Developers working in Data Science, Software Engineering, and the Social Sciences will be able to put their knowledge to work with this practical guide to Network Analysis. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time.
Key Features
- Network Timeseries Analysis and Evolution
- Networks and Unsupervised Machine Learning
- Networks and Supervised Machine Learning
Book Description
This book will be explaining topics from social science and mathematics in a way that is hands on and practical. It will be taught in a way so that readers will be inspired to use it to understand complex relationships that exist around them in their work and personal lives. Data Scientists, Software Engineers, and NLP Engineers will be able to put their knowledge to work with this practical guide to Network Analysis. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time. Complete with step-by-step explanations of essential concepts, practical examples and self-assessment questions, you will begin by learning the basics of NLP, Network Science, and Social Network Analysis and then will learn to programmatically build and analyze networks in order to understand the world around you. We will learn the science, where data comes from, how to get it, how to interact with it, and how to pull insights from it. However, this will be a hands-on book, not a math book, but you will be provided sources to look to for more specific technical and mathematical details.
By the end of the book you will be able to identify network data and use it to extract unconventional insights to make sense of the complex world that exists around you.
What you will learn
- Get familiar with NLP, Network Science, and Social Network Analysis.
- Get familiar with the tech stack used to apply NLP, Network Science, and Social Network Analysis.
- Learn how to get and prepare NLP and network data
- Learn how to extract insights from NLP and network data
- Understand how to think up your own NLP and network projects
- Understand how to authenticate and scrape tweets, connection, and the stream
Who This Book Is For
Data Scientists, NLP Engineers, Software Engineers, Social Scientists, and Students with introductory software skills, some Data Science, some statistics skills will find this book useful. Having python programming intermediate skills is necessary to get the best from this book.
Table of Contents
- Natural Language Processing (NLP)
- Network Science and Social Network Analysis
- Tools for NLP
- Tools for Network Analysis and Visualization
- The Power of NLP and Networks Combined
- Even Easier Scraping!
- Graph Construction and Cleaning
- Network Construction
- Egocentric Network Analysis
- Visualizing Networks
- Network Destruction
- Using Results for Further Investigation
- Test your knowledge
