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Main Library
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Folly Beach Library
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Mining social media : finding stories in Internet data / by Lam Thuy Vo.
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- Author(s): Vo, Lam Thuy, author
- Language:
English- Publication Information:
San Francisco : No Starch Press, Inc., [2020]- Publication Date:
2020- Physical Description:
xxiv, 184 pages : illustrations ; 24 cm- Publication Type:
Book- Document Type:
Non-fiction- Subject Terms:
- Availability: 2 Holdings
- Language:
- Additional Information
- Abstract: Summary: "A guide to mining and analyzing data from social media websites. Combines both practical exercises and conceptual lessons on topics like writing a script to tap into an API and making sense of emoji usage in collected data"-- provided by publisher.
- Abstract: Summary: "Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language. Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: Write Python scripts and use APIs to gather data from the social web; Download data archives and dig through them for insights; Inspect HTML downloaded from websites for useful content; Format, aggregate, sort, and filter your collected data using Google Sheets; Create data visualizations to illustrate your discoveries; Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library; Apply what you've learned to research topics on your own. Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories."
- Content Notes: Part I: Data mining. The programming languages you'll need to know -- Where to get your data -- Getting data with code -- Scraping your own Facebook data -- Scraping a live site -- Part II: Data analysis. Introduction to data analysis -- Visualizing your data -- Advanced tools for data analysis -- Finding trends in Reddit data -- Measuring the Twitter activity of political actors -- Where to go from here.
- Notes: Includes index.
Includes bibliographical references and index.
1 5 - ISBN: 9781593279165
1593279167 - Accession Number: 2019030568
- Accession Number: 1112138651
- Accession Number: ccp.1087653
- Abstract:
Holdings
- Branch: Main Library - Non-Fiction Area
- Call Number: 302.231 VO
- Branch: St. Andrews Library - Non-Fiction Area
- Call Number: 302.231 VO
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