library(twitteR)
library(tm)
library(wordcloud)
library(RColorBrewer)


api_key <- "c1OvJfvNxzd4H01PzVpGQSQM1"

api_secret <- "Qxe1JKMJefn22HQnWHTP46LnFx86eyHf9Qc24nOfuimHceQwAW"

access_token <- "1095432120-csFurAKhaOAVVIwMQFEGPoNoIUwFTcFqaZUHDL2"

access_token_secret <- "0zeEh45a2l6jiHkJYjbyOURGcodd9pncsgQR3jYT2hsWq"

setup_twitter_oauth(api_key,api_secret,access_token,access_token_secret)


tweets <- searchTwitter("#NASA",lang = "pt", n = 250)


# Create an empty character vector of the same length as the number of
# tweets
l <- length(tweets)
tweeter <- vector(mode = "character", length = l)

# Extract the screen names from each tweet status
for (i in 1:l) tweeter[i] <- tweets[[i]]$getScreenName()


# Compile the frequencies of each screen name
tweeter.freq <- table(tweeter)


# Black backgrounds are 'this year's colour' in terms of dataviz!
par(bg = "grey")

# Draw the word cloud
wordcloud(names(tweeter.freq), tweeter.freq, colors = c("tomato",
                                                        "wheat", "lightblue"), scale = c(6, 0.5), random.color = TRUE, rot.per = 0.5,
          min.freq = 1, font = 2, family = "serif")