Index
A
C
D
E
- English Football Club's brand page engagements
- English Football Clubs brand page engagements
- data, obtaining / Getting the data
- data, curating / Curating the data
- post counts per page, visualizing / Visualizing post counts per page
- post counts, visualizing by post type per page / Visualizing post counts by post type per page
- average likes, visualizing by post type per page / Visualizing average likes by post type per page
- average shares, visualizing by post type per page / Visualizing average shares by post type per page
- page engagement over time, visualizing / Visualizing page engagement over time
- user engagement, visualizing with page over time / Visualizing user engagement with page over time
- posts, trending by user likes per page / Trending posts by user likes per page
- posts, trending by user shares per page / Trending posts by user shares per page
- influential users, on popular page posts / Top influential users on popular page posts
- English football social network
- English Premier League (EPL) / Analyzing an English football social network
- Exchangeable Image File Format (EXIF) / Understanding more about EXIF
- Extensible Markup Language (XML) / Data processing and normalization
- Extract-Transform-Load (ETL) / Analytics workflow
F
- Facebook
- Facebook data
- Facebook Graph API
- Flickr
- Flickr, challenges
- Flickr APIs
- Flickr data
- Foursquare
- Foursquare, APIs
- Foursquare data analysis
- functions, data types
G
H
I
J
K
L
- language trends
- analyzing / Analyzing language trends
- top trending languages, visualizing / Visualizing top trending languages
- top trending languages, visualizing over time / Visualizing top trending languages over time
- languages, analyzing with issues / Analyzing languages with the most open issues
- languages, analyzing with issues over time / Analyzing languages with the most open issues over time
- languages, analyzing with repositories / Analyzing languages with the most helpful repositories
- languages, analyzing with highest popularity score / Analyzing languages with the highest popularity score
- language correlations, analyzing / Analyzing language correlations
- user trends, analyzing / Analyzing user trends
- top contributing users, visualizing / Visualizing top contributing users
- user activity metrics, analyzing / Analyzing user activity metrics
- Latent Dirichlet Allocation (LDA) / Topic modeling
- LexRank algorithm / Understanding LexRank
- lexRankr package
- Linux, GitHub repository
- Linux operating system
- lists / Lists
M
- machine learning (ML)
- matrices / Matrices
N
- N-grams
- Natural Language Processing (NLP) / Features
- Netvizz application / Understanding Netvizz
- network communities
- network communities, English football social network
- news articles
- news data
- news data analysis
- nltk library
- node properties
- node properties, English football social network
O
P
R
- Read-Evaluate-Print-Loop (REPL) / Environment setup
- recommendation engine
- repository activity
- repository metrics
- analyzing / Analyzing repository metrics
- repository metric distributions, visualizing / Visualizing repository metric distributions
- repository metric correlations, analyzing / Analyzing repository metric correlations
- relationship, analyzing between stargazer and repository counts / Analyzing relationship between stargazer and repository counts
- relationship, analyzing between stargazer and fork counts / Analyzing relationship between stargazer and fork counts
- relationship, analyzing between total forks and repository count / Analyzing relationship between total forks, repository count, and health
- relationship, analyzing between total forks and repository health / Analyzing relationship between total forks, repository count, and health
- repository trends
- Rfacebook / Understanding Rfacebook
- rgithub package
- R package
- R programming language
- R programming language 3.3.1
- RStudio
S
- sentimental rankings
- sentiment analysis / Features
- sentiment trend analysis
- SentiNet / Sentiment analysis in R
- SentiWordNet / Sentiment analysis in R
- social media
- social media, advantages
- social media, challenges
- social media, disadvantages
- social network
- StackExchange
- StackExchange data dump
- supervised learning techniques
- Support Vector Machines (SVM) / Sentiment analysis in R
- syuzhet
T
- text analytics / Text analytics
- The Guardian
- The New York Times
- tips data
- topic modeling
- trend / Trend analysis
- trending repositories
- Twitter
U
V
W
- weekly code modification history
- weekly commit frequency
- weekly commit frequency comparison
- WordNet / Sentiment analysis in R
..................Content has been hidden....................
You can't read the all page of ebook, please click
here login for view all page.