}
## 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
}
## Last loop is reached. Now clear the data frame
#     # Is the last tweet in tweets_temp from 2013?
#     status <- str_detect(tweets_temp$created_at[nrow(tweets_temp)], "2014$")
# Extract year of last tweet in tweets_temp
year <- as.numeric(str_extract(tweets_temp$created_at[nrow(tweets_temp)], "\\d{4}$"))
status <- year < 2014
if (status) { # Starting when tweet is earlier than 2014 (i.e. 2013, 2012...)
#       # 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 newer or equal 2014, so we need another loop
else {
# Setting max_id to gather next 200 tweets
max_id <- tweets_temp$id_str[nrow(tweets_temp)]
loop <- loop + 1  # just for stats
tweets_full <- insertRow(tweets_full, tweets_temp)
#rm(tweets_temp)
}
} # /repeat
tweets_complete <- insertRow(tweets_complete, tweets_full)
tweets_full <- head(tweets_full, -nrow(tweets_full)) # Empty tweets_full
cat("User:",user,"finished after",loop,"loops. Total Tweets now:",nrow(tweets_complete),"\n")
write.csv(tweets_complete, "tweets_complete.csv")
# Every tweet from 2014 or newer from user[a] is downloaded. Now next user in for-loop
}
api_url <- "https://api.twitter.com/1.1/statuses/user_timeline.json";
max_count <- "200"
keep <- c("created_at", "id_str", "text", "retweet_count")
# tweets_complete: All tweets
# tweets_full: All tweets of current user
# tweets_temp: The current max 200 tweets of current user
tweets_full <- data.frame(user=character(), name=character(), created_at=character(), id_str=character(), text=character(), retweet_count=character())
tweets_complete <- tweets_full
for(a in 1:nrow(acc_df)) {
user <- as.character(acc_df$twitter_acc[a])
name <- as.character(acc_df$name[a])
max_id <- "999999999999999999"
loop <- 1
error <- 0
repeat {
# Define specific search query
query <- c(include_rts=1, exclude_replies="true", trim_user="true", include_entities="false",
screen_name=user,
count=max_count,
max_id=max_id);
# At first, work with an temporary tweet-DB
current <- twitter_api_call(api_url, query, api_params)
rm(tweets_temp)
tweets_temp <- fromJSON(correctJSON(current))
## START ERROR HANDLING ##
# Empty API output
status <- errorEmptyAPI(tweets_temp)
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
# Contains "error" column
status <- errorErrorColumn(tweets_temp)
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
# Check if error code exists
code <- errorCheckCode(tweets_temp) # 0 if no error
if(code == 34) {  # page does not exist
status <- errorCode34()
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
}
if(code == 88) {  # rate limit exceeded
wait <- errorCode88()
Sys.sleep(wait)
next
}
## END ERROR HANDLING ##
# Delete unnecessary columns and add username and real name to dataframe
tweets_temp <- tweets_temp[keep]
tweets_temp <- cbind(user=user, name=name, tweets_temp)
# Now sleep 3 second to dodge 300queries/15min limit
cat("[",a,"/",nrow(acc_df),"] ", sep = "")
cat("User: ",user," in loop: ",loop,". \n", sep = "")
Sys.sleep(2)
if(tweets_full$id_str[nrow(tweets_full)] == tweets_temp$id_str[nrow(tweets_temp)] && nrow(tweets_full) > 0) {
cat("[INFO] Last tweet of temp is last tweet of full. Abort loop and begin with next user.\n")
break
}
## Last loop is reached. Now clear the data frame
#     # Is the last tweet in tweets_temp from 2013?
#     status <- str_detect(tweets_temp$created_at[nrow(tweets_temp)], "2014$")
# Extract year of last tweet in tweets_temp
year <- as.numeric(str_extract(tweets_temp$created_at[nrow(tweets_temp)], "\\d{4}$"))
status <- year < 2014
if (status) { # Starting when tweet is earlier than 2014 (i.e. 2013, 2012...)
#       # Delete all tweets other than from 2014
#       old <- 0
#       for(r in 1:nrow(tweets_temp)) {
#         status <- str_detect(tweets_temp$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$")
#         if(!status) {
#           old <- nrow(tweets_temp)
#           cat("[INFO] Timeline enhält keinen einzigen aus 2014\n")
#         }
#
#         # delete all lines which are older than 2014
#         tweets_temp <- head(tweets_temp, -old)
#       }
#       rm(old)
tweets_full <- insertRow(tweets_full, tweets_temp)
#rm(tweets_temp)
break  # End loop because 2013 is reached
}
# The last tweet is newer or equal 2014, so we need another loop
else {
# Setting max_id to gather next 200 tweets
max_id <- tweets_temp$id_str[nrow(tweets_temp)]
loop <- loop + 1  # just for stats
tweets_full <- insertRow(tweets_full, tweets_temp)
#rm(tweets_temp)
}
} # /repeat
tweets_complete <- insertRow(tweets_complete, tweets_full)
tweets_full <- head(tweets_full, -nrow(tweets_full)) # Empty tweets_full
cat("User:",user,"finished after",loop,"loops. Total Tweets now:",nrow(tweets_complete),"\n")
write.csv(tweets_complete, "tweets_complete.csv")
# Every tweet from 2014 or newer from user[a] is downloaded. Now next user in for-loop
}
tweets_full <- data.frame(user=character(), name=character(), created_at=character(), id_str=character(), text=character(), retweet_count=character())
tweets_complete <- tweets_full
for(a in 1:nrow(acc_df)) {
user <- as.character(acc_df$twitter_acc[a])
name <- as.character(acc_df$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)
rm(tweets_temp)
tweets_temp <- fromJSON(correctJSON(current))
## START ERROR HANDLING ##
# Empty API output
status <- errorEmptyAPI(tweets_temp)
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
# Contains "error" column
status <- errorErrorColumn(tweets_temp)
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
# Check if error code exists
code <- errorCheckCode(tweets_temp) # 0 if no error
if(code == 34) {  # page does not exist
status <- errorCode34()
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
}
if(code == 88) {  # rate limit exceeded
wait <- errorCode88()
Sys.sleep(wait)
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
}
## Last loop is reached. Now clear the data frame
#     # Is the last tweet in tweets_temp from 2013?
#     status <- str_detect(tweets_temp$created_at[nrow(tweets_temp)], "2014$")
# Extract year of last tweet in tweets_temp
year_last <- as.numeric(str_extract(tweets_temp$created_at[nrow(tweets_temp)], "\\d{4}$"))
status <- year_last < 2014
if (status) { # Starting when tweet is earlier than 2014 (i.e. 2013, 2012...)
year_first <- as.numeric(str_extract(tweets_temp$created_at[1], "\\d{4}$"))
status <- year_first < 2014
cat("[INFO] Timeline enhält keinen einzigen aus 2014\n")
}
#       # 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 newer or equal 2014, so we need another loop
else {
# Setting max_id to gather next 200 tweets
max_id <- tweets_temp$id_str[nrow(tweets_temp)]
loop <- loop + 1  # just for stats
tweets_full <- insertRow(tweets_full, tweets_temp)
#rm(tweets_temp)
}
} # /repeat
tweets_complete <- insertRow(tweets_complete, tweets_full)
tweets_full <- head(tweets_full, -nrow(tweets_full)) # Empty tweets_full
cat("User:",user,"finished after",loop,"loops. Total Tweets now:",nrow(tweets_complete),"\n")
write.csv(tweets_complete, "tweets_complete.csv")
# Every tweet from 2014 or newer from user[a] is downloaded. Now next user in for-loop
}
tweets_full <- data.frame(user=character(), name=character(), created_at=character(), id_str=character(), text=character(), retweet_count=character())
tweets_complete <- tweets_full
for(a in 1:nrow(acc_df)) {
user <- as.character(acc_df$twitter_acc[a])
name <- as.character(acc_df$name[a])
max_id <- "999999999999999999"
loop <- 1
error <- 0
repeat {
# Define specific search query
query <- c(include_rts=1, exclude_replies="true", trim_user="true", include_entities="false",
screen_name=user,
count=max_count,
max_id=max_id);
# At first, work with an temporary tweet-DB
current <- twitter_api_call(api_url, query, api_params)
rm(tweets_temp)
tweets_temp <- fromJSON(correctJSON(current))
## START ERROR HANDLING ##
# Empty API output
status <- errorEmptyAPI(tweets_temp)
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
# Contains "error" column
status <- errorErrorColumn(tweets_temp)
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
# Check if error code exists
code <- errorCheckCode(tweets_temp) # 0 if no error
if(code == 34) {  # page does not exist
status <- errorCode34()
if(status == 1) { Sys.sleep(3);error <- error + 1;next}
if(status == 2) {break}
}
if(code == 88) {  # rate limit exceeded
wait <- errorCode88()
Sys.sleep(wait)
next
}
## END ERROR HANDLING ##
# Delete unnecessary columns and add username and real name to dataframe
tweets_temp <- tweets_temp[keep]
tweets_temp <- cbind(user=user, name=name, tweets_temp)
# Now sleep 3 second to dodge 300queries/15min limit
cat("[",a,"/",nrow(acc_df),"] ", sep = "")
cat("User: ",user," in loop: ",loop,". \n", sep = "")
Sys.sleep(2)
if(tweets_full$id_str[nrow(tweets_full)] == tweets_temp$id_str[nrow(tweets_temp)] && nrow(tweets_full) > 0) {
cat("[INFO] Last tweet of temp is last tweet of full. Abort loop and begin with next user.\n")
break
}
## Last loop is reached. Now clear the data frame
#     # Is the last tweet in tweets_temp from 2013?
#     status <- str_detect(tweets_temp$created_at[nrow(tweets_temp)], "2014$")
# Extract year of last tweet in tweets_temp
year_last <- as.numeric(str_extract(tweets_temp$created_at[nrow(tweets_temp)], "\\d{4}$"))
status <- year_last < 2014
if (status) { # Starting when tweet is earlier than 2014 (i.e. 2013, 2012...)
# Is even the first tweet older than 2014?
year_first <- as.numeric(str_extract(tweets_temp$created_at[1], "\\d{4}$"))
status <- year_first < 2014
if(status) {
cat("[INFO] Timeline enhält keinen einzigen aus 2014\n")
}
#       # Delete all tweets other than from 2014
#       old <- 0
#       for(r in 1:nrow(tweets_temp)) {
#         status <- str_detect(tweets_temp$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$")
#         if(!status) {
#           old <- nrow(tweets_temp)
#           cat("[INFO] Timeline enhält keinen einzigen aus 2014\n")
#         }
#
#         # delete all lines which are older than 2014
#         tweets_temp <- head(tweets_temp, -old)
#       }
#       rm(old)
tweets_full <- insertRow(tweets_full, tweets_temp)
#rm(tweets_temp)
break  # End loop because 2013 is reached
}
# The last tweet is newer or equal 2014, so we need another loop
else {
# Setting max_id to gather next 200 tweets
max_id <- tweets_temp$id_str[nrow(tweets_temp)]
loop <- loop + 1  # just for stats
tweets_full <- insertRow(tweets_full, tweets_temp)
#rm(tweets_temp)
}
} # /repeat
tweets_complete <- insertRow(tweets_complete, tweets_full)
tweets_full <- head(tweets_full, -nrow(tweets_full)) # Empty tweets_full
cat("User:",user,"finished after",loop,"loops. Total Tweets now:",nrow(tweets_complete),"\n")
write.csv(tweets_complete, "tweets_complete.csv")
# Every tweet from 2014 or newer from user[a] is downloaded. Now next user in for-loop
}
rm(a, code, current, error, loop, max_id, name, query, r, status, user, wait, tweets_full, tweets_temp)
rm(a, code, current, error, loop, max_id, max_count, year_first, year_last, name, query, status, user, wait, tweets_full, tweets_temp)
rm(year)
save(tweets_complete, file="tweets_complete.RData")
tweets_complete2 <- tweets_complete
View(tweets_complete2)
tweets <- tweets_complete[!duplicated(tweets_complete), ]
tweets <- na.omit(tweets)
save(tweets, file="tweets.RData")
rm(tweets_complete2)
Sys.setlocale("LC_TIME", "C")
tweets$created_at <- as.POSIXct(tweets$created_at, format = "%a %b %d %H:%M:%S %z %Y")
tweets <- tweets[order(tweets$created_at), ]
head(tweets)
delrow <- NULL
for(r in 1:nrow(tweets)) {
if(format(tweets$created_at[r], "%Y") != "2014") {
delrow <- c(delrow, r)
}
if(format(tweets$created_at[r], "%Y") == "2014") {
break
}
}
delrow <- NULL
pb <- txtProgressBar(min = 0, max = total, style = 3)
for(r in 1:nrow(tweets)) {
setTxtProgressBar(pb, r)
if(format(tweets$created_at[r], "%Y") != "2014") {
delrow <- c(delrow, r)
}
if(format(tweets$created_at[r], "%Y") == "2014") {
break
}
}
pb <- txtProgressBar(min = 0, max = total, style = 3)
pb <- txtProgressBar(min = 0, max = nrow(tweets), style = 3)
for(r in 1:nrow(tweets)) {
setTxtProgressBar(pb, r)
if(format(tweets$created_at[r], "%Y") != "2014") {
delrow <- c(delrow, r)
}
if(format(tweets$created_at[r], "%Y") == "2014") {
break
}
}
tweets <- tweets[-delrow, ]
rm(delrow, r)
summary(tweets)
tweets$created_at[140000]
tweets$created_at[130000]
tweets$created_at[1]
tweets$created_at[2]
tweets$created_at[100]
tweets$created_at[141086]
delrow
delrow <- NULL
for(r in 1:nrow(tweets)) {
if(format(tweets$created_at[r], "%Y") != "2014") {
delrow <- c(delrow, r)
}
if(format(tweets$created_at[r], "%Y") == "2014") {
break
}
}
pb <- txtProgressBar(min = 0, max = nrow(tweets), style = 3)
for(r in 1:nrow(tweets)) {
if(format(tweets$created_at[r], "%Y") != "2014") {
delrow <- c(delrow, r)
}
setTxtProgressBar(pb, r)
}
tweets <- tweets[-delrow, ]
tweets$created_at[137800]
tweets$created_at[137876]
rm(delrow, r)
rm(pb)
tweets$created_at <- format(tweets$created_at, "%Y-%m-%d")
tweets$created_at[137876]
save(tweets, file="tweets.RData")
readLines("twitter-api-consumerkey.txt")
api_params2 <- api_params
readLines("twitter-api-consumerkey.txt")
readLines("twitter-api-consumerkey.txt")[2]
readLines("twitter-api-credentials.txt")[2]
readLines("twitter-api-credentials.txt")[1]
api_params <- c(
"oauth_consumer_key"     = readLines("twitter-api-credentials.txt")[2],
"oauth_nonce"            = NA,
"oauth_signature_method" = "HMAC-SHA1",
"oauth_timestamp"        = NA,
"oauth_token"            = readLines("twitter-api-credentials.txt")[4],
"oauth_version"          = "1.0",
"consumer_secret"        = readLines("twitter-api-credentials.txt")[3],
"oauth_token_secret"     = readLines("twitter-api-credentials.txt")[5]
)
api_params
api_params2
rm(tweets_complete)
rm(api_params2)
source("issuecomp-functions.R")
source("issuecomp-functions.R")
setwd("~/Dokumente/Uni/Aktuell/BA-Arbeit/uni-ba-issuecomp")
require(lubridate)
require(XML)
require(ggplot2)
require(reshape2)
date_start <- as.Date("2014-01-01")
date_end <- as.Date("2014-12-01")
drange <- as.integer(date_end - date_start)
drange <- date_start + days(0:drange)
issues <- data.frame(date = drange)
View(issues)
date_start <- as.Date("2014-01-01")
date_end <- as.Date("2014-12-31")
drange <- as.integer(date_end - date_start)
drange <- date_start + days(0:drange)
issues <- data.frame(date = drange)
View(issues)
issuelist <- xmlToList("issues.xml")
issueheads <- names(issuelist)
issues[issueheads] <- 0
View(issues)