We are living in a digital era in which most of our daily activities take place online. This has created a big data phenomenon that has been subject to scientific research with increasingly available tools and processing power. As a result, a growing number of social science scholars are using computational methods for analyzing social behavior. To further the area, these evolving methods must be made known to sociological research scholars.

Opportunities and Challenges for Computational Social Science Methods focuses on the implementation of social science methods and the opportunities and challenges of these methods. This book sheds light on the infrastructure that should be built to gain required skillsets, the tools used in computational social sciences, and the methods developed and applied into computational social sciences. Covering topics like computational communication, ecological cognition, and natural language processing, this book is an essential resource for researchers, data scientists, scholars, students, professors, sociologists, and academicians.

Coverage:
The many academic areas covered in this publication include, but are not limited to:
•Big Data
•Computational Communication
•Digital World
•Ecological Cognition
•Ethnography
•Machine Learning
•Microeconomics
•Natural Language Processing
•Opinion Mining
•Semantic Saturation
•Social Network Analysis
•Sociopolitical Research