Getting Started With Twitter Analysis in R

Earlier today, I saw a post vis the aggregating R-Bloggers service a post on Using Text Mining to Find Out What @RDataMining Tweets are About. The post provides a walktrhough of how to grab tweets into an R session using the twitteR library, and then do some text mining on it.

I’ve been meaning to have a look at pulling Twitter bits into R for some time, so I couldn’t but have a quick play…

Starting from @RDataMiner’s lead, here’s what I did… (Notes: I use R in an R-Studio context. If you follow through the example and a library appears to be missing, from the Packages tab search for the missing library and import it, then try to reload the library in the script. The # denotes a commented out line.)

#The original example used the twitteR library to pull in a user stream
#rdmTweets <- userTimeline("psychemedia", n=100)
#Instead, I'm going to pull in a search around a hashtag.
rdmTweets <- searchTwitter('#mozfest', n=500)
# Note that the Twitter search API only goes back 1500 tweets (I think?)

#Create a dataframe based around the results
df <-"rbind", lapply(rdmTweets,
#Here are the columns
#And some example content

So what can we do out of the can? One thing is look to see who was tweeting most in the sample we collected:


# Let's do something hacky:
# Limit the data set to show only folk who tweeted twice or more in the sample
barplot(cc,las=2,cex.names =0.3)

Now let’s have a go at parsing some tweets, pulling out the names of folk who have been retweeted or who have had a tweet sent to them:

#Whilst tinkering, I came across some errors that seemed
# to be caused by unusual character sets
#Here's a hacky defence that seemed to work...
df$text=sapply(df$text,function(row) iconv(row,to='UTF-8'))

#A helper function to remove @ symbols from user names...
trim <- function (x) sub('@','',x)

#A couple of tweet parsing functions that add columns to the dataframe
#We'll be needing this, I think?
#Pull out who a message is to
df$to=sapply(df$text,function(tweet) str_extract(tweet,"^(@[[:alnum:]_]*)"))
df$to=sapply(df$to,function(name) trim(name))

#And here's a way of grabbing who's been RT'd
df$rt=sapply(df$text,function(tweet) trim(str_match(tweet,"^RT (@[[:alnum:]_]*)")[2]))

So for example, now we can plot a chart showing how often a particular person was RT’d in our sample. Let’s use ggplot2 this time…


Okay – enough for now… if you’re tempted to have a play yourself, please post any other avenues you explored with in a comment, or in your own post with a link in my comments;-)


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  5. oppih Xue

    When I was trying the last command, I just got ” rror: could not find function “ggplot” “,
    I’ve installed the package “ggplot2″, so I cannot get what I want here.
    Anyone has the same problem with me ?

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  7. Ciprian Begu (@ciprianbegu)

    Interesting example. It is great that R can now access tweets. Right now, I am trying to implement a digital marketing project that requires me to get 2-month’s worth of data from Twitter, during December and January. Basically I have to get all the tweets tagged with a location identifier (checkins from Foursquare or Gowalla), in a radius of 50 kilometers around the center of Brussels, Belgium, but only the locations that are supermarkets of certain brands (e.g. delhaize, colruyt, carrefour) AND the fast-food restaurants (mcdonalds, quick, pizza hut).

    If I could somehow build a database containing these particular tweets with their corresponding timestamp and location stamp it would be absolutely great.

    My questions are:

    Can this be done?

    If yes how would the data gathering be done. Every week for the previous week, until the 1st of February?

    Where would I store all this data. In one file? If yes, how do I append it so that the tweets are numbered correctly?

    Many thanks for an answer

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