This book is intended for traders and investors that want to gain an edge on the competition by incorporating social media and search analytics into their study of the market. The book assumes you are new to data manipulation in Python, one of the most popular languages for data manipulation.
Intro to Social Data focuses on the following platforms:
1) Google Trends - provides historical Google search volume data
2) StockTwits - a social network for traders and investors
3) Twitter - one of the original social networks and still very valuable
4) Estimize - crowd-sourced structured financial predictions
The book contains a focused introduction to get you up and running as quick as possible (relatively, speaking, learning new things is always a challenge) and also provides tools and examples written in Python. Additionally, the book guides you through the Python analytics stack which includes NumPy, Pandas, PyPlot and more. Also included are two examples written in R, another popular open-source language for data analysis.
A large breadth of topics is covered, providing you with the seeds of knowledge to access Social Data sources and begin to explore how they can be incorporated into your trading. You will learn how to build the interfaces between your computer and these novel social datasets. Examples include learning how to extract historical search volumes and programmatically read the StockTwits and Twitter streams.
I have tried to write for traders who want the highest level of abstraction. In other words, this is a book written for traders by a trader: you will learn efficiently because your time is a non-renewable resource. That being said, to fully gain from the knowledge this book has to offer you must be interested in the infinite possibilities that arise from including Social Data in your study of the market.
This book will not provide mindless cookie-cutter trading strategies. You must be willing to learn new topics, to download a myriad of open-source software to your computer and possibly learn a bit about system administration. While I assume very little programming knowledge, it would be good if you had encountered things like loops, functions, variables, and types prior to reading Intro to Social Data.
Intro to Social Data focuses on the following platforms:
1) Google Trends - provides historical Google search volume data
2) StockTwits - a social network for traders and investors
3) Twitter - one of the original social networks and still very valuable
4) Estimize - crowd-sourced structured financial predictions
The book contains a focused introduction to get you up and running as quick as possible (relatively, speaking, learning new things is always a challenge) and also provides tools and examples written in Python. Additionally, the book guides you through the Python analytics stack which includes NumPy, Pandas, PyPlot and more. Also included are two examples written in R, another popular open-source language for data analysis.
A large breadth of topics is covered, providing you with the seeds of knowledge to access Social Data sources and begin to explore how they can be incorporated into your trading. You will learn how to build the interfaces between your computer and these novel social datasets. Examples include learning how to extract historical search volumes and programmatically read the StockTwits and Twitter streams.
I have tried to write for traders who want the highest level of abstraction. In other words, this is a book written for traders by a trader: you will learn efficiently because your time is a non-renewable resource. That being said, to fully gain from the knowledge this book has to offer you must be interested in the infinite possibilities that arise from including Social Data in your study of the market.
This book will not provide mindless cookie-cutter trading strategies. You must be willing to learn new topics, to download a myriad of open-source software to your computer and possibly learn a bit about system administration. While I assume very little programming knowledge, it would be good if you had encountered things like loops, functions, variables, and types prior to reading Intro to Social Data.
