Stock photo: cover may vary
Mining the Social Web : Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More Paperback - 2019
by Russell, Matthew A., Klassen, Mikhail
- Used
A$11.91
Free Delivery within USA
Standard delivery: 4 to 8 days
More delivery options
Standard delivery: 4 to 8 days
Details
- Title Mining the Social Web : Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More
- Author Russell, Matthew A., Klassen, Mikhail
- Binding Paperback
- Condition Used - Good
- Pages 426
- Volumes 1
- Language ENG
- Publisher O'Reilly Media, Incorporated
- Publication date 2019-02-12
- Features Bibliography, Index
- Bookseller's Inventory # 41631587-75
- ISBN 9781491985045 / 1491985046
- Weight 1.5 lbs (0.68 kg)
- Dimensions 9.1 x 7 x 0.8 in (23.11 x 17.78 x 2.03 cm)
- Category Computer - Internet
- Library of Congress subjects Data mining, Online social networks
- Dewey Decimal Code 006.312
- Quantity available 2
About Better World Books Indiana, United States
Biblio member since 2005
Better World Books is a for-profit, socially conscious business and a global online bookseller that collects and sells new and used books online, matching each purchase with a book donation. Each sale generates funds for literacy and education initiatives in the U.S., the UK, and around the world. Since its launch in 2003, Better World Books has raised over $35 million for libraries and literacy, donated over 38 million books, and reused or recycled more than 475 million books.
Reader reviews for Mining the Social Web : Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
