Sentiment-Analysis-Using-R

Sentiment Analysis of tweets for any Twitter Handles consumer_key <- 'xxxxx' consumer_secret <- 'xxxxxx' access_token <- 'xxxxxx' access_secret <- 'xxxxxx' setup_twitter_oauth(consumer_key, consumer_secret, access_token, access_secret) options(httr_oauth_cache = T) tweets <- userTimeline("@MBuhari", n = 3000) ntweets <- length(tweets) tweets.df <- twListToDF(tweets) head(tweets.df$text) tweets_df2 <- gsub("https.","",tweets.df$text) tweets_df2 <- gsub("https.","",tweets_df2) tweets_df2 <- gsub("#.","",tweets_df2) tweets_df2 <- gsub("@.","",tweets_df2) head(tweets_df2) word_df <- as.vector(tweets_df2) emotion_df <- get_nrc_sentiment(word_df) emotion_df2 <- cbind(tweets_df2,emotion_df) head(emotion_df2) sent_value <- get_sentiment(word_df) most_positive <- word_df[sent_value == max(sent_value)] most_negative <- word_df[sent_value <= min(sent_value)] positive_tweets <- word_df[sent_value > 0] negative_tweets <- word_df[sent_value < 0] neutral_tweets <- word_df[sent_value == 0] category_sent <- ifelse(sent_value < 0, "Negative", ifelse(sent_value > 0, "Positive", "Neutral") ) table(category_sent)