geocoded_Tweets.R

doInstall <- TRUE
toInstall <- c("twitteR", "dismo", "maps", "ggplot2")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

searchTerm <- "#rstats"
searchResults <- searchTwitter(searchTerm, n = 1000)  # Gather Tweets 
tweetFrame <- twListToDF(searchResults)  # Convert to a nice dF

userInfo <- lookupUsers(tweetFrame$screenName)  # Batch lookup of user info
userFrame <- twListToDF(userInfo)  # Convert to a nice dF

locatedUsers <- !is.na(userFrame$location)  # Keep only users with location info

locations <- geocode(userFrame$location[locatedUsers])  # Use amazing API to guess
# approximate lat/lon from textual location data.
with(locations, plot(lon, lat))

worldMap <- map_data("world")  # Easiest way to grab a world map shapefile

zp1 <- ggplot(worldMap)
zp1 <- zp1 + geom_path(aes(x = long, y = lat, group = group),  # Draw map
                       colour = gray(2/3), lwd = 1/3)
zp1 <- zp1 + geom_point(data = locations,  # Add points indicating users
                        aes(x = lon, y = lat),
                        colour = "RED", alpha = 1/2, size = 1)
zp1 <- zp1 + coord_equal()  # Better projections are left for a future post
zp1 <- zp1 + theme_minimal()  # Drop background annotations
print(zp1)