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Twitter Data Analytics

  • Book
  • © 2014

Overview

Authors:
  1. Shamanth Kumar

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

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    You can also search for this author in PubMed   Google Scholar

  2. Fred Morstatter

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

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    You can also search for this author in PubMed   Google Scholar

  3. Huan Liu

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

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)

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Table of contents (5 chapters)

  1. Front Matter

    Pages i-x
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  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
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Keywords

About this book

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.

Authors and Affiliations

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

    Shamanth Kumar, Fred Morstatter, Huan Liu

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