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E-raamat: Mining Social Media

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  • Formaat: EPUB+DRM
  • Ilmumisaeg: 10-Dec-2019
  • Kirjastus: No Starch Press,US
  • Keel: eng
  • ISBN-13: 9781593279172
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Mining Social MediaSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 10-Dec-2019
  • Kirjastus: No Starch Press,US
  • Keel: eng
  • ISBN-13: 9781593279172
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A Buzzfeeed News senior reporter explains how to get, process and analyze data from the social web in meaningful ways with the Python programming language. Original.

BuzzFeed News Senior Reporter Lam Thuy Vo explains how to get, process, and analyze data from the social web in meaningful ways with the Python programming language.

Mining Social Media will show you the kind of data that can be mined on the social web, the insights that can be gained from it, and the limitations of its scope. You'll learn how to find out what kind of data is available on popular social media juggernauts like Facebook and Twitter and how to recognize the value of what is measured.

Practical exercises interweave with conceptual lessons that cover ways to use Python to extract data from social media sources, analyze it, and make sense of it visually. You'll learn how to write a script that taps into an API, how to scrape data from websites, and even how to analyze data from an automated Twitter bot.

Arvustused

"If you want to know a little bit about Data Science while learning Python along the way, Mining Social Media is a must read . . . It's a fun and hands on approach to the topic, and I'd love to have read this when I was starting coding!" Gonçalo Palma, @GonPalma

"Excellently written, with complex topics made easy to understand, and has a welcoming style of prose." Ryan K. Louie, MD, PhD, @ryanlouie

"If you haven't read Lam's book, Mining Social Media, trust us you're gonna dig it." Craig Newmark Graduate School of Journalism, @newmarkjschool

Muu info

Buzzfeeed News Senior Reporter Lam Thuy Vo explains how to get, process, and analyze data from the social web in meaningful ways with the Python programming language.
Acknowledgments xv
Introduction xvii
What Is Data Analysis? xviii
Who Is This Book For? xviii
Conventions Used in This Book xviii
What This Book Covers xix
Part I Data Mining xix
Part II Data Analysis xx
Downloading and Installing Python xx
Installing on Windows xxi
Installing on macOS xxi
Getting Help When You're Stuck xxi
Summary xxiv
PART I DATA MINING
1(98)
1 The Programming Languages You'll Need To Know
3(24)
Frontend Languages
4(10)
How HTML Works
4(2)
How CSS Works
6(6)
How JavaScript Works
12(2)
Backend Languages
14(11)
Using Python
14(1)
Getting Started with Python
14(2)
Working with Numbers
16(1)
Working with Strings
17(1)
Storing Values in Variables
17(2)
Storing Multiple Values in Lists
19(1)
Working with Functions
20(1)
Creating Your Own Functions
21(1)
Using Loops
22(1)
Using Conditionals
23(2)
Summary
25(2)
2 Where to Get your Data
27(16)
What Is an API?
28(1)
Using an API to Get Data
28(9)
Getting a YouTube API Key
31(1)
Retrieving JSON Objects Using Your Credentials
31(6)
Answering a Research Question Using Data
37(4)
Refining the Data That Your API Returns
41(1)
Summary
41(2)
3 Getting Data With Code
43(20)
Writing Your First Script
44(1)
Running a Script
44(2)
Planning Out a Script
46(1)
Libraries and pip
46(2)
Creating a URL-based API Call
48(1)
Storing Data in a Spreadsheet
49(4)
Converting JSON into a Dictionary
51(1)
Going Back to the Script
51(2)
Running the Finished Script
53(2)
Dealing with API Pagination
55(2)
Templates: How to Make Your Code Reusable
57(4)
Storing Values That Change in Variables
57(1)
Storing Code in a Reusable Function
58(3)
Summary
61(2)
4 Scraping Your Own Facebook Data
63(14)
Your Data Sources
64(1)
Downloading Your Facebook Data
64(2)
Reviewing the Data and Inspecting the Code
66(4)
Structuring Information as Data
67(1)
Scraping Automatically
68(2)
Analyzing HTML Code to Recognize Patterns
70(2)
Grabbing the Elements You Need
70(1)
Extracting the Contents
71(1)
Writing Data into a Spreadsheet
72(3)
Building Your Rows List
72(2)
Writing to Your csv File
74(1)
Running the Script
75(1)
Summary
76(1)
5 Scraping A Live Site
77(22)
Messy Data
78(5)
Ethical Considerations for Data Scraping
80(1)
The Robots Exclusion Protocol
80(2)
The Terms of Service
82(1)
Technical Considerations for Data Scraping
82(1)
Reasons for Scraping Data
82(1)
Scraping from a Live Website
83(15)
Analyzing the Page's Contents
84(4)
Storing the Page Content in Variables
88(4)
Making the Script Reusable
92(2)
Practicing Polite Scraping
94(4)
Summary
98(1)
PART II DATA ANALYSIS
99(82)
6 Introduction To Data Analysis
101(22)
The Process of Data Analysis
102(1)
Bot Spotting
103(1)
Getting Started with Google Sheets
104(2)
Modifying and Formatting the Data
106(4)
Aggregating the Data
110(4)
Using Pivot Tables to Summarize Data
110(2)
Using Formulas to Do Math
112(2)
Sorting and Filtering the Data
114(3)
Merging Data Sets
117(4)
Other Ways to Use Google Sheets
121(1)
Summary
122(1)
7 Visualizing Your Data
123(12)
Understanding Our Bot Through Charts
124(7)
Choosing a Chart
124(4)
Specifying a Time Period
128(1)
Making a Chart
128(3)
Conditional Formatting
131(2)
Single-Color Formatting
131(1)
Color Scale Formatting
132(1)
Summary
133(2)
8 Advanced Tools For Data Analysis
135(16)
Using Jupyter Notebook
136(6)
Setting Up a Virtual Environment
136(2)
Organizing the Notebook
138(1)
Installing Jupyter and Creating Your First Notebook
139(1)
Working with Cells
140(2)
What Is pandas?
142(7)
Working with Series and Data Frames
143(2)
Reading and Exploring Large Data Files
145(1)
Looking at the Data
146(2)
Viewing Specific Columns and Rows
148(1)
Summary
149(2)
9 Finding Trends In Reddit Data
151(12)
Clarifying Our Research Objective
152(1)
Outlining a Method
152(1)
Narrowing the Data's Scope
153(4)
Selecting Data from Specific Columns
153(1)
Handling Null Values
154(2)
Classifying the Data
156(1)
Summarizing the Data
157(5)
Sorting the Data
158(2)
Describing the Data
160(2)
Summary
162(1)
10 Measuring The Twitter Activity Of Political Actors
163(14)
Getting Started
164(4)
Setting Up Your Environment
164(1)
Loading the Data into Your Notebook
165(3)
Lambdas
168(1)
Filtering the Data Set
169(1)
Formatting the Data as datetimes
170(2)
Resampling the Data
172(3)
Plotting the Data
175(1)
Summary
176(1)
11 Where To Go From Here
177(4)
Coding Styles
178(1)
Statistical Analysis
179(1)
Other Kinds of Analyses
179(1)
Conclusion
180(1)
Index 181
Lam Thuy Vo is a senior reporter at BuzzFeed News where she focuses on the intersection of technology, society, and social media data. She has reported for The Wall Street Journal, Al Jazeera America, and NPR's Planet Money, telling economic stories across the US and throughout Asia. Vo has also spent over a decade as an educator, training newsrooms and developing courses for the Craig Newmark Graduate School of Journalism at CUNY.
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