FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
|
|
- Title Social Media Mining: An Introduction
- Author(s) Reza Zafarani, Mohammad Ali Abbasi, Huan Liu
- Publisher: Cambridge University Press (April 28, 2014)
- Hardcover/Paperback 332 pages (est.)
- eBook PDF (382 pages, 4.8 MB)
- Language: English
- ISBN-10: 1107018854
- ISBN-13: 978-1107018853
- Share This:
The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms, and tool development.
Social Media Mining integrates social media, social network analysis, and data mining to provide a convenient and coherent platform for students, practitioners, researchers, and project managers to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining.
Suitable for use in advanced undergraduate and beginning graduate courses as well as professional short courses, the text contains exercises of different degrees of difficulty that improve understanding and help apply concepts, principles, and methods in various scenarios of social media mining.
About the Authors- N/A
- Data Analysis and Data Mining
- Big Data
- Data Science
- Machine Learning
- Social Media and Social Networks
-
Mining Social Media: Finding Stories in Internet Data
This book shows you how to use Python and key data analysis tools to find the stories buried in social media. Perform advanced data analysis using Python, Jupyter Notebooks, and the Pandas library.
-
O'Reilly® Mining the Social Web, 2nd Edition (Matthew A. Russell)
This book shows you how to answer these questions like how can you tap into social data and discover who's connecting with whom, which insights are lurking just beneath the surface, and what people are talking about?
-
Social Networks with Rich Edge Semantics (Quan Zheng, et al.)
This book introduces a new mechanism for representing social networks in which pairwise relationships can be drawn from a range of realistic possibilities. For each possibility, the book shows how to model the social network using spectral embedding.
-
Twitter Data Analytics (Shamanth Kumar, et al)
This book 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.
-
Mining the Web: Discovering Knowledge from Hypertext Data
This is is the first book devoted entirely to techniques for producing knowledge from the vast body of unstructured Web data. Building on an initial survey of infrastructural issues-including Web crawling and indexing.
-
Mining of Massive Datasets (Jure Leskovec, et al)
It focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically.
-
Data Mining for the Masses (Matthew North)
This book uses simple examples, clear explanations and free, powerful, easy-to-use software to teach you the basics of data mining; techniques that can help you answer some of your toughest business questions.
:
|
|