An Introduction To Social Analytics
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| Author | : Charu C. Aggarwal |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 508 |
| Release | : 2011-03-18 |
| Genre | : Computers |
| ISBN | : 1441984623 |
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.
| Author | : Kosuke Imai |
| Publisher | : Princeton University Press |
| Total Pages | : 464 |
| Release | : 2021-03-16 |
| Genre | : Political Science |
| ISBN | : 0691191093 |
"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--
| Author | : Stephen Sinclair |
| Publisher | : Policy Press |
| Total Pages | : 188 |
| Release | : 2016-02-24 |
| Genre | : Political Science |
| ISBN | : 1447313917 |
In a political climate that is ever more focused on austerity and efficiency, it is crucial that those who advocate for, support, and implement social policy know how to analyze it and understand its effects, successes, and failures. This volume offers a clear introduction to social policy analysis, starting from the question of why social policy analysis is worthwhile, then moving on to how it can be used to consider approaches to a wide range of social welfare issues.
| Author | : Elena Llaudet |
| Publisher | : Princeton University Press |
| Total Pages | : 256 |
| Release | : 2022-11-29 |
| Genre | : Computers |
| ISBN | : 0691199434 |
"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--
| Author | : Reza Zafarani |
| Publisher | : Cambridge University Press |
| Total Pages | : 337 |
| Release | : 2014-04-28 |
| Genre | : Computers |
| ISBN | : 1107018854 |
Integrates social media, social network analysis, and data mining to provide an understanding of the potentials of social media mining.
| Author | : João Moreira |
| Publisher | : John Wiley & Sons |
| Total Pages | : 352 |
| Release | : 2018-07-18 |
| Genre | : Mathematics |
| ISBN | : 1119296242 |
A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.
| Author | : Suraj Bandyopadhyay |
| Publisher | : SAGE Publications |
| Total Pages | : 250 |
| Release | : 2010-06-02 |
| Genre | : Social Science |
| ISBN | : 1483305376 |
Written by a sociologist, a graph theorist, and a statistician, this title provides social network analysts and students with a solid statistical foundation from which to analyze network data. Clearly demonstrates how graph-theoretic and statistical techniques can be employed to study some important parameters of global social networks. The authors uses real life village-level social networks to illustrate the practicalities, potentials, and constraints of social network analysis ("SNA"). They also offer relevant sampling and inferential aspects of the techniques while dealing with potentially large networks. Intended Audience This supplemental text is ideal for a variety of graduate and doctoral level courses in social network analysis in the social, behavioral, and health sciences
| Author | : Todd Kelsey |
| Publisher | : Apress |
| Total Pages | : 155 |
| Release | : 2017-06-21 |
| Genre | : Computers |
| ISBN | : 1484228545 |
Easily understand the most important tools and skills in social media marketing. You'll be exposed to Facebook pages and ads, work with Twitter and LinkedIn, save time with Hootsuite, and learn social media monitoring. If you are completely new to social media marketing and you want to learn the basics, this guide will introduce you to the content quickly. Introduction to Social Media Marketing has a particular focus on ROI (return on investment), to help you think critically about the value social media could bring a business or organization. You'll explore the question of whether or not it's worth it to invest time and money in each social media channel. What You’ll Learn Understand basic functions for most social media tools, including how to get up and running See the benefits of social media tools and which one you should use for specific purposes Calculate the real ROI expected from using specific tools Utilize social media monitoring and analytics Who This Book Is For Those who need to get up to speed on a broad range of social media tools and techniques for business or personal use. This book is also suitable as a student reference.
| Author | : Melinda C. Mills |
| Publisher | : MIT Press |
| Total Pages | : 433 |
| Release | : 2020-02-18 |
| Genre | : Science |
| ISBN | : 0262357445 |
A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics. Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics. This book offers the first comprehensive introduction to modern applied statistical genetic data analysis that covers theory, data preparation, and analysis of molecular genetic data, with hands-on computer exercises. It is accessible to students and researchers in any empirically oriented medical, biological, or social science discipline; a background in molecular biology or genetics is not required. The book first provides foundations for statistical genetic data analysis, including a survey of fundamental concepts, primers on statistics and human evolution, and an introduction to polygenic scores. It then covers the practicalities of working with genetic data, discussing such topics as analytical challenges and data management. Finally, the book presents applications and advanced topics, including polygenic score and gene-environment interaction applications, Mendelian Randomization and instrumental variables, and ethical issues. The software and data used in the book are freely available and can be found on the book's website.
| Author | : Kali H. Trzesniewski |
| Publisher | : American Psychological Association (APA) |
| Total Pages | : 264 |
| Release | : 2011 |
| Genre | : Psychology |
| ISBN | : |
This wide-ranging yet practical book shows how the analysis of secondary data can provide unique opportunities for advancing psychological science. --Book Jacket.
