geoffjentry
No request token to open this page
I have implemented a twitter application on my website based on OAuth. But I got the error : Whoa there! There is no request token for this page. That’s the special key we need from applications asking to use your Twitter account. Please go back to the site or application that sent you here and try again; it was probably just a mistake.
–> i reseted the costumery key & secret key, but nothing. I also, reseted my token, but still nothing. My code is as follows: #connect all libraries library(twitteR) library(ROAuth) library(plyr) library(dplyr) library(stringr) library(ggplot2)
#connect to API download.file(url='https://curl.haxx.se/ca/cacert.pem', destfile='cacert.pem') reqURL <- 'https://api.twitter.com/oauth/request_token' accessURL <- 'https://api.twitter.com/oauth/access_token' authURL <- 'https://api.twitter.com/oauth/authenticate' consumerKey <- 'use29u2CLpp9Pb9aeALPBgKwf' #put the Consumer Key from Twitter Application consumerSecret <- 'YRYvAExvschnj2fnPw4iIGC58xuk9xJyqDWG8zTTH3OBqDyuUY' #put the Consumer Secret from Twitter Application Cred <- OAuthFactory$new(consumerKey=consumerKey, consumerSecret=consumerSecret, requestURL=reqURL, accessURL=accessURL, authURL=authURL) Cred$handshake(cainfo = system.file('CurlSSL', 'cacert.pem', package = 'RCurl')) #There is URL in Console. You need to go to, get code and enter it in Console
save(Cred, file='twitter authentication.Rdata') load('twitter authentication.Rdata') #Once you launched the code first time, you can start from this line in the future (libraries should be connected) registerTwitterOAuth(Cred)
#the function for extracting and analyzing tweets search <- function(searchterm) { #extact tweets and create storage file
list <- searchTwitter(searchterm, cainfo='cacert.pem', n=1500) df <- twListToDF(list) df <- df[, order(names(df))] df$created <- strftime(df$created, '%Y-%m-%d') if (file.exists(paste(searchterm, '_stack.csv'))==FALSE) write.csv(df, file=paste(searchterm, '_stack.csv'), row.names=F)
#merge the last extraction with storage file and remove duplicates stack <- read.csv(file=paste(searchterm, '_stack.csv')) stack <- rbind(stack, df) stack <- subset(stack, !duplicated(stack$text)) write.csv(stack, file=paste(searchterm, '_stack.csv'), row.names=F)
#tweets evaluation function score.sentiment <- function(sentences, pos.words, neg.words, .progress='none') { require(plyr) require(stringr) scores <- laply(sentences, function(sentence, pos.words, neg.words){ sentence <- gsub('[[:punct:]]', "", sentence) sentence <- gsub('[[:cntrl:]]', "", sentence) sentence <- gsub('\d+', "", sentence) sentence <- tolower(sentence) word.list <- str_split(sentence, '\s+') words <- unlist(word.list) pos.matches <- match(words, pos.words) neg.matches <- match(words, neg.words) pos.matches <- !is.na(pos.matches) neg.matches <- !is.na(neg.matches) score <- sum(pos.matches) - sum(neg.matches) return(score) }, pos.words, neg.words, .progress=.progress) scores.df <- data.frame(score=scores, text=sentences) return(scores.df) }
pos <- scan('C://positive-words.txt', what='character', comment.char=';') #folder with positive dictionary neg <- scan('C://negative-words.txt', what='character', comment.char=';') #folder with negative dictionary pos.words <- c(pos, 'upgrade') neg.words <- c(neg, 'wtf', 'wait', 'waiting', 'epicfail')
Dataset <- stack Dataset$text <- as.factor(Dataset$text) scores <- score.sentiment(Dataset$text, pos.words, neg.words, .progress='text') write.csv(scores, file=paste(searchterm, '_scores.csv'), row.names=TRUE) #save evaluation results
#total score calculation: positive / negative / neutral stat <- scores stat$created <- stack$created stat$created <- as.Date(stat$created) stat <- mutate(stat, tweet=ifelse(stat$score > 0, 'positive', ifelse(stat$score < 0, 'negative', 'neutral'))) by.tweet <- group_by(stat, tweet, created) by.tweet <- summarise(by.tweet, number=n()) write.csv(by.tweet, file=paste(searchterm, '_opin.csv'), row.names=TRUE)
#chart ggplot(by.tweet, aes(created, number)) + geom_line(aes(group=tweet, color=tweet), size=2) + geom_point(aes(group=tweet, color=tweet), size=4) + theme(text = element_text(size=18), axis.text.x = element_text(angle=90, vjust=1)) + #stat_summary(fun.y = 'sum', fun.ymin='sum', fun.ymax='sum', colour = 'yellow', size=2, geom = 'line') + ggtitle(searchterm)
ggsave(file=paste(searchterm, '_plot.jpeg'))
}
search("stockmarket") #enter keyword
Any one can help? ASAP please
