Digital Media
Analysis with R
1st Edition
Published on 1. January 2021
Book
Hardback
250 pages
978-1-4987-5852-9 (ISBN)
More details
Series
Language
English
Place of publication
Portland
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-4987-5852-9 (9781498758529)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Content
Getting the Data. Importing CSV, XLS and TXT into R. Twitter (steamR, twitteR, Twitter Rest API). Facebook (Rfacebook,
customized functions). Social Media (Rflickr, plusser, SocialMediaMineR). Email (Enron dataset, AoIR and IAMCR listservs, Yahoo
Groups). News (GuardianR, RNYTimes). Google (r-google-analytics, scholar, RGoogleTrends, RgoogleMaps). Web and Wikipedia
((RCurl, httr, XML). rOpenSci (RMendeley, rplos, rAltmetric, etc.). Blogs (httr, RCurl, scrapeR). Processing the Data. R data types
(numerical, character, logical). Date-Time data classes (Date, POSIXct). Summary statistics. Correlation matrix and linear
regression. Plotting with R Base Graphics. Plotting with R packages (lattice, ggplot, googleViz, corrplot). Analyzing the Data.
Network analisys (sna, igraph, Matrix, statnet). Text analysis with regular expression. Content analysis (tm, LSA, wordcloud,
topicsmodels). Linear regression (lm, glm, predict). Time series (forecast, zoo, lubridate). Clustering (kmeans, cluster, mclust. Spatial
analysis (spatstat, sp, rgdal, maptools, rgeos)
customized functions). Social Media (Rflickr, plusser, SocialMediaMineR). Email (Enron dataset, AoIR and IAMCR listservs, Yahoo
Groups). News (GuardianR, RNYTimes). Google (r-google-analytics, scholar, RGoogleTrends, RgoogleMaps). Web and Wikipedia
((RCurl, httr, XML). rOpenSci (RMendeley, rplos, rAltmetric, etc.). Blogs (httr, RCurl, scrapeR). Processing the Data. R data types
(numerical, character, logical). Date-Time data classes (Date, POSIXct). Summary statistics. Correlation matrix and linear
regression. Plotting with R Base Graphics. Plotting with R packages (lattice, ggplot, googleViz, corrplot). Analyzing the Data.
Network analisys (sna, igraph, Matrix, statnet). Text analysis with regular expression. Content analysis (tm, LSA, wordcloud,
topicsmodels). Linear regression (lm, glm, predict). Time series (forecast, zoo, lubridate). Clustering (kmeans, cluster, mclust. Spatial
analysis (spatstat, sp, rgdal, maptools, rgeos)