Tap into the realm of social media and unleash the power of
analytics for data-driven insights using R About This Book * A
practical guide written to help leverage the power of the R
eco-system to extract, process, analyze, visualize and model social
media data * Learn about data access, retrieval, cleaning, and
curation methods for data originating from various social media
platforms. * Visualize and analyze data from social media platforms
to understand and model complex relationships using various
concepts and techniques such as Sentiment Analysis, Topic Modeling,
Text Summarization, Recommendation Systems, Social Network
Analysis, Classification, and Clustering. Who This Book Is For It
is targeted at IT professionals, Data Scientists, Analysts,
Developers, Machine Learning Enthusiasts, social media marketers
and anyone with a keen interest in data, analytics, and generating
insights from social data. Some background experience in R would be
helpful, but not necessary, since this book is written keeping in
mind, that readers can have varying levels of expertise. What You
Will Learn * Learn how to tap into data from diverse social media
platforms using the R ecosystem * Use social media data to
formulate and solve real-world problems * Analyze user social
networks and communities using concepts from graph theory and
network analysis * Learn to detect opinion and sentiment, extract
themes, topics, and trends from unstructured noisy text data from
diverse social media channels * Understand the art of representing
actionable insights with effective visualizations * Analyze data
from major social media channels such as Twitter, Facebook, Flickr,
Foursquare, Github, StackExchange, and so on * Learn to leverage
popular R packages such as ggplot2, topicmodels, caret, e1071, tm,
wordcloud, twittR, Rfacebook, dplyr, reshape2, and many more In
Detail The Internet has truly become humongous, especially with the
rise of various forms of social media in the last decade, which
give users a platform to express themselves and also communicate
and collaborate with each other. This book will help the reader to
understand the current social media landscape and to learn how
analytics can be leveraged to derive insights from it. This data
can be analyzed to gain valuable insights into the behavior and
engagement of users, organizations, businesses, and brands. It will
help readers frame business problems and solve them using social
data. The book will also cover several practical real-world use
cases on social media using R and its advanced packages to utilize
data science methodologies such as sentiment analysis, topic
modeling, text summarization, recommendation systems, social
network analysis, classification, and clustering. This will enable
readers to learn different hands-on approaches to obtain data from
diverse social media sources such as Twitter and Facebook. It will
also show readers how to establish detailed workflows to process,
visualize, and analyze data to transform social data into
actionable insights. Style and approach This book follows a
step-by-step approach with detailed strategies for understanding,
extracting, analyzing, visualizing, and modeling data from several
major social network platforms such as Facebook, Twitter,
Foursquare, Flickr, Github, and StackExchange. The chapters cover
several real-world use cases and leverage data science, machine
learning, network analysis, and graph theory concepts along with
the R ecosystem, including popular packages such as ggplot2,
caret,dplyr, topicmodels, tm, and so on.
General
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