Author: R-Bloggers

Feed: R-bloggers. Author: . I haven’t had a lot of time to play with this but yesterday, I discovered the tuber R package, which allows you to interact with the YouTube API. To use the tuber package, not only do you need to install it in R – you’ll need a Google account and will have to authorize 4 APIs through Developer Console: all 3 YouTube APIs (though the Data API will be doing the heavy lifting) and the Freebase API. Before you authorize the first API, Google will have you create a project to tie the APIs to. Then, ... Read More

Feed: R-bloggers. Author: . How to Read in and Clean Your Facebook Data – I recently learned that you can download all of your Facebook data, so I decided to check it out and bring it into R. To access your data, go to Facebook, and click on the white down arrow in the upper-right corner. From there, select Settings, then, from the column on the left, “Your Facebook Information.” When you get the Facebook Information screen, select “View” next to “Download Your Information.” On this screen, you’ll be able to select the kind of data you want, a date ... Read More

Feed: R-bloggers. Author: . I recently discovered the R Graph Gallery, where users can share the beautiful visualizations they’ve created using R and its various libraries (especially ggplot2). One of my favorite parts about this gallery is a section called Art From Data, in which users create works of art, sometimes with real data, and sometimes with a random number generator and a little imagination. Last night, I completed a DataCamp project to learn how to draw flowers in R and ggplot2. Based on that, I created this little yellow flower: Not only was the flower fun to create, it ... Read More

Feed: R-bloggers. Author: . Cloudy with a Chance of Words Lots of fun projects in the works, so today’s post will be short – a demonstration on how to create wordclouds, both with and without sentiment analysis results. While I could use song lyrics again, I decided to use a different dataset that comes with the quanteda packages: all 58 Inaugural Addresses, from Washington’s first speech in 1789 to Trump’s in 2017. library(quanteda) #install with install.packages("quanteda") if needed data(data_corpus_inaugural)speeches data_corpus_inaugural$documentsrow.names(speeches) NULL As you can see, this dataset has each Inaugural Address in a column called “texts,” with year and President’s ... Read More

Feed: R-bloggers. Author: . I’ve just returned from a business trip – lots of long days, working sometimes from 8 am to 9 pm or 10 pm. I didn’t get a chance to write this week’s Statistics Sunday post, in part because I wasn’t entirely certain what to write about. But as I started digging into sentiment analysis tools for a fun project I’m working on – and will hopefully post about soon – I found a few things I wanted to share. The tidytext package in R is great for tokenizing text and running sentiment analysis with 4 dictionaries: ... Read More

Feed: R-bloggers. Author: . I’m currently out of town and not spending as much time on my computer as I have over the last couple months. (It’s what happens when you’re the only one in your department at work and also most of your hobbies involve a computer.) But I wanted to write up something for Statistics Sunday and I recently discovered two R packages I need to check out in the near future. The first is called echor, which allows you to search and download data directly from the US Environmental Protection Agency (EPA) Environmental Compliance and History Online ... Read More

Feed: R-bloggers. Author: . How Has Taylor Swift’s Word Choice Changed Over Time?Sunday night was a big night for Taylor Swift – not only was she nominated for multiple Billboard Music Awards; she took home Top Female Artist and Top Selling Album. So I thought it was a good time for some more Taylor Swift-themed statistical analysis. When I started this blog back in 2011, my goal was to write deep thoughts on trivial topics – specifically, to overthink and overanalyze pop culture and related topics that appear fluffy until you really dig into them. Recently, I’ve been blogging more ... Read More

Feed: R-bloggers. Author: . Welcome to the Hotel CaliforniaAs promised in last week’s post, this week: sentiment analysis, also with song lyrics. Sentiment analysis is a method of natural language processing that involves classifying words in a document based on whether a word is positive or negative, or whether it is related to a set of basic human emotions; the exact results differ based on the sentiment analysis method selected. The tidytext R package has 4 different sentiment analysis methods: “AFINN” for Finn Årup Nielsen – which classifies words from -5 to +5 in terms of negative or positive valence ... Read More

Feed: R-bloggers. Author: . Earlier this week, the Association for Psychological Science sent out a press release about a study examining what makes a song popular: Researchers Jonah Berger of the University of Pennsylvania and Grant Packard of Wilfrid Laurier University were interested in understanding the relationship between similarity and success. In a recent study published in Psychological Science, the authors describe how a person’s drive for stimulation can be satisfied by novelty. Cultural items that are atypical, therefore, may be more liked and become more popular. “Although some researchers have argued that cultural success is impossible to predict,” they ... Read More

Feed: R-bloggers. Author: . Statistics Sunday Last week, I showed how to tokenize text. Today I’ll use those functions to do some text analysis of one of my favorite types of text: song lyrics. Plus, this is a great opportunity to demonstrate a new R package I discovered: geniusR, which will download lyrics from Genius. There are two packages – geniusR and geniusr – which will do this. I played with both and found geniusR easier to use. Neither is perfect, but what is perfect, anyway? To install geniusR, you’ll use a different method than usual – you’ll need to ... Read More