOK Learning Social Media Analytics with R

Tap into the realm of social media and unleash the power of analytics for data-driven insights using RAbout 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

Social Network Data Analytics

Social Network Data Analytics
  • Author : Charu C. Aggarwal
  • Publisher : Springer Science & Business Media
  • Release : 18 March 2011
GET THIS BOOK Social Network Data Analytics

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

High Performance Big Data Analytics

High Performance Big Data Analytics
  • Author : Pethuru Raj,Anupama Raman,Dhivya Nagaraj,Siddhartha Duggirala
  • Publisher : Springer
  • Release : 16 October 2015
GET THIS BOOK High Performance Big Data Analytics

This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics