I thought it would be fun to play around with the R package twitteR , an R API into Twitter.  I decided to take the most prominent news story of the past few days, Osama bin Laden’s death, to see the progression of tweets as news spread.  I quickly found that the max results for the searchTwitter() function were 1500 per day since this is such a big story right now.  I decided to narrow the results by location using the geocode parameter to look at how people in Denver were tweeting.  I used the Colorado State Capitol Building (39.739567,-104.984794) with a radius of 6 miles.  I am still maxing out the results per day, but it looks like a better representation than at a 5 mile radius.  I’m still new to this API so maybe with a little tweaking, I can improve the results.

library(twitteR)
#Colorado State Capitol Building
geoLocation = '39.739567,-104.984794,6mi'
tweets <- searchTwitter("Osama Bin Laden", n=1500,
     geocode=geoLocation, since='2011-04-30', until='2011-05-01')
tweets <- rbind(tweets, searchTwitter("Osama Bin Laden", n=1500,
     geocode=geoLocation, since='2011-05-01', until='2011-05-02'))
tweets <- rbind(tweets, searchTwitter("Osama Bin Laden", n=1500,
     geocode=geoLocation, since='2011-05-02', until='2011-05-03'))
tweets <- rbind(tweets, searchTwitter("Osama Bin Laden", n=1500,
     geocode=geoLocation, since='2011-05-03'))
times <- sapply(tweets, function(x) format(x$created,
     "%m-%d %H:00",tz = "America/Denver"))
users <- sapply(tweets, function(x) x$screenName)
times <- times[!duplicated(users)] #removing duplicate
counts <- table(times)
bp <- barplot(counts, main="Counts of 'Osama Bin Laden' Tweets by
     Hour\nwithin 6 miles of Colorado State Capitol Building",
     col="lightblue", border=NA, ylim=c(0,300),las=3 )
lines(spline(counts ~ bp), lwd=3, lty="dashed", col="darkblue")