It is possible to extract tweets about your company or a competitor on twitter using an R package called twitteR. Once you load this package, you can use the following commands to extract and archive tweets every day:
company.tweets = searchTwitter(‘@[your_screen_name_or_competitor]’,sinceID=[last_ID_extracted])
df <- do.call(“rbind”, lapply(company.tweets, as.data.frame))
write.csv(df,file=”c:\\[your_file].txt”)
Below list of commands facilitate extracting number of likes and talks for any given company from Facebook.com using R which can be automated with an end-of-day process and build up trend charts comparing your likes against competitors:
require(RCurl)
require(rjson)
data <- getURL(“http://graph.facebook.com/%5Byour_company_or_competitor%5D/”)
feed <- fromJSON(data)
df<-data.frame(created=Sys.date(),likes=feed$likes,talks=feed$talking_about_count,stringsAsFactors=FALSE)
write.csv(df,file=”c:\\[your_file].txt”)
And, below sniplet extracts list of all comments, about your company or your competitor into a nice formatted text file:
data <- getURL( “https://graph.facebook.com/%5Byour_company_or_competitor%5D/feed?limit=%5Ba_max_value%5D&access_token=%5Byour_token%5D” )
feed <- fromJSON(data)
N<-length(feed$data)
def<-data.frame(id=rep(0,N), name=rep(“”,N), created=rep(“”,N), likes = rep(0,N), message=rep(“”,N),stringsAsFactors=FALSE)
for(e in 1:N) {
def$id[e] <- feed$data[[e]]$from$id
def$name[e] <- feed$data[[e]]$from$name
def$created[e] <- feed$data[[e]]$created_time
if (is.null(feed$data[[e]]$likes) == FALSE) def$likes[e] <- feed$data[[e]]$likes$count
if (is.null(feed$data[[e]]$message) == FALSE) def$message[e] <- feed$data[[e]]$message
}
write.csv(def,file=”c:\\[your_file_2].txt”)
Please note that this extraction requires an access_token which can be received from developers.facebook.com.
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