Data Mining for the Social Sciences - An Introduction

"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tunetheir advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.

Product details

• Authors: Paul Attewell, Paul A. Attewell, Paul A. Monaghan Attewell, David Monaghan, Monaghan David
• Publisher: University Of California Press
• Languages: English
• Product format: Hardback
• Release: 28.05.2015, delayed
• EAN: 9780520280977
• ISBN: 978-0-520-28097-7
• No. of pages: 264
• Subjects: Social sciences, law, business > Political science > Political science and political education; Data Mining, SOCIAL SCIENCE / Research, SOCIAL SCIENCE / Statistics, Social research & statistics, Social research and statistics, COMPUTERS / Data Science / Data Analytics