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Mastering Social Media Mining with R

You're reading from  Mastering Social Media Mining with R

Product type Book
Published in Sep 2015
Publisher
ISBN-13 9781784396312
Pages 248 pages
Edition 1st Edition
Languages
Concepts

Table of Contents (13) Chapters

Mastering Social Media Mining with R
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Fundamentals of Mining 2. Mining Opinions, Exploring Trends, and More with Twitter 3. Find Friends on Facebook 4. Finding Popular Photos on Instagram 5. Let's Build Software with GitHub 6. More Social Media Websites Index

Measuring CTR performance for a page


The performance of a page can be measured by the user activity in the page and the user's interaction in the posts published in the page. Let's measure the performance for a page. When we say measuring the performance, it is by means of counting the user interaction through likes, comments, and shares.

In order to come up with a trend, we will need the timestamp data. Then, we need to consolidate the data on a monthly basis so that we can draw the time-series performance chart.

First, we need to convert the Facebook date format into R-supported date format. The following code is a function to convert the date format. We need to pass the date timestamp data to this function. The function will return the same date timestamp in R-supported format so that we can perform date operation. The code is as follows:

format.facebook.date<- function(datestring) {
date<- as.POSIXct(datestring, format = "%Y-%m-%dT%H:%M:%S+0000", tz = "GMT")
}

Then, we need to aggregate...

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