commit ecd3d5214da5d1b6fa808f0315f63887b95a56a8 Author: mxmehl Date: Fri Nov 28 18:05:12 2014 +0100 initial commit v1.0 diff --git a/Abbildungen/abbildung1mehl.pdf b/Abbildungen/abbildung1mehl.pdf new file mode 100644 index 0000000..263a93d Binary files /dev/null and b/Abbildungen/abbildung1mehl.pdf differ diff --git a/Abbildungen/abbildung1mehl.png b/Abbildungen/abbildung1mehl.png new file mode 100644 index 0000000..03dab33 Binary files /dev/null and b/Abbildungen/abbildung1mehl.png differ diff --git a/Abbildungen/abbildung2mehl.pdf b/Abbildungen/abbildung2mehl.pdf new file mode 100644 index 0000000..0322fd2 Binary files /dev/null and b/Abbildungen/abbildung2mehl.pdf differ diff --git a/Abbildungen/abbildung2mehl.png b/Abbildungen/abbildung2mehl.png new file mode 100644 index 0000000..a86fca6 Binary files /dev/null and b/Abbildungen/abbildung2mehl.png differ diff --git a/Abbildungen/abbildung3mehl.pdf b/Abbildungen/abbildung3mehl.pdf new file mode 100644 index 0000000..4557b80 Binary files /dev/null and b/Abbildungen/abbildung3mehl.pdf differ diff --git a/Abbildungen/abbildung3mehl.png b/Abbildungen/abbildung3mehl.png new file mode 100644 index 0000000..839d259 Binary files /dev/null and b/Abbildungen/abbildung3mehl.png differ diff --git a/Abbildungen/abbildung4mehl.pdf b/Abbildungen/abbildung4mehl.pdf new file mode 100644 index 0000000..8d254fd Binary files /dev/null and b/Abbildungen/abbildung4mehl.pdf differ diff --git a/Abbildungen/abbildung4mehl.png b/Abbildungen/abbildung4mehl.png new file mode 100644 index 0000000..1e72623 Binary files /dev/null and b/Abbildungen/abbildung4mehl.png differ diff --git a/Abbildungen/abbildung5mehl.pdf b/Abbildungen/abbildung5mehl.pdf new file mode 100644 index 0000000..ca1196b Binary files /dev/null and b/Abbildungen/abbildung5mehl.pdf differ diff --git a/Abbildungen/abbildung5mehl.png b/Abbildungen/abbildung5mehl.png new file mode 100644 index 0000000..b19c210 Binary files /dev/null and b/Abbildungen/abbildung5mehl.png differ diff --git a/Blogartikel 2 - Mehl.pdf b/Blogartikel 2 - Mehl.pdf new file mode 100644 index 0000000..2e2c24b Binary files /dev/null and b/Blogartikel 2 - Mehl.pdf differ diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..94a9ed0 --- /dev/null +++ b/LICENSE @@ -0,0 +1,674 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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Interpretation of Sections 15 and 16. + + If the disclaimer of warranty and limitation of liability provided +above cannot be given local legal effect according to their terms, +reviewing courts shall apply local law that most closely approximates +an absolute waiver of all civil liability in connection with the +Program, unless a warranty or assumption of liability accompanies a +copy of the Program in return for a fee. + + END OF TERMS AND CONDITIONS + + How to Apply These Terms to Your New Programs + + If you develop a new program, and you want it to be of the greatest +possible use to the public, the best way to achieve this is to make it +free software which everyone can redistribute and change under these terms. + + To do so, attach the following notices to the program. It is safest +to attach them to the start of each source file to most effectively +state the exclusion of warranty; and each file should have at least +the "copyright" line and a pointer to where the full notice is found. + + + Copyright (C) + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . + +Also add information on how to contact you by electronic and paper mail. + + If the program does terminal interaction, make it output a short +notice like this when it starts in an interactive mode: + + Copyright (C) + This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w' and `show c' should show the appropriate +parts of the General Public License. Of course, your program's commands +might be different; for a GUI interface, you would use an "about box". + + You should also get your employer (if you work as a programmer) or school, +if any, to sign a "copyright disclaimer" for the program, if necessary. +For more information on this, and how to apply and follow the GNU GPL, see +. + + The GNU General Public License does not permit incorporating your program +into proprietary programs. If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/R-Code/backup_cl.RData b/R-Code/backup_cl.RData new file mode 100644 index 0000000..22cb3c4 Binary files /dev/null and b/R-Code/backup_cl.RData differ diff --git a/R-Code/backup_headlines.RData b/R-Code/backup_headlines.RData new file mode 100644 index 0000000..7f0b1fa Binary files /dev/null and b/R-Code/backup_headlines.RData differ diff --git a/R-Code/newsfokus-1-countrylist.R b/R-Code/newsfokus-1-countrylist.R new file mode 100644 index 0000000..3992fbc --- /dev/null +++ b/R-Code/newsfokus-1-countrylist.R @@ -0,0 +1,46 @@ +require(stringr) +require(dplyr) +require(XML) + +setwd(dir="~/Dokumente/Uni/Aktuell/Datenerhebung WWW/Blogartikel 2 - Newsfokus") + +clist_url <- "http://de.wikipedia.org/wiki/ISO-3166-1-Kodierliste" +clist_tbl <- readHTMLTable(clist_url, encoding = "UTF-8")[[1]] +names(clist_tbl) <- c("name", "code", "code-3", "code-num", "tld", "ioc", "code-2", "un") + +clist <- data.frame(clist_tbl, stringsAsFactors = FALSE) +keep <- c("code", "name") +clist <- clist[keep] +clist$code <- as.character.factor(clist$code) +clist$name <- as.character.factor(clist$name) +rm(keep) + +# Cleaning table from headlines, annotations and brackets +for (i in 1:nrow(clist)) { + name <- as.character(clist$name[i]) + status <- str_detect(name, "!!") + if (status) { + clist <- clist[-i,] + } + rm(i, name, status) +} + +cleanBrackets <- function(string) { + string <- str_replace(string, "\\[.*\\]", "") + string <- str_replace(string, "\\(.*\\)", "") + string <- str_replace(string, ".+!", "") + string <- str_trim(string) + return(string) +} + +for (i in 1:nrow(clist)) { + name <- as.character(clist$name[i]) + code <- as.character(clist$code[i]) + clist$name[i] <- cleanBrackets(name) + clist$code[i] <- cleanBrackets(code) + rm(i, name, code) +} + +write.table(clist, "newsfokus-countrylist.txt", sep=";", row.names=FALSE, col.names=FALSE) + +# Diese exportierte Länderliste wird noch manuell bearbeitet, siehe "newsfokus-countrylist-manualchanges.txt" diff --git a/R-Code/newsfokus-2-scraping.R b/R-Code/newsfokus-2-scraping.R new file mode 100644 index 0000000..7e80a8f --- /dev/null +++ b/R-Code/newsfokus-2-scraping.R @@ -0,0 +1,185 @@ +require(XML) +require(RCurl) +require(stringr) + + + +setwd("~/Dokumente/Uni/Aktuell/Datenerhebung WWW/Blogartikel 2 - Newsfokus/") +# Import manually edited country list +cl <- read.csv("newsfokus-countrylist.txt", sep = ";", header = FALSE) +names(cl) <- c("code", "name") + + +# FUNCTIONS --------------------------------------------------------------- + +source("newsfokus-functions.R") + + +# PREPARATIONS ------------------------------------------------------------ + +# Generate all month.year combinations since January 2000 +tspans <- NULL +for (y in 2000:2014) { + for (m in 01:12) { + if (length(tspans) == 0) { + tspans <- str_c(m,".",y) + } + else { + tspans <- c(tspans, str_c(m,".",y)) + } + } + rm(y, m) +} + +# # All combinations mmmYYYY (not used yet) +# years <- 2000:2014 # 15 +# months <- month.abb +# no <- 0 +# comb <- NULL +# for (m in 1:12) { +# for (y in 1:15) { +# no <- no + 1 +# comb[no] <- str_c(months[m],years[y]) +# } +# } +# rm(years, months, m, y, no) + +# Remove future/incomplete months +removemonths <- c(9.2014, 10.2014, 11.2014, 12.2014) +tspans <- tspans [! tspans %in% removemonths] +rm(removemonths) + + +# Create new columns for every month and set the column names accordingly +cl[sprintf("%s", tspans)] <- 0 + +# Copy data frame for headlines +headlines <- cl + +# Set curl handle for friendly scraping +handle <- getCurlHandle(httpheader = list(from = "max.mehl@uni.kn", + 'user-agent' = str_c(R.version$version.string) + ) + ) + + +# SCRAPING ALL THE NEWS \o/ ---------------------------------------------- + +# Das Prozedere ist folgendes: +# 1. Erstelle die URL je nach Zeitspanne und wiederhole das für jede existierende Seite (meist über 100) +# - Es gibt eine Fehlermeldung auf der Suchseite, wenn keine Ergebnisse mehr vorhanden sind +# 2. Lade Seite herunter und parse sie +# - Nicht, wenn sie schon vorhanden ist, um Bandbreite zu sparen +# 3. Suche nach Auftauchen von Ländernamen +# 3a. Wenn ja, dann zähle jeweiligen Eintrag im DF um 1 hoch +# - nur ein Auftauchen des Landes in einem Artikel wird gezählt +# (es gibt für einzelne Ländercodes mehrere Schreibweisen) + +stat_news_all <- 0 +stat_news_pos <- 0 +stat_pages <- 0 +# This loop does the scraping, searching and indexing of each month and country +# !!! Beware: It takes around 24 hours to finish for 1.2000 - 8.2014! Load backup_cl.RData (and optionally backup_headlines.RData) to skip this step +for (i in 3:ncol(cl)) { + tspan <- names(cl)[i] + + # Create folder for downloaded HTML files + dir.create(str_c("materials/",tspan), showWarnings = FALSE, recursive = TRUE) + + days <- getDays(i, cl) + # Generate the month's base url + baseurl <- str_c("http://www.spiegel.de/suche/index.html?suchbegriff=+&quellenGroup=SPOX&suchbereich=kopftext&fromDate=1.", tspan, "&toDate=", days, ".", tspan, "&offsets=999999&pageNumber=") + + # In every loop we start with page 1 again + page <- 1 + + # Now expand the URL by the page number UNTIL there's an error page + repeat { + cat("\n--> Processing page", page, "of timespan", tspan, "\n") + + url <- str_c(baseurl, page) + dest <- str_c("materials/",tspan,"/",tspan,"-",page,".html") + url_parsed <- dlParsePage(url, dest) + + status <- unlist(xpathSApply(url_parsed, "//h3[contains(text(), 'Ihre Suche ergab keinen Treffer')]")) + if (! is.null(status)) { + # If there's an error page, there're no further articles. Skip this loop and begin with next month + cat("Letzte Seite erreicht:", url, "\n") + break + } + + # Page is valid, now split in single articles and search for countries in each title and teaser + headline <- xpathSApply(url_parsed, "//div[@class='search-teaser']//span[@class='headline']", xmlValue) + teaser <- xpathSApply(url_parsed, "//div[@class='search-teaser']/p", xmlValue) + url_arts <- xpathSApply(url_parsed, "//div[@class='search-teaser']/a", xmlGetAttr, "href") + url_short <- "" + # Combine headline and teaser to make it easier to search + teaser <- str_c(headline, teaser, sep=" ") + if (length(teaser) == 0) { + errormsg <- str_c("Probably 500 error at: ", tspan,"-",page) + write(errormsg, "scraping-errors.log", append = TRUE) + rm(errormsg) + } + else { + # Analyse every single teaser/headline combination + for (t in 1:length(teaser)) { + yet <- "" # Did the country already appear in the article? Empty with each loop + string <- teaser[t] + for (c in 1:nrow(cl)) { + name <- as.character(cl$name[c]) # Name of the county to detect in the teaser + status <- str_detect(tolower(string), tolower(name)) # Does the country's name appear in the teaser? + + if (status) { # yes + code <- getCode(c, cl$code) + + cat("The string contains news from:", code, "\n") + + # We only want to count a country once even if it appears multiple times in an article + already <- str_detect(yet, code) # Did the country already appear? + if (!already) { # no + yet <- str_c(yet, code, sep=" ") + cl[c , tspan] <- cl[c , tspan] + 1 # Count +1 to the number of appearances in the data frame + + # Save headlines + links to a different data frame + url_short[t] <- str_extract(url_arts[t], ".+/") + url_short[t] <- str_c(url_short[t], str_extract(url_arts[t], "a\\-\\d+\\.html")) + new_headline_entry <- str_c(headline[t], " (", url_short[t], ")") + if (headlines[c , tspan] == 0) { + headlines[c , tspan] <- new_headline_entry + } + else { + headlines[c , tspan] <- str_c(headlines[c , tspan], "\n", new_headline_entry) + } + + } + rm(code, already) + stat_news_pos <- stat_news_pos + 1 + } + rm(c, name, status) + } + rm(t, yet, string) + stat_news_all <- stat_news_all +1 + } + } + + # Go to the next page + page <- page + 1 + stat_pages <- stat_pages + 1 + } + rm(i, tspan, days, baseurl, page, url, url_parsed, status, teaser, headline, dest, url_arts, url_short, new_headline_entry) + # Backup all data after each month + write.csv(cl, "backup_cl.csv") + write.csv(headlines, "backup_headlines.csv") + save(cl, file="backup_cl.RData") + save(headlines, file="backup_headlines.RData") +} +# End of huge for-loop + + +# Final Backup +write.csv(cl, "backup_cl.csv") +write.csv(headlines, "backup_headlines.csv") +save(cl, file="backup_cl.RData") +save(headlines, file="backup_headlines.RData") + + diff --git a/R-Code/newsfokus-3-analysis.R b/R-Code/newsfokus-3-analysis.R new file mode 100644 index 0000000..77927a9 --- /dev/null +++ b/R-Code/newsfokus-3-analysis.R @@ -0,0 +1,264 @@ +require(plyr) +require(dplyr) +require(stringr) + + +# PREPARATIONS ------------------------------------------------------------ + + +no <- 0 +for (r in 1:nrow(cl)) { + for (c in 3:ncol(cl)) { + no <- no + as.numeric(cl[r,c]) + } +} +cat("Sum of country news entries:",no) +rm(r,c,no) + +# Save old cl-dataframe for next steps +cl_bak <- cl + +# Merge appearances for same country code (but different name) +cl <- ddply(cl,"code",numcolwise(sum)) +target <- which(names(cl) == 'code')[1] +cl <- cbind(cl[,1:target,drop=F], data.frame(name="PLACEHOLDER"), cl[,(target+1):length(cl),drop=F]) +rm(target) +cl$name <- "bla" + +# Now choose names for the according codes (first fits) +for (r in 1:nrow(cl)) { + code <- as.character(cl$code[r]) + code <- namibiaBug(code) + r2 <- 1 + + repeat { + code2 <- as.character(cl_bak$code[r2]) + code2 <- namibiaBug(code2) + + if (code2 == code) { + name <- as.character(cl_bak$name[r2]) + cl$name[r] <- name + break + } + else { + r2 <- r2 + 1 + } + } + rm(r, r2, code, code2, name) +} + + +# Summarize all counts for each country +cl_stats <- cl[,1:2] +cl_stats["overall"] <- 0 +overall <- NULL +for (r in 1:nrow(cl)) { + overall[r] <- 0 + for (c in 3:ncol(cl)) { + overall[r] <- overall[r] + as.numeric(cl[r,c]) + } + cl_stats$overall[r] <- overall[r] +} +rm(overall, r, c) + + +# # If we would want the overall-counter in cl +# cl["overall"] <- 0 +# cl$overall <- cl_stats$overall + + +# # Get all names for one country code (if there are multiple) +# for (r in 1:nrow(cl)) { +# name <- NULL +# no <- 0 +# code <- as.character(cl$code[r]) +# code <- namibiaBug(code) +# r2 <- 1 +# repeat { +# if (r2 > nrow(cl_bak)) { +# break # only end if no next row +# } +# code2 <- as.character(cl_bak$code[r2]) +# code2 <- namibiaBug(code2) +# if (code2 == code) { +# no <- no + 1 +# name[no] <- as.character(cl_bak$name[r2]) +# r2 <- r2 + 1 +# } +# else { +# r2 <- r2 + 1 +# } +# } +# if (length(name) > 1) { +# cat("For",code,"there are", no, "names:", name, "\n") +# } +# rm(r, name, no, code, r2, code2) +# } + +# Old dataframe not needed anymore +rm(cl_bak) + + +# Calculate the total and average news entries for each year +years <- 2000:2014 +# Search string for str_detect for every year +year_str <- sprintf("^\\d{1,2}\\.%s", years) + +for (r in 1:nrow(cl)) { + total <- 0 + average <- 0 + for (y in 1:length(years)) { + months <- 0 + for (c in 1:ncol(cl)) { + if (str_detect(names(cl)[c], year_str[y])) { + total <- total + as.numeric(cl[r,c]) + months <- months + 1 + } + } + colnametotal <- str_c(years[y],"-total") + colnameaverg <- str_c(years[y],"-averg") + average <- round(total / months, 4) + cl_stats[r, colnametotal] <- total + cl_stats[r, colnameaverg] <- average + total <- 0 + average <- 0 + } + rm(r, total, average, y, months, c, colnametotal, colnameaverg) +} +rm(years, year_str) + + + + +# IDENTIFY SURPRISING NEWSFOCUS ------------------------------------------- + + +# Land war 3x öfter genannt als im Monat davor, aber mehr als 50x +no <- 0 +for (c in 4:ncol(cl)) { # starting 1 month later + for (r in 1:nrow(cl)) { + month <- names(cl)[c] + + # Conditions to fulfill + status1 <- cl[r,c] > 3 * cl[r,c-1] + status2 <- cl[r,c] > 50 + + if (status1 && status2) { + no <- no + 1 + cat("[",no,"] ",as.character(cl$code[r]),": 3x m-1 && >50 in: ", month,"\n", sep = "") + } + } + rm(r,c,month,status1,status2) +} +rm(no) + + +# Land wurde in einem Monat 3x öfter als im Jahresdurchschnitt genannt +no <- 0 +for (c in 3:ncol(cl)) { + for (r in 1:nrow(cl)) { + month <- names(cl)[c] + year <- str_extract(month, "\\d{4}") + averg <- str_c(year,"-averg") + averg <- cl_stats[r,averg] + + # Conditions to fulfill + status1 <- cl[r,c] > 3 * averg + status2 <- cl[r,c] > 50 + + if (status1 && status2) { + no <- no + 1 + cat("[",no,"] ",as.character(cl$code[r]),": 3x year average && >50 ", month,"\n", sep = "") } + } + rm(r,c,month,year,averg,status1,status2) +} +rm(no) + +# Final method: Land in einem Monat öfter genannt als alle 3 Monate davor zusammen +cl_supfoc_mon <- data.frame(code=NA,name=NA) +cl_supfoc_mon[sprintf("%s", tspans)] <- 0 +no <- 0 +for (c in 6:ncol(cl)) { + for (r in 1:nrow(cl)) { + month <- names(cl)[c] + code <- as.character(cl$code[r]) + name <- as.character(cl$name[r]) + + # Conditions to fulfill + status1 <- cl[r,c] > cl[r,c-1]+cl[r,c-2]+cl[r,c-3] + status2 <- cl[r,c] > 50 + + if (status1 && status2) { + no <- no + 1 + cl_supfoc_mon[no, "code"] <- code + cl_supfoc_mon$name[no] <- name + #if (is.null(cl_supfoc_mon[no, month])) { cl_supfoc_mon[no, month] <- 0} + #cl_supfoc_mon[no, month] <- cl_supfoc_mon[no, month] + 1 + cl_supfoc_mon[no, month] <- 1 + cat("[",no,"] ",as.character(cl$code[r]),": >m-(1:3) && >50 ", month,"\n", sep = "") + } + } + rm(r,c,month,status1,status2) +} +rm(no, code, name) + +# Clean cl_supfoc_mon: Replace NAs by 0, and sum up multiple appeared countries +cl_supfoc_mon[is.na(cl_supfoc_mon)] <- 0 +cl_supfoc_mon <- ddply(cl_supfoc_mon,c("code", "name"),numcolwise(sum)) + +# Delete all month-columns with 0 surprising events +cl_supfoc_only_mon <- removeZeroMonths(cl_supfoc_mon, 3, ncol(cl_supfoc_mon)) + + + + +# Get total surprising newsfocuses for each country +cl_supfoc_total <- data.frame(code=NA, name=NA, total=NA) +for (r in 1:nrow(cl_supfoc_mon)) { + total <- 0 + cl_supfoc_total[r,"code"] <- as.character(cl_supfoc_mon$code[r]) + cl_supfoc_total[r,"name"] <- as.character(cl_supfoc_mon$name[r]) + for (c in 3:ncol(cl_supfoc_mon)) { + total <- total + as.numeric(cl_supfoc_mon[r,c]) + } + cl_supfoc_total[r,"total"] <- total +} +rm(r, total, c) + + + + +# Total highlights per month + turn around table for graphs +cl_supfoc_mon["highlight"] <- 1 +cl_supfoc_turn_mon <- ddply(cl_supfoc_mon,"highlight", numcolwise(sum)) +cl_supfoc_mon$highlight <- NULL +cl_supfoc_turn_mon$highlight <- NULL +cl_supfoc_turn_mon <- data.frame(month = names(cl_supfoc_turn_mon), highs = as.numeric(cl_supfoc_turn_mon[1,])) +# Convert %d.%y to valid date class +months <- NULL +for (m in 1:length(tspans)) { + dates <- str_c("15.",tspans[m]) + months[m] <- dates +} +rm(m, dates) +cl_supfoc_turn_mon$month <- as.Date(months, format = "%d.%m.%Y") +rm(months) + +# Delete all month-rows with 0 surprising events +cl_supfoc_turn_only_mon <- cl_supfoc_turn_mon[!cl_supfoc_turn_mon$highs == 0,] +rownames(cl_supfoc_turn_only_mon) <- NULL + + + + + + +# # Replace 0s by NAs +# for (r in 1:180) { +# if (! is.na(cl_total2$highs[r])) { +# if (cl_total2$highs[r] == 0) { +# cl_total2$highs[r] <- NA +# } +# } +# } + diff --git a/R-Code/newsfokus-4-visual.R b/R-Code/newsfokus-4-visual.R new file mode 100644 index 0000000..5b00c24 --- /dev/null +++ b/R-Code/newsfokus-4-visual.R @@ -0,0 +1,80 @@ +require(rworldmap) +require(ggplot2) + +theCountries <- c("DE", "US", "BR") +# These are the ISO3 names of the countries you'd like to plot in red + +malDF <- data.frame(country = c("DE", "US", "BR", "ZA"), malaria = c(2000, 2001, 2002, 2002), news = c(2, 3, 0, 1)) +# malDF is a data.frame with the ISO3 country names plus a variable to +# merge to the map data + +malMap <- joinCountryData2Map(malDF, joinCode = "ISO2", nameJoinColumn = "country") +# This will join your malDF data.frame to the country map data + +mapCountryData(malMap, nameColumnToPlot="malaria", catMethod = "categorical", missingCountryCol = gray(.8)) +# And this will plot it, with the trick that the color palette's first +# color is red + + + +# Absolute Frequ Newsfocus Map -------------------------------------------- + + +# # Absolute Häufigkeiten der Highlights mit Bubbles +# malMap <- joinCountryData2Map(cl_supfoc_total, joinCode = "ISO2", nameJoinColumn = "code") +# mapBubbles( dF=malMap, nameZSize="total",nameZColour="GEO3major", +# colourPalette=c("black", "yellow", "blue", "orange", "red", "white", "green"), +# oceanCol="lightblue", +# landCol="wheat", +# fill=TRUE, +# symbolSize=0.5, +# pch=21) + +# Absolute Newfokus Häufigkeiten Welt: +absMap <- joinCountryData2Map(cl_supfoc_total, joinCode = "ISO2", nameJoinColumn = "code", verbose=TRUE) +mapCountryData(absMap, nameColumnToPlot="total", catMethod="fixedWidth", + numCats=5, + mapTitle="Anzahl Überraschungsfokusse weltweit", + oceanCol="lightblue", + missingCountryCol=gray(.9) + ) + +# Absolute Newfokus Häufigkeiten EU-Asien-Nordafrika: +mapCountryData(absMap, nameColumnToPlot="total", catMethod="fixedWidth", + numCats=5, + mapTitle="Anzahl Überraschungsfokusse Nordafrika und Asien", + oceanCol="lightblue", + missingCountryCol=gray(.9), + xlim=c(10,140), + ylim=c(30,70) + ) + + + +# Development Newsfocus over time ----------------------------------------- + + +# Entwicklung der Surprising Focuses über die Jahre +cc <- ggplot(cl_supfoc_turn_mon, aes(month,highs)) +cc <- cc + geom_histogram(fill="steelblue", stat="identity") +cc <- cc + stat_smooth(size=1,colour="red",method="loess", se=FALSE) +cc <- cc + ggtitle("Zeitliche Entwicklung von plötzlichen Medienfokussen") + xlab("Einzelne Monate") + ylab("Plötzliche Medienfokusse") +cc + + +# Beispiel1: Jährliche Durchschnittsanzahl 2000-2014 der Nachrichten über Syrien +yearspan <- 2000:2014 +avergdf <- getAverages(df = cl_stats, codecol = "code", code = "SY", yearspan = yearspan) + +averg <- ggplot(data = avergdf, aes(x = year, y=averg)) +averg + geom_line() + ggtitle("Durchschnittliche Nachrichten pro Jahr über Syrien") + xlab("Jahre") + ylab("Durchschnittliche Nachrichten") + +# Beispiel2: Jährliche Durchschnittsanzahl 2000-2014 der Nachrichten über Israel +yearspan <- 2000:2014 +avergdf <- getAverages(df = cl_stats, codecol = "code", code = "IL", yearspan = yearspan) + +averg <- ggplot(data = avergdf, aes(x = year, y=averg)) +averg + geom_line() + ggtitle("Durchschnittliche Nachrichten pro Jahr über Israel") + xlab("Jahre") + ylab("Durchschnittliche Nachrichten") + + + diff --git a/R-Code/newsfokus-countrylist-manualchanges.txt b/R-Code/newsfokus-countrylist-manualchanges.txt new file mode 100644 index 0000000..f417195 --- /dev/null +++ b/R-Code/newsfokus-countrylist-manualchanges.txt @@ -0,0 +1,38 @@ +"Nordkorea";"KP" +"Südkorea";"KR" +"Zaire";"CD" +"Großbritannien";"GB" +"England";"GB" +"Russland";"RU" +"Palästina";"PS" +"Gazastreifen";"PS" +"Burma";"MM" +"Moldau";"MW" +"Laos";"LA" +"Kosovo";"RS" +"Kongo";"CD" +"Kongo-Brazzaville";"CG" +"Iran";"IR" +"Isle of Man";"IM" +"DDR";"DD" +"Elfenbeinküste";"CI" +"China";"CN" +"Weißrussland";"BY" +"Antarktis";"AQ" +"Krim";"UA" +"UdSSR";"RU" +"USA";"US" +"BRD";"DE" +"Nordirland";"IE" +"Nordzypern";"CY" +"Syrien";"SY" +"VA";"Vatikan" +"TZ";"Tansania" +"EA";"Ceuta" +"EA";"Melilla" + + +"ENTFERNT Neutrale Zone";"NT" +"ENTFERNT Europäische Gemeinschaft";"CE" +"ENTFERNT Europäische Union";"EU" +"ENTFERNT Burma";"BU" diff --git a/R-Code/newsfokus-countrylist.txt b/R-Code/newsfokus-countrylist.txt new file mode 100644 index 0000000..143a4a8 --- /dev/null +++ b/R-Code/newsfokus-countrylist.txt @@ -0,0 +1,295 @@ +"AC";"Ascension" +"AD";"Andorra" +"AE";"Vereinigte Arabische Emirate" +"AF";"Afghanistan" +"AG";"Antigua und Barbuda" +"AI";"Anguilla" +"AL";"Albanien" +"AM";"Armenien" +"AN";"Niederländische Antillen" +"AO";"Angola" +"AQ";"Antarktis" +"AQ";"Antarktika" +"AR";"Argentinien" +"AS";"Amerikanisch-Samoa" +"AT";"Österreich" +"AU";"Australien" +"AW";"Aruba" +"AX";"Åland" +"AZ";"Aserbaidschan" +"BA";"Bosnien und Herzegowina" +"BB";"Barbados" +"BD";"Bangladesch" +"BE";"Belgien" +"BF";"Burkina Faso" +"BG";"Bulgarien" +"BH";"Bahrain" +"BI";"Burundi" +"BJ";"Benin" +"BL";"Saint-Barthélemy" +"BM";"Bermuda" +"BN";"Brunei Darussalam" +"BO";"Bolivien" +"BQ";"Bonaire, Sint Eustatius und Saba" +"BR";"Brasilien" +"BS";"Bahamas" +"BT";"Bhutan" +"BV";"Bouvetinsel" +"BW";"Botswana" +"BY";"Belarus" +"BY";"Weißrussland" +"BZ";"Belize" +"CA";"Kanada" +"CC";"Kokosinseln" +"CD";"Demokratische Republik Kongo" +"CD";"Kongo, Demokratische Republik" +"CD";"Kongo" +"CD";"Zaire" +"CF";"Zentralafrikanische Republik" +"CG";"Republik Kongo" +"CG";"Kongo-Brazzaville" +"CH";"Schweiz" +"CI";"Elfenbeinküste" +"CI";"Côte d’Ivoire" +"CK";"Cookinseln" +"CL";"Chile" +"CM";"Kamerun" +"CN";"China" +"CN";"China, Volksrepublik" +"CO";"Kolumbien" +"CP";"Clipperton" +"CR";"Costa Rica" +"CS";"Tschechoslowakei" +"CS";"Serbien und Montenegro" +"CU";"Kuba" +"CV";"Kap Verde" +"CW";"Curaçao" +"CX";"Weihnachtsinsel" +"CY";"Zypern" +"CY";"Nordzypern" +"CZ";"Tschechische Republik" +"DD";"DDR" +"DD";"Deutsche Demokratische Republik" +"DE";"Deutschland" +"DE";"BRD" +"DG";"Diego Garcia" +"DJ";"Dschibuti" +"DK";"Dänemark" +"DM";"Dominica" +"DO";"Dominikanische Republik" +"DZ";"Algerien" +"EA";"Ceuta, Melilla" +"EA";"Ceuta" +"EA";"Melilla" +"EC";"Ecuador" +"EE";"Estland" +"EG";"Ägypten" +"EH";"Westsahara" +"ER";"Eritrea" +"ES";"Spanien" +"ET";"Äthiopien" +"FI";"Finnland" +"FJ";"Fidschi" +"FK";"Falklandinseln" +"FM";"Mikronesien" +"FO";"Färöer" +"FR";"Frankreich" +"FX";"Frankreich, France métropolitaine" +"GA";"Gabun" +"GB";"Großbritannien" +"GB";"England" +"GB";"Vereinigtes Königreich Großbritannien und Nordirland" +"GD";"Grenada" +"GE";"Georgien" +"GF";"Französisch-Guayana" +"GG";"Guernsey" +"GH";"Ghana" +"GI";"Gibraltar" +"GL";"Grönland" +"GM";"Gambia" +"GN";"Guinea" +"GP";"Guadeloupe" +"GQ";"Äquatorialguinea" +"GR";"Griechenland" +"GS";"Südgeorgien und die Südlichen Sandwichinseln" +"GT";"Guatemala" +"GU";"Guam" +"GW";"Guinea-Bissau" +"GY";"Guyana" +"HK";"Hongkong" +"HM";"Heard und McDonaldinseln" +"HN";"Honduras" +"HR";"Kroatien" +"HT";"Haiti" +"HU";"Ungarn" +"IC";"Kanarische Inseln" +"ID";"Indonesien" +"IE";"Irland" +"IE";"Nordirland" +"IL";"Israel" +"IM";"Isle of Man" +"IM";"Insel Man" +"IN";"Indien" +"IO";"Britisches Territorium im Indischen Ozean" +"IQ";"Irak" +"IR";"Iran" +"IR";"Iran, Islamische Republik" +"IS";"Island" +"IT";"Italien" +"JE";"Jersey" +"JM";"Jamaika" +"JO";"Jordanien" +"JP";"Japan" +"KE";"Kenia" +"KG";"Kirgisistan" +"KH";"Kambodscha" +"KI";"Kiribati" +"KM";"Komoren" +"KN";"St. Kitts und Nevis" +"KP";"Nordkorea" +"KP";"Korea, Demokratische Volksrepublik" +"KR";"Südkorea" +"KR";"Korea, Republik" +"KW";"Kuwait" +"KY";"Kaimaninseln" +"KZ";"Kasachstan" +"LA";"Laos" +"LA";"Laos, Demokratische Volksrepublik" +"LB";"Libanon" +"LC";"St. Lucia" +"LI";"Liechtenstein" +"LK";"Sri Lanka" +"LR";"Liberia" +"LS";"Lesotho" +"LT";"Litauen" +"LU";"Luxemburg" +"LV";"Lettland" +"LY";"Libyen" +"MA";"Marokko" +"MC";"Monaco" +"MD";"Moldawien" +"ME";"Montenegro" +"MF";"Saint-Martin" +"MG";"Madagaskar" +"MH";"Marshallinseln" +"MK";"Mazedonien" +"ML";"Mali" +"MM";"Myanmar" +"MM";"Burma" +"MN";"Mongolei" +"MO";"Macao" +"MP";"Nördliche Marianen" +"MQ";"Martinique" +"MR";"Mauretanien" +"MS";"Montserrat" +"MT";"Malta" +"MU";"Mauritius" +"MV";"Malediven" +"MW";"Malawi" +"MW";"Moldau" +"MX";"Mexiko" +"MY";"Malaysia" +"MZ";"Mosambik" +"NA";"Namibia" +"NC";"Neukaledonien" +"NE";"Niger" +"NF";"Norfolkinsel" +"NG";"Nigeria" +"NI";"Nicaragua" +"NL";"Niederlande" +"NO";"Norwegen" +"NP";"Nepal" +"NR";"Nauru" +"NU";"Niue" +"NZ";"Neuseeland" +"OM";"Oman" +"PA";"Panama" +"PE";"Peru" +"PF";"Französisch-Polynesien" +"PG";"Papua-Neuguinea" +"PH";"Philippinen" +"PK";"Pakistan" +"PL";"Polen" +"PM";"Saint-Pierre und Miquelon" +"PN";"Pitcairninseln" +"PR";"Puerto Rico" +"PS";"Staat Palästina" +"PS";"Gazastreifen" +"PS";"Palästina" +"PT";"Portugal" +"PW";"Palau" +"PY";"Paraguay" +"QA";"Katar" +"RE";"Réunion" +"RO";"Rumänien" +"RS";"Serbien" +"RS";"Kosovo" +"RU";"Russland" +"RU";"Russische Föderation" +"RU";"UdSSR" +"RW";"Ruanda" +"SA";"Saudi-Arabien" +"SB";"Salomonen" +"SC";"Seychellen" +"SD";"Sudan" +"SE";"Schweden" +"SG";"Singapur" +"SH";"St. Helena" +"SI";"Slowenien" +"SJ";"Svalbard und Jan Mayen" +"SK";"Slowakei" +"SL";"Sierra Leone" +"SM";"San Marino" +"SN";"Senegal" +"SO";"Somalia" +"SR";"Suriname" +"SS";"Südsudan" +"ST";"São Tomé und Príncipe" +"SV";"El Salvador" +"SX";"Sint Maarten" +"SY";"Syrien" +"SY";"Syrien, Arabische Republik" +"SZ";"Swasiland" +"TA";"Tristan da Cunha" +"TC";"Turks- und Caicosinseln" +"TD";"Tschad" +"TF";"Französische Süd- und Antarktisgebiete" +"TG";"Togo" +"TH";"Thailand" +"TJ";"Tadschikistan" +"TK";"Tokelau" +"TL";"Osttimor" +"TM";"Turkmenistan" +"TN";"Tunesien" +"TO";"Tonga" +"TR";"Türkei" +"TT";"Trinidad und Tobago" +"TV";"Tuvalu" +"TW";"Republik China" +"TZ";"Tansania" +"TZ";"Tansania, Vereinigte Republik" +"UA";"Ukraine" +"UA";"Krim" +"UG";"Uganda" +"UM";"United States Minor Outlying Islands" +"US";"USA" +"US";"Vereinigte Staaten von Amerika" +"UY";"Uruguay" +"UZ";"Usbekistan" +"VA";"Vatikanstadt" +"VA";"Vatikan" +"VC";"St. Vincent und die Grenadinen" +"VE";"Venezuela" +"VG";"Britische Jungferninseln" +"VI";"Amerikanische Jungferninseln" +"VN";"Vietnam" +"VU";"Vanuatu" +"WF";"Wallis und Futuna" +"WS";"Samoa" +"YE";"Jemen" +"YT";"Mayotte" +"YU";"Jugoslawien" +"ZA";"Südafrika" +"ZM";"Sambia" +"ZR";"Zaire" +"ZW";"Simbabwe" diff --git a/R-Code/newsfokus-functions.R b/R-Code/newsfokus-functions.R new file mode 100644 index 0000000..b292355 --- /dev/null +++ b/R-Code/newsfokus-functions.R @@ -0,0 +1,127 @@ +require(stringr) +require(RCurl) + + +dlParsePage <- function(url, dest) { + if (!file.exists(dest)) { + url_curl <- getURL(url, curl=handle) + write(url_curl, dest) + } + parsed <- htmlParse(dest, encoding = "UTF-8") + return(parsed) +} + +# Calculate the number of days in a specific month + # (Important for manipulating the search URL because otherwise there would be articles + # of the NEXT month in the search results if we have a too large time span) +getDays <- function(i, df) { + cur_tspan <- names(df)[i] + cur_m <- as.numeric(str_extract(cur_tspan, "^\\d+\\>")) + cur_y <- as.numeric(str_extract(cur_tspan, "\\d{4}")) + if (cur_m == 12) { + nex_y <- cur_y + 1 + nex_m <- 1 + } + else { + nex_y <- cur_y + nex_m <- cur_m +1 + } + cur_date <- str_c(cur_y, cur_m, "01", sep = "-") + nex_date <- str_c(nex_y, nex_m, "01", sep = "-") + days <- as.numeric(difftime(as.Date(nex_date), as.Date(cur_date))) + return(days) +} + +getCode <- function(i, df) { + # There's a bug with appearances of Namibia, producing NAs instead of "NA" + if (! is.na(as.character(df[i]))) { + code <- as.character(df[i]) # Get the country's code + } + else { + code <- "NA" + } + return(code) +} + +# NAs get converted into "NA" for Namibia +namibiaBug <- function(x) { + if (is.na(x)) {x <- "NA"} + return(x) +} + + +# Get all headlines for a specific country and a specific month +getHeadlines <- function(df, countrycol, descountry, month) { + no <- 0 + news <- NULL + for (r in 1:nrow(df)) { + descountry <- namibiaBug(descountry) + curcountry <- namibiaBug(as.character(df[r,countrycol])) + if (curcountry == descountry) { + no <- no + 1 + news[no] <- as.character(df[r,month]) + } + } + cat(news) +} + + +# Remove months with 0 surprising newsfocuses +removeZeroMonths <- function(df, mincol, maxcol) { + delmonthno <- 0 + delmonth <- NULL + for (c in mincol:maxcol) { + month <- names(df)[c] + no <- 0 + for (r in 1:nrow(df)) { + no <- no + as.numeric(df[r,c]) + } + if (no == 0) { + delmonthno <- delmonthno + 1 + delmonth[delmonthno] <- month + } + } + return(df [! names(df) %in% delmonth]) +} + +# Get countries which produced newsfocuses in a given month +getFocusCountries <- function(df, month) { +exists <- FALSE +for (c in 1:ncol(df)) { + status <- str_detect(month, names(df)[c]) + if (status) { + exists <- TRUE + } +} +if (!exists) { + return(cat(month, "isn't a valid column in given dataframe")) +} +no <- 0 +countries <- NULL + for (r in 1:nrow(df)) { + supfoc <- df[r,month] + if (supfoc > 0) { + no <- no + 1 + countries[no] <- as.character(df[r,"name"]) + } + } + return(countries) +} + +# Get average development of news over a span of years +getAverages <- function(df, codecol, code, yearspan) { + no <- 0 + averg <- NULL + for (r in 1:nrow(df)) { + code <- namibiaBug(code) + curcode <- namibiaBug(df[r,codecol]) + if (curcode == code) { + for (y in yearspan) { + no <- no + 1 + curcol <- str_c(y,"-averg") + averg[no] <- as.numeric(df[r,curcol]) + } + } + } + return(data.frame(year=yearspan, averg=averg)) +}