Twitter Data Analytics

1. Front Matter

   Pages i-x

   PDF

2. Introduction

   • Shamanth Kumar, Fred Morstatter, Huan Liu

   Pages 1-3

3. Crawling Twitter Data

   • Shamanth Kumar, Fred Morstatter, Huan Liu

   Pages 5-22

4. Storing Twitter Data

   • Shamanth Kumar, Fred Morstatter, Huan Liu

   Pages 23-33

5. Analyzing Twitter Data

   • Shamanth Kumar, Fred Morstatter, Huan Liu

   Pages 35-48

6. Visualizing Twitter Data

   • Shamanth Kumar, Fred Morstatter, Huan Liu

   Pages 49-69

7. Back Matter

   Pages 71-77

   PDF

This brief provides methods for harnessing Twitter data to discover solutions to complex inquiries. The brief introduces the process of collecting data through Twitter’s APIs and offers strategies for curating large datasets. The text gives examples of Twitter data with real-world examples, the present challenges and complexities of building visual analytic tools, and the best strategies to address these issues. Examples demonstrate how powerful measures can be computed using various Twitter data sources. Due to its openness in sharing data, Twitter is a prime example of social media in which researchers can verify their hypotheses, and practitioners can mine interesting patterns and build their own applications. This brief is designed to provide researchers, practitioners, project managers, as well as graduate students with an entry point to jump start their Twitter endeavors. It also serves as a convenient reference for readers seasoned in Twitter data analysis.

• Big data
• Data mining
• Social media
• Twitter analytics
• Visual analytics

• Data Mining and Machine Learning Lab, Arizona State University, Tempe, USA

  Shamanth Kumar, Fred Morstatter, Huan Liu

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