Files
uni-ba-socialagenda/extract-twitter-accounts.R
T
2014-12-05 13:21:53 +01:00

188 lines
6.2 KiB
R

# PREPARATIONS ------------------------------------------------------------
require(jsonlite)
require(stringr)
require(RCurl)
require(devtools)
require(RTwitterAPI)
setwd("~/Dokumente/Uni/Aktuell/BA-Arbeit/uni-ba-issuecomp")
source("functions.R")
# # Set curl handle for friendly scraping
# handle <- getCurlHandle(httpheader = list(from = "max.mehl@uni.kn",
# 'user-agent' = str_c(R.version$version.string)
# )
# )
acc_url <- "http://www.bundestwitter.de/api/politiker"
acc_df <- fromJSON(acc_url)
# COLLECT ALL TWEETS ------------------------------------------------------
# http://www.joyofdata.de/blog/twitters-rest-api-v1-1-with-r-for-linux-and-windows/
# --> devtools::install_github("joyofdata/RTwitterAPI")
# https://dev.twitter.com/rest/reference/get/statuses/user_timeline
api_params <- c(
"oauth_consumer_key" = "c9Ob2fWNSONMC0mA2JlNaeRke",
"oauth_nonce" = NA,
"oauth_signature_method" = "HMAC-SHA1",
"oauth_timestamp" = NA,
"oauth_token" = "1007025684-RFxCDFc4OPkt02bASmdci00TB4jgaPjfqxLRT58",
"oauth_version" = "1.0",
"consumer_secret" = "cZ3Il2hmbLgK0Lc57mj5kUvymjVdsmZKYwKOGHR3NhCpvWgEOI",
"oauth_token_secret" = "rvfv8MgexFKTqrPNSoGrdrZVNhV4fTJb2Bgz249nbvKNg"
)
api_url2 <- "https://api.twitter.com/1.1/statuses/show.json"
id2="325330742961909760"
query2 <- c(id=id2, trim_user="true", include_entities="false")
current2 <- twitter_api_call(api_url2, query2, api_params)
api_url <- "https://api.twitter.com/1.1/statuses/user_timeline.json";
max_count <- "200"
keep <- c("created_at", "id_str", "text", "retweet_count")
tweets_full <- data.frame(user=character(), name=character(), created_at=character(), id_str=character(), text=character(), retweet_count=character())
for(a in 201:nrow(acc_df)) {
user <- as.character(acc_df$screenname[a])
name <- as.character(acc_df$name[a])
max_id <- "999999999999999999"
loop <- 1
error <- 0
repeat {
# Define specific search query
query <- c(include_rts=1, exclude_replies="true", trim_user="true", include_entities="false",
screen_name=user,
count=max_count,
max_id=max_id);
# At first, work with an temporary tweet-DB
current <- twitter_api_call(api_url, query, api_params)
tweets_temp <- fromJSON(correctJSON(current))
## STAT ERROR HANDLING ##
# Check for empty API returns
status <- length(tweets_temp)
if(status == 0) {
if(error > 2) {
cat("[WARNING] 3x empty API result. Aborting now.\n")
break
}
cat("[WARNING] Empty API result. Trying again.\n")
rm(tweets_temp)
error <- error + 1
Sys.sleep(3)
next
}
# Check if API output contains error fields
status <- "error" %in% names(tweets_temp)
if(status) {
cat("[WARNING] Error in API request:", tweets_temp$error[1],"\n")
rm(tweets_temp)
break
}
# Check for other errors, mostly rate limits
status <- "errors" %in% names(tweets_temp)
if(status) {
cat("[WARNING] Error in API request:", tweets_temp$errors[1,1],"\n")
# Rate limit exceeded?
status <- tweets_temp$errors[1,2]
if(status == 88) {
rate_api_url <- "https://api.twitter.com/1.1/application/rate_limit_status.json"
rate_query <-c (resources="statuses")
resettime <- fromJSON(twitter_api_call(rate_api_url, rate_query, api_params))
resettime <- resettime$resources$statuses$`/statuses/user_timeline`$reset
curtime <- as.numeric(as.POSIXct(Sys.time()))
wait <- round(resettime - curtime + 10)
cat("[INFO] Rate limit is exceeded. Now waiting",wait,"seconds.\n")
Sys.sleep(wait)
}
rm(tweets_temp)
Sys.sleep(3)
next
}
## END ERROR HANDLING ##
# Delete unnecessary columns and add username and real name to dataframe
tweets_temp <- tweets_temp[keep]
tweets_temp <- cbind(user=user, name=name, tweets_temp)
# Now sleep 3 second to dodge 300queries/15min limit
cat("[",a,"/",nrow(acc_df),"] ", sep = "")
cat("User: ",user," in loop: ",loop,". \n", sep = "")
Sys.sleep(2)
if(tweets_full$id_str[nrow(tweets_full)] == tweets_temp$id_str[nrow(tweets_temp)] && nrow(tweets_full) > 0) {
cat("[INFO] Last tweet of temp is last tweet of full. Abort loop and begin with next user.\n")
break
}
# Is the last tweet in tweets_temp from 2013?
status <- str_detect(tweets_temp$created_at[nrow(tweets_temp)], "2014$")
# Last loop is reached. Now clear the data frame
if (!status) { # Starting when tweet not from 2014
# Delete all tweets other than from 2014
old <- 0
for(r in 1:nrow(tweets_temp)) {
status <- str_detect(tweets_temp$created_at[r], "2014$")
if(is.na(status)) {
#status <- FALSE
cat("[INFO] NA-Status in Tweet", r)
}
if(!status) { # Starting when tweet not from 2014
old <- old + 1
}
}
if(old > 0) {
old <- old - 1
# If even the first entry isn't from 2014, we have to set "old" manually because of a bug
status <- str_detect(tweets_temp$created_at[1], "2014$")
if(!status) {
old <- nrow(tweets_temp)
cat("[INFO] Timeline enhält keinen einzigen aus 2014\n")
}
# delete all lines which are older than 2014
tweets_temp <- head(tweets_temp, -old)
}
rm(old)
tweets_full <- insertRow(tweets_full, tweets_temp)
rm(tweets_temp)
break # End loop because 2013 is reached
}
# The last tweet is still from 2014, so we need another loop
else {
# Setting max_id to gather next 200 tweets
max_id <- tweets_temp$id_str[nrow(tweets_temp)]
loop <- loop + 1 # just for stats
tweets_full <- insertRow(tweets_full, tweets_temp)
rm(tweets_temp)
}
} # /repeat
stat_tweet <- nrow(tweets_full)
cat("User:",user,"finished after",loop,"loops. Total Tweets now:",nrow(tweets_full),"\n")
write.csv(tweets_full, "tweets_full.csv")
# Every tweet from 2014 from user[r] is downloaded. Now next user in for-loop
}