Twitter is a massive social networking site tuned towards fast communication. More than 140 million active users publish over 400 million 140-character ‘Tweets’ every day. Twitter’s speed and ease of publication have made it an important communication medium for people from all walks of life. Twitter has played a prominent role in socio-political events, such as the Arab Spring and the Occupy Wall Street movement. Twitter has also been used to post damage reports and disaster preparedness information during large natural disasters, such as the Hurricane Sandy.
This book is for the reader who is interested in understanding the basics of collecting, storing, and analyzing Twitter data. The first half of this book discusses collection and storage of data. It starts by discussing how to collect Twitter data, looking at the free APIs provided by Twitter. We then goes on to discuss how to store this data in a tangible way for use in real-time applications. The second half is focused on analysis. Here, we focus on common measures and algorithms that are used to analyze social media data. We finish the analysis by discussing visual analytics, an approach which helps humans inspect the data through intuitive visualizations.
This book provides hands-on introduction to the collection and analysis of Twitter data from the perspective of a novice. No knowledge of data analysis, or social network analysis is presumed. For all the concepts discussed in this book, we will provide in-depth description of the underlying assumptions and explain via construction of examples. The reader will gain knowledge of the concepts in this book by building a crawler that collects Twitter data in real time. The reader will then learn how to analyze this data to find important time periods, users, and topics in their dataset. Finally, the reader will see how all of these concepts can be brought together to perform visual analysis and create meaningful software that uses Twitter data.
The code examples in this book are written in Java, and JavaScript. Familiarity with these languages will be useful in understanding the code, however the examples should be straightforward enough for anyone with basic programming experience. This book does assume that you know the programming concepts behind a high level language.
Twitter Data Analytics
by Shamanth Kumar, Fred Morstatter, and Huan Liu (PDF) – 89 pages and Code Examples
