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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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Ravindran, Sharan Kumar (Autor), Garg, Vikram (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2015.
Colección:Community experience distilled.
Temas:
Acceso en línea:Texto completo

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 
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. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Data mining. 
650 0 |a R (Computer program language) 
650 0 |a Social media. 
650 6 |a Exploration de données (Informatique) 
650 6 |a R (Langage de programmation) 
650 6 |a Médias sociaux. 
650 7 |a social media.  |2 aat 
650 7 |a COMPUTERS  |x General.  |2 bisacsh 
650 7 |a Data mining.  |2 fast  |0 (OCoLC)fst00887946 
650 7 |a R (Computer program language)  |2 fast  |0 (OCoLC)fst01086207 
650 7 |a Social media.  |2 fast  |0 (OCoLC)fst01741098 
700 1 |a Garg, Vikram,  |e author. 
776 |z 1-78439-631-1 
830 0 |a Community experience distilled. 
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