Mining social media : finding stories in internet data

Mining social media finding stories in internet data

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 y...

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Detalles Bibliográficos
Otros Autores: Vo, Lam Thuy, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: San Francisco, California : No Starch Press [2020]
Edición:1st edition
Materias:
Data mining.
Web usage mining.
Social media > Use studies.
Social sciences > Research > Methodology.
Internet research.
Quantitative research.
Qualitative research.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630846706719
Tabla de Contenidos:
  • Intro
  • Title Page
  • Copyright Page
  • Dedication
  • About the Author
  • BRIEF CONTENTS
  • CONTENTS IN DETAIL
  • ACKNOWLEDGMENTS
  • INTRODUCTION
  • What Is Data Analysis?
  • Who Is This Book For?
  • Conventions Used in This Book
  • What This Book Covers
  • Downloading and Installing Python
  • Getting Help When You're Stuck
  • Summary
  • PART I: DATA MINING
  • 1 THE PROGRAMMING LANGUAGES YOU'LL NEED TO KNOW
  • Frontend Languages
  • Backend Languages
  • Summary
  • 2 WHERE TO GET YOUR DATA
  • What Is an API?
  • Using an API to Get Data
  • Answering a Research Question Using Data
  • Summary
  • 3 GETTING DATA WITH CODE
  • Writing Your First Script
  • Running a Script
  • Planning Out a Script
  • Libraries and pip
  • Creating a URL-based API Call
  • Storing Data in a Spreadsheet
  • Running the Finished Script
  • Dealing with API Pagination
  • Templates: How to Make Your Code Reusable
  • Summary
  • 4 SCRAPING YOUR OWN FACEBOOK DATA
  • Your Data Sources
  • Downloading Your Facebook Data
  • Reviewing the Data and Inspecting the Code
  • Analyzing HTML Code to Recognize Patterns
  • Writing Data into a Spreadsheet
  • Running the Script
  • Summary
  • 5 SCRAPING A LIVE SITE
  • Messy Data
  • Scraping from a Live Website
  • Summary
  • PART II: DATA ANALYSIS
  • 6 INTRODUCTION TO DATA ANALYSIS
  • The Process of Data Analysis
  • Bot Spotting
  • Getting Started with Google Sheets
  • Modifying and Formatting the Data
  • Aggregating the Data
  • Sorting and Filtering the Data
  • Merging Data Sets
  • Other Ways to Use Google Sheets
  • Summary
  • 7 VISUALIZING YOUR DATA
  • Understanding Our Bot Through Charts
  • Conditional Formatting
  • Summary
  • 8 ADVANCED TOOLS FOR DATA ANALYSIS
  • Using Jupyter Notebook
  • What Is pandas?
  • Summary
  • 9 FINDING TRENDS IN REDDIT DATA
  • Clarifying Our Research Objective
  • Outlining a Method
  • Narrowing the Data's Scope.
  • Summarizing the Data
  • Summary
  • 10 MEASURING THE TWITTER ACTIVITY OF POLITICAL ACTORS
  • Getting Started
  • Lambdas
  • Filtering the Data Set
  • Formatting the Data as datetimes
  • Resampling the Data
  • Plotting the Data
  • Summary
  • 11 WHERE TO GO FROM HERE
  • Coding Styles
  • Statistical Analysis
  • Other Kinds of Analyses
  • Conclusion
  • Index.

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