Created
January 30, 2023 23:35
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| # assuming you have downloaded the data (Data1.csv) correctly, | |
| # as discussed here: https://piazza.com/class/l7oq25mqbrz1nd/post/110 | |
| # you may need to change the file location in quotes below, to suit where your file is | |
| apple <- read.csv("~/Documents/Data1.csv", stringsAsFactors = F, encoding="UTF-8") | |
| str(apple) | |
| install.packages("tm") | |
| library(tm) | |
| corpus <- iconv(apple$text, "ASCII", "UTF-8") | |
| corpus <- Corpus(VectorSource(corpus)) | |
| inspect(corpus[1:15]) | |
| corpus <- tm_map(corpus, tolower) | |
| inspect(corpus[1:15]) | |
| corpus <- tm_map(corpus, removePunctuation) | |
| inspect(corpus[1:15]) | |
| corpus <- tm_map(corpus, removeNumbers) | |
| inspect(corpus[1:15]) | |
| cleanset <- tm_map(corpus, removeWords, stopwords('english')) | |
| inspect(cleanset[1:15]) | |
| removeURL <- function(x) gsub('http[[:alnum:]]*', '', x) | |
| cleanset <- tm_map(cleanset, content_transformer(removeURL)) | |
| inspect(cleanset[1:15]) | |
| cleanset <- tm_map(cleanset, removeWords, c('aapl', 'apple')) | |
| cleanset <- tm_map(cleanset, gsub, | |
| pattern = 'stocks', | |
| replacement = 'stock') | |
| cleanset <- tm_map(cleanset, stemDocument) | |
| cleanset <- tm_map(cleanset, stripWhitespace) | |
| inspect(cleanset[1:7]) | |
| tdm <- TermDocumentMatrix(cleanset) | |
| tdm <- as.matrix(tdm) | |
| tdm[1:10, 1:20] | |
| w <- rowSums(tdm) | |
| w <- subset(w, w>=25) | |
| barplot(w, | |
| las = 2, | |
| col = rainbow(50)) | |
| install.packages("wordcloud") | |
| library(wordcloud) | |
| w <- sort(rowSums(tdm), decreasing = TRUE) | |
| set.seed(222) | |
| wordcloud(words = names(w), | |
| freq = w, | |
| max.words = 150, | |
| random.order = F, | |
| min.freq = 5, | |
| colors = brewer.pal(8, 'Dark2'), | |
| scale = c(5, 0.3), | |
| rot.per = 0.7) | |
| install.packages("syuzhet") | |
| library(syuzhet) | |
| # you may need to change the file location in quotes below, to suit where your file is | |
| apple <- read.csv("~/Documents/Data1.csv", stringsAsFactors = F, encoding="UTF-8") | |
| texts <- iconv(apple$text, "ASCII", "UTF-8", sub="byte") | |
| raw_data$textCol<- iconv(raw_data$textCol, "ASCII", "UTF-8", sub="byte") | |
| s <- get_nrc_sentiment(texts) | |
| head(s) | |
| barplot(colSums(s), | |
| las = 2, | |
| col = rainbow(10), | |
| ylab = 'Count', | |
| main = 'Sentiment Scores Tweets') |
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