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Learning Social Media Analytics with R

Learning Social Media Analytics with R

By : Sarkar, Karthik Ganapathy, Raghav Bali, Sharma
5 (4)
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Learning Social Media Analytics with R

Learning Social Media Analytics with R

5 (4)
By: Sarkar, Karthik Ganapathy, Raghav Bali, Sharma

Overview of this book

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.
Table of Contents (10 chapters)
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9
Index

Topic modeling


In the most basic words, topic modeling is the process of finding out the hidden topics that exist in any document. We will try to explain the basic concept of topic modeling by using an analogy of a lavish buffet spread.

Suppose you go to a wedding that features a large number of items from various cuisines. You, being an absolute foodie, go to all the counters and collect a very large number of items at your table (with the obvious disapproving looks of other guests). Now one of your other friends arrives at the table and takes a look at the large number of food items at your table. He tries to guess the various cuisines on offer from the snapshot of items you have collected. He is able to do so because there is an association between the food item and the cuisine it comes from. For example, if you have various types of pasta and sea foods on your table, he could guess that a major cuisine at the buffet was Italian. This is very much similar to the thought process of exploring...

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Learning Social Media Analytics with R
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