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bb_graph.R
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# Load libraries
library(tm)
library(igraph)
library(DBI)
library(RSQLite)
library(Hmisc)
library(SnowballC)
# Functions
sqLiteConnect <- function(database, table) {
con <- dbConnect("SQLite", dbname = database)
query <- dbSendQuery(con, paste("SELECT * FROM ", table, ";", sep=""))
result <- fetch(query, n = -1, encoding="utf-8")
dbClearResult(query)
dbDisconnect(con)
return(result)
}
replaceName <- function (text, dictionary) {
for (i in 1:length(dictionary)) {
text <- gsub(dictionary[i],names(dict_names[i]),text)
}
PlainTextDocument(text, id = ID(text), language = Language(text))
}
addPrefix <- function (string, suffix) {
string <- paste(" ",suffix,string," ",sep="")
return(string)
}
extractNameFromUrl <- function (string) {
string <- substr(string,35, nchar(string))
string <- gsub("_"," ", string)
string <- URLdecode(string)
}
# Define source of data
database <- "~/bb_project/breakingbad.sqlite"
# Load tables
raw_character <- sqLiteConnect(database, "character")
raw_scene <- sqLiteConnect(database, "scene")
## Create dictionary of characters ##
character_dictionary <- raw_character
# Invert order to avoid misidentification
character_dictionary$characterId[character_dictionary$characterUrl=="http://breakingbad.wikia.com/wiki/Walter_White"] <- 8
character_dictionary$characterId[character_dictionary$characterUrl=="http://breakingbad.wikia.com/wiki/Walter_White_Jr."] <- 1
# Split the cousins into two records
character_dictionary$characterName[
character_dictionary$characterUrl=="http://breakingbad.wikia.com/wiki/The_Cousins"] <- "Marco Salamanca"
character_dictionary$characterUrl[
character_dictionary$characterName=="Marco Salamanca"] <- "http://breakingbad.wikia.com/wiki/Marco_Salamanca"
character_dictionary <- rbind(character_dictionary,
c(as.character(nrow(character_dictionary)+1),
"http://breakingbad.wikia.com/wiki/Leonel_Salamanca",
"Leonel Salamanca",
format(Sys.time(), "%Y-%m-%d %X")))
# Add first name only to dictionary
character_dictionary_first_name <- character_dictionary
character_dictionary_first_name$characterName <- lapply(character_dictionary_first_name$characterName, first.word)
# Correct for special names
character_dictionary_first_name$characterName[
character_dictionary_first_name$characterUrl=="http://breakingbad.wikia.com/wiki/Walter_White_Jr."] <- "Walter Jr"
character_dictionary_first_name$characterName[
character_dictionary_first_name$characterUrl=="http://breakingbad.wikia.com/wiki/Don_Eladio"] <- "Don Eladio"
character_dictionary_first_name$characterName[
character_dictionary_first_name$characterUrl=="http://breakingbad.wikia.com/wiki/George_Merkert"] <- "George"
character_dictionary <- rbind(character_dictionary,character_dictionary_first_name)
rm(character_dictionary_first_name)
# Add nick name to dictionary
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Walter_White_Jr.",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Walter_White_Jr.",
"Walt Jr","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Walter_White",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Walter_White",
"Walt","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Walter_White",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Walter_White",
"Walts","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Jesse_Pinkman",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Jesse_Pinkman",
"Jesses","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Jesse_Pinkman",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Jesse_Pinkman",
"Pinkman","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Brandon_%22Badger%22_Mayhew",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Brandon_%22Badger%22_Mayhew",
"Badger","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Christian_%22Combo%22_Ortega",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Christian_%22Combo%22_Ortega",
"Combo","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/George_Merkert",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/George_Merkert",
"George Merkert","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/George_Merkert",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/George_Merkert",
"Merkert","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Gustavo_Fring",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Gustavo_Fring",
"Gus","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Gustavo_Fring",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Gustavo_Fring",
"Guss","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Steven_Gomez",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Steven_Gomez",
"Gomez","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Hector_%22Tio%22_Salamanca",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Hector_%22Tio%22_Salamanca",
"Tio","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Hector_%22Tio%22_Salamanca",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Hector_%22Tio%22_Salamanca",
"tio","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Hank_Schrader",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Hank_Schrader",
"Schrader","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Jane_Margolis",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Jane_Margolis",
"Margolis","",
format(Sys.time(), "%Y-%m-%d %X")))
character_dictionary <- rbind(character_dictionary,
c(character_dictionary$characterId[match("http://breakingbad.wikia.com/wiki/Skinny_Pete",character_dictionary$characterUrl)],
"http://breakingbad.wikia.com/wiki/Skinny_Pete",
"Pete","",
format(Sys.time(), "%Y-%m-%d %X")))
# Remove first name when title or just too short
pattern <- c("Mrs.$", "Dr.$", "M.$", "Mr.$", "Van$")
matches <- grep(paste(pattern,collapse="|"),
character_dictionary$characterName)
character_dictionary <- character_dictionary[-matches,]
# Sort by character ID
character_dictionary$characterId <- as.numeric(character_dictionary$characterId)
character_dictionary <- character_dictionary[order(character_dictionary$characterId, decreasing=FALSE),]
character_dictionary <- character_dictionary[-which(duplicated(character_dictionary$characterName)),]
# Add prefix "chr" to character id to avoid misidentification by replaceName
character_dictionary$characterId <- lapply(character_dictionary$characterId,addPrefix,"chr")
# Temporary fix (Daniel Moncada is wrongly identified as a character while is an actor)
character_dictionary <- character_dictionary[
character_dictionary$characterUrl != "http://breakingbad.wikia.com/wiki/Daniel_Moncada",]
# Create url dictionary
dict_urls <- substring(character_dictionary$characterUrl, 29)
names(dict_urls) <- character_dictionary$characterId
# Create name dictionary
dict_names <- character_dictionary$characterName
names(dict_names) <- character_dictionary$characterId
## Create scene corpus ##
sceneSynopsis <- raw_scene$sceneSynopsis
# Remove '
sceneSynopsis <- gsub("'", " ", sceneSynopsis)
# Replace collective names with personal names
sceneSynopsis <- gsub("cousins","Leonel and Marco Salamanca", sceneSynopsis)
sceneSynopsis <- gsub("Cousins","Leonel and Marco Salamanca", sceneSynopsis)
# Create corpus
corpus <- Corpus(VectorSource(sceneSynopsis))
# Replace urls with unique id
corpus <- tm_map(corpus, replaceName, dict_urls)
# Clean corpus
corpus <- tm_map(corpus, removePunctuation)
corpus <- tm_map(corpus, removeWords, stopwords("en"))
corpus <- tm_map(corpus, stripWhitespace)
# Replace name with unique id
corpus <- tm_map(corpus, replaceName, dict_names)
# Create list of character ID
dict_character_id <- gsub(" ", "", unique(names(dict_names)))
# Create dictionary for ids
# dict_character_id <- Dictionary(characterId)
# Create Document Term Matrix for ID frequency
character_id_freq <- as.matrix(
c(DocumentTermMatrix(corpus,list(dictionary = dict_character_id))
))
character_id_freq[character_id_freq>0] <- 1
# Create graph
graph <- graph.incidence(character_id_freq)
graph <- bipartite.projection(graph)
graph <- graph$proj2
# Add attributes to graph
unique_character_dictionary <- unique(cbind(character_dictionary$characterId,
character_dictionary$characterUrl,
sapply(character_dictionary$characterUrl,extractNameFromUrl)))
unique_character_dictionary <- as.data.frame(unique_character_dictionary, row.names = NULL)
unique_character_dictionary$V1 <- gsub(" ","",unique_character_dictionary$V1)
for (v in V(graph)){
V(graph)$ext_name[v] <- unique_character_dictionary$V3[unique_character_dictionary$V1 %in% V(graph)$name[v]]
V(graph)$url[v] <- unique_character_dictionary$V2[unique_character_dictionary$V1 %in% V(graph)$name[v]]
}
V(graph)$size <- degree(graph)/4
# Cluster analysis (Few minor characters are not connected to the main cluster)
clusters <- clusters(graph, mode="weak")
unconnected_char <- unlist(V(graph)$chr_name[which(clusters$membership>1)])
# Decompose graph based on cluster membership
graph <- decompose.graph(graph, mode = ("weak"), min.vertices = 2)
graph <- graph[[1]]
# Find communities
ed.bt.cm <- edge.betweenness.community(graph,
weights = E(graph)$weight,
directed= FALSE)
no.communities <- length(ed.bt.cm)
V(graph)$membership <- membership(ed.bt.cm)
# Generate colors
col <- rainbow(no.communities)
# Assign colors
V(graph)$color <- col[V(graph)$membership]
# Plot graph
plot(graph,
layout=layout.fruchterman.reingold(graph),
# mark.groups=communities(ed.bt.cm),
vertex.label=V(graph)$ext_name,
vertex.label.cex=0.8,
edge.arrow.size=0.5,
edge.arrow.width=0.5)
# Prepare graph to be exported to graphml
# graphml_ready <- graph
# V(graphml_ready)$name <- gsub("[[:punct:]]", "", V(graphml_ready)$ext_name)
# write.graph(graphml_ready, "~/Desktop/test.graphml", "graphml")
## Check for missing characters ##
# (This step is optional, it will text-mine the corpus of all episode
# for frequent words which might refer to characters)
# Create list of uppercase words
# words <- character(0)
# for (i in 1:length(corpus)) {
# words <- append(words,as.character(corpus[[i]]))
# }
# rm(i)
# words <- unlist(strsplit(words, " "))
#
# uppercase_words <- character(0)
# for(word in words) {
# if (substr(word, 1, 1) == toupper(substr(word, 1, 1))) {
# uppercase_words <- append(uppercase_words, word)
# }
# }
# rm(word,words)
#
# uppercase_words <- unique(uppercase_words)
# dict_uppercase_words <- Dictionary(uppercase_words)
# Inspect term frequency (list common words to check for unidentified BB character)
# term_freq <- t(as.matrix(
# c(DocumentTermMatrix(corpus,list(dictionary = tolower(dict_uppercase_words)))
# )))
# term_freq <- data.frame(term_freq)
# term_freq[,"Total"] <- rowSums(term_freq)
# term_freq <- term_freq[term_freq$Total>1,]
# term_freq <- term_freq[order(term_freq$Total, decreasing=TRUE),]
# term_freq <- term_freq["Total"]