Wordcloud truncates text

Question

I use twitter API to create moods. I am trying to create a word cloud based on tweets.

Here is my code for generating wordcloud

wordcloud(clean.tweets, random.order=F,max.words=80, col=rainbow(50), scale=c(3.5,1))

Result for this:

I also tried this:

pal <- brewer.pal(8,"Dark2")

wordcloud(clean.tweets,min.freq = 125,max.words = Inf,random.order  = TRUE,colors = pal)

Result for this:

Did I miss something?

Here's how I get and clean tweets:

#downloading tweets
tweets <- searchTwitter("#hanshtag",n = 5000, lang = "en",resultType = "recent")
# removing re tweets 
no_retweets <- strip_retweets(tweets , strip_manual = TRUE)

#converts to data frame
df <- do.call("rbind", lapply(no_retweets , as.data.frame))

#remove odd characters
df$text <- sapply(df$text,function(row) iconv(row, "latin1", "ASCII", sub="")) #remove emoticon
df$text = gsub("(f|ht)tp(s?)://(.*)[.][a-z]+", "", df$text) #remove URL
sample <- df$text


    # Cleaning Tweets 
    sum_txt1 <- gsub("(RT|via)((?:\\b\\w*@\\w+)+)","",sample)
    sum_txt2 <- gsub("http[^[:blank:]]+","",sum_txt1)
    sum_tx3 <- gsub("@\\w+","",sum_txt2)
    sum_tx4 <- gsub("[[:punct:]]"," ", sum_tx3)
    sum_tex5 <- gsub("[^[:alnum:]]", " ", sum_tx4)
    sum_tx6 <- gsub("RT  ","", sum_tex5)

    # WordCloud

    # data frame is not good for text convert it corpus
    corpus <- Corpus(VectorSource(sum_tx6))
    clean.tweets<- tm_map(corpus , content_transformer(tolower)) #converting everything to lower cases
    clean.tweets<- tm_map(guj_clean,removeWords, stopwords("english")) #stopword are words like of, the, a, as..
    clean.tweets<- tm_map(guj_clean, removeNumbers)
    clean.tweets<- tm_map(guj_clean, stripWhitespace)

Thanks in advance!

Answer 1

Try changing the scale to wordcloud from c (3.5.1) to c (3.5,0.25).

wordcloud(clean.tweets, random.order=F,max.words=80, col=rainbow(50), scale=c(3.5,0.25))