Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R /
Chapter 3: Find Friends on Facebook ; Creating an app on the Facebook platform; Rfacebook package installation and authentication; Installation; A closer look at how the package works; A basic analysis of your network; Network analysis and visualization; Social network analysis; Degree; Betweenness;...
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Birmingham, UK :
Packt Publishing,
2015.
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| Series: | Community experience distilled.
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| Subjects: | |
| Online Access: | CONNECT |
MARC
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| 100 | 1 | |a Ravindran, Sharan Kumar, |e author. | |
| 245 | 1 | 0 | |a Mastering social media mining with R : |b extract valuable data from social media sites and make better business decisions using R / |c Sharan Kumar Ravindran, Vikram Garg. |
| 246 | 3 | 0 | |a Extract valuable data from social media sites and make better business decisions using R |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2015. | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a data file |2 rda | ||
| 490 | 1 | |a Community experience distilled | |
| 588 | 0 | |a Online resource; title from cover page (Safari, viewed October 12, 2015). | |
| 500 | |a Includes index. | ||
| 505 | 0 | |a Cover ; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Fundamentals of Mining; Social media and its importance; Various social media platforms; Social media mining; Challenges for social media mining; Social media mining techniques; Graph mining; Text mining; The generic process of social media mining; Getting authentication from the social website -- OAuth 2.0; Differences between OAuth and OAuth 2.0; Data visualization R packages; The simple word cloud; Sentiment analysis Wordcloud; Preprocessing and cleaning in R | |
| 505 | 8 | |a Data modeling -- the application of mining algorithmsOpinion mining (sentiment analysis); Steps for sentiment analysis; Community detection via clustering ; Result visualization; An example of social media mining; Summary; Chapter 2: Mining Opinions, Exploring Trends, and More with Twitter ; Twitter and its importance; Understanding Twitter's APIs; Twitter vocabulary; Creating a Twitter API connection; Creating a new app; Finding trending topics; Searching tweets; Twitter sentiment analysis; Collecting tweets as a corpus; Cleaning the corpus; Estimating sentiment (A); Estimating sentiment (B) | |
| 505 | 8 | |a The order of stories on a user's home pageRecommendations to friends; Reading the output; Other business cases; Summary; Chapter 4: Finding Popular Photos on Instagram ; Creating an app on the Instagram platform; Installation and authentication of the instaR package; Accessing data from R; Searching public media for a specific hashtag; Searching public media from a specific location; Extracting public media of a user; Extracting user profile; Getting followers; Who does the user follow?; Getting comments; Number of times hashtag is used; Building a dataset; User profile; User media | |
| 505 | 8 | |a Travel-related mediaWho do they follow?; Popular personalities; Who has the most followers?; Who follows more people?; Who shared most media?; Overall top users; Most viral media; Finding the most popular destination; Locations; Locations with most likes; Locations most talked about; What are people saying about these locations?; Most repeating locations; Clustering the pictures; Recommendations to the users; How to do it; Top three recommendations; Improvements to the recommendation system; Business case; Reference; Summary; Chapter 5: Let's Build Software with GitHub | |
| 520 | |a Chapter 3: Find Friends on Facebook ; Creating an app on the Facebook platform; Rfacebook package installation and authentication; Installation; A closer look at how the package works; A basic analysis of your network; Network analysis and visualization; Social network analysis; Degree; Betweenness; Closeness; Cluster; Communities; Getting Facebook page data; Trending topics; Trend analysis; Influencers; Based on a single post; Based on multiple posts; Measuring CTR performance for a page; Spam detection; Implementing a spam detection algorithm | ||
| 546 | |a English. | ||
| 500 | |a EBSCO eBook Academic Comprehensive Collection North America |5 TMurS | ||
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a R (Computer program language) | |
| 650 | 0 | |a Social media. | |
| 700 | 1 | |a Garg, Vikram, |e author. | |
| 730 | 0 | |a WORLDSHARE SUB RECORDS | |
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| 830 | 0 | |a Community experience distilled. | |
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