library(stringr)
library(stringi)
library(tm)## Loading required package: NLPlibrary(wordcloud)## Loading required package: RColorBrewerlibrary(ggplot2)##
## Attaching package: 'ggplot2'## The following object is masked from 'package:NLP':
##
## annotatew_Blogs <- readLines("en_US.blogs.txt")
#Select ALL DOCUMENTS in News
w_News <- readLines("en_US.news.txt")## Warning in readLines("en_US.news.txt"): incomplete final line found on
## 'en_US.news.txt'#Select ALL DOCUMENTS in Twitters
w_Twitter <- readLines("en_US.twitter.txt")## Warning in readLines("en_US.twitter.txt"): line 167155 appears to contain an
## embedded nul## Warning in readLines("en_US.twitter.txt"): line 268547 appears to contain an
## embedded nul## Warning in readLines("en_US.twitter.txt"): line 1274086 appears to contain an
## embedded nul## Warning in readLines("en_US.twitter.txt"): line 1759032 appears to contain an
## embedded nulsummary(w_Blogs)## Length Class Mode
## 899288 character charactersummary(w_News)## Length Class Mode
## 77259 character charactersummary(w_Twitter)## Length Class Mode
## 2360148 character charactertokenmaker <- function(x) {
corpus <- Corpus(VectorSource(x))
corpus <- tm_map(corpus, content_transformer(tolower))
corpus <- tm_map(corpus, removePunctuation)
corpus <- tm_map(corpus, stripWhitespace)
corpus <- tm_map(corpus, removeWords, stopwords("english"))
corpus <- tm_map(corpus, removeNumbers)
corpus <- tm_map(corpus, PlainTextDocument)
corpus <- Corpus(VectorSource(corpus))
}
wordcounter <- function(x) {
dtm<-DocumentTermMatrix(x)
dtm_matrix <- as.matrix(dtm)
word_freq <- colSums(dtm_matrix)
word_freq <- sort(word_freq, decreasing = TRUE)
words <- names(word_freq)
return(list(words, word_freq))
}
Next_Word <- function(x,y){
BQuest<-grepl(x, w_Blogs, ignore.case=TRUE)
BDocs<-w_Blogs[BQuest]
c_text<-'a'
Next_Word<-'a'
i<-length(BDocs)
if (i>0)
{
for (i in 1:i)
{ c_text[i]<- str_extract(BDocs[i], y)
Next_Word[i]<- stri_extract_last_words(c_text[i])
}
}
NQuest<-grepl(x, w_News, ignore.case=TRUE)
NDocs<-w_News[NQuest]
j=length(NDocs)
if (j>0)
{
for (j in 1:j)
{ c_text[i+j]<- str_extract(NDocs[j], y)
Next_Word[i+j]<- stri_extract_last_words(c_text[i+j])
}
}
TQuest<-grepl(x, w_Twitter, ignore.case=TRUE)
TDocs<-w_Twitter[TQuest]
k=length(TDocs)
if (k>0)
{
for (k in 1:k)
{ c_text[i+j+k]<- str_extract(TDocs[k], y)
Next_Word[i+j+k]<- stri_extract_last_words(c_text[i+j+k])
}
}
bundle<-as.data.frame(Next_Word, stringsAsFactors=FALSE)
summary (bundle)
blogs_token <- tokenmaker(bundle)
blogs_words <- wordcounter(blogs_token)
summary(nchar(bundle))
head(bundle)
tdm_Blogs<-TermDocumentMatrix(blogs_token)
m_Blogs<-as.matrix(tdm_Blogs)
v_Blogs<-sort(rowSums(m_Blogs),decreasing=TRUE)
d_Blogs<-data.frame(word=names(v_Blogs),freq=v_Blogs)
head(v_Blogs, 100)
return(list(head(v_Blogs,100)))
}–Question 1-
result_01<-Next_Word("a case of ", "([Aa]+ +[Cc]ase+ +[Oo]f+ +[^ ]+ )" )## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_01## [[1]]
## beer character(0), miller mistaken
## 19 5 4 4
## wine first making waiting
## 4 3 3 3
## water crossed food great
## 3 2 2 2
## jet knowing mind one
## 2 2 2 2
## pabst poor red severe
## 2 2 2 2
## spring trial trying whether
## 2 2 2 2
## "cargument 0), 121, 20,
## 1 1 1 1
## 21.5346229076385, 25, 26, 45,
## 1 1 1 1
## amnesia anchor anxiety armed
## 1 1 1 1
## arrested art assembling baboon
## 1 1 1 1
## bad bananas banks better
## 1 1 1 1
## bible bolting books boosting
## 1 1 1 1
## bottles bowed boxer bud
## 1 1 1 1
## bulk buyer bwvaktboom carpal
## 1 1 1 1
## carrots catching cds cellulitis
## 1 1 1 1
## changing character(0))) citation class
## 1 1 1 1
## cold colic collateral conspicuous
## 1 1 1 1
## cool coors corona damaged
## 1 1 1 1
## datetimestamp defense deja delhi
## 1 1 1 1
## democratic dependent description dialing
## 1 1 1 1
## digging dip dipping disgusting
## 1 1 1 1
## disposables dispute dodge double
## 1 1 1 1
## dragonitis duct dundee ebola
## 1 1 1 1
## everybody excusable exploring extreme
## 1 1 1 1
## extremes fascism fearing finding
## 1 1 1 1The answer is “beer” since it is the most frequent word that makes the sentence make sense. –Question 2—
result_02<-Next_Word("would mean the ", "([Ww]ould+ +[Mm]ean+ +[Tt]he+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_02## [[1]]
## world character(0), absolute end
## 168 5 2 2
## entire "cworld 0), 121,
## 2 1 1 1
## 20, 25, 26, 33.9637188911438,
## 1 1 1 1
## 45, airport angles central
## 1 1 1 1
## century character(0))) datetimestamp death
## 1 1 1 1
## description heading hour isdst
## 1 1 1 1
## language list(author list(content list(sec
## 1 1 1 1
## mday meta min mon
## 1 1 1 1
## origin person sitter state
## 1 1 1 1
## sun transformation wday world",
## 1 1 1 1
## worldd yday year "en")
## 1 1 1 1
## list(language list()
## 1 1The answer is “world” since it is the most frequent word that makes the sentence make sense.
–Question 3-
result_03<-Next_Word("make me the ", "([Mm]ake+ +[Mm]e+ +[Tt]he+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_03## [[1]]
## happiest character(0), best worlds
## 26 5 2 2
## "cfirst 0), 121, 20,
## 1 1 1 1
## 25, 26, 45, 47.8151431083679,
## 1 1 1 1
## asshole bad biggest bun
## 1 1 1 1
## character(0))) datetimestamp daughter description
## 1 1 1 1
## girl happiest", heading hour
## 1 1 1 1
## isdst jackie kiddy language
## 1 1 1 1
## list(author list(content list(sec manager
## 1 1 1 1
## mday meta min mon
## 1 1 1 1
## morbid mother number origin
## 1 1 1 1
## parent professional role scape
## 1 1 1 1
## target undisputed universe way
## 1 1 1 1
## wday winner yday year
## 1 1 1 1
## "en") list(language list()
## 1 1 1The answer is “happiest”. –Question 4—
result_04<-Next_Word("struggling ", "([Ss]truggling+ +[^ ]+ +[^ ]+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_04## [[1]]
## ends bit fact life
## 15 8 7 6
## new years character(0), first
## 6 6 5 5
## keep afloat back issues
## 5 4 4 4
## now part touring work
## 4 4 4 4
## baby buy can eating
## 3 3 3 3
## even food make money
## 3 3 3 3
## mortgage self sense since
## 3 3 3 3
## social still stuff things
## 3 3 3 3
## think time weight another
## 3 3 3 2
## anything awake bad care
## 2 2 2 2
## child concept conditions crust
## 2 2 2 2
## dance day desire economy
## 2 2 2 2
## enough everything free gender
## 2 2 2 2
## god going great head
## 2 2 2 2
## identity jobs just last
## 2 2 2 2
## lately lot neutral outside
## 2 2 2 2
## particular pay payments photos
## 2 2 2 2
## pounds readers really right
## 2 2 2 2
## said school season something
## 2 2 2 2
## started state times way
## 2 2 2 2
## ways will wont world
## 2 2 2 2
## year "cin 0), 0.945008993148804,
## 2 1 1 1
## 121, 20, 25, 26,
## 1 1 1 1
## 46, able absent academic
## 1 1 1 1
## accidentally addiction addition adult
## 1 1 1 1result_04a<-Next_Word("struggling ", "([Ss]truggling+ +[^ ]+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_04a## [[1]]
## find get make keep bit
## 54 51 36 33 15
## survive stay little pay now
## 14 12 10 10 9
## figure maintain understand work fit
## 8 8 8 7 6
## like put see something carry
## 6 6 6 6 5
## character(0), depression finish hold just
## 5 5 5 5 5
## life raise reach walk breath
## 5 5 5 5 4
## bring come control cope infertility
## 4 4 4 4 4
## musician afford air almost another
## 4 3 3 3 3
## breathe catch day decide feel
## 3 3 3 3 3
## free hard issues learn loss
## 3 3 3 3 3
## lot market much preserve recover
## 3 3 3 3 3
## remember right sell start write
## 3 3 3 3 3
## year accept addiction back best
## 3 2 2 2 2
## break businesses buy check clear
## 2 2 2 2 2
## climb close coming compete complete
## 2 2 2 2 2
## contain escape establish feed feeding
## 2 2 2 2 2
## first focus gain half handle
## 2 2 2 2 2
## hide high hit identity live
## 2 2 2 2 2
## long maker manage math meet
## 2 2 2 2 2
## move negative overcome people practice
## 2 2 2 2 2result_04b<-Next_Word("struggling ", "([Ss]truggling+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_04b## [[1]]
## financially right just readers
## 9 8 7 6
## struggling students character(0), economy
## 6 6 5 5
## writer artist artists mightily
## 5 4 4 4
## nyc since americans city
## 4 4 3 3
## families lately learners like
## 3 3 3 3
## now today trying actress
## 3 3 3 2
## chain company consistency daily
## 2 2 2 2
## early every going housing
## 2 2 2 2
## offensively quite radio residents
## 2 2 2 2
## schools team urban writers
## 2 2 2 2
## "cin 0), 121, 20,
## 1 1 1 1
## 25, 26, 27.7474119663239, 46,
## 1 1 1 1
## abandoned actor addicts adding
## 1 1 1 1
## air airlines along always
## 1 1 1 1
## among anymore apprentices art
## 1 1 1 1
## artist<e2> attorney away baker
## 1 1 1 1
## barrister behind big black
## 1 1 1 1
## blues born breweries brewery
## 1 1 1 1
## business businessman character(0))) child
## 1 1 1 1
## children christian<e2> cities climb
## 1 1 1 1
## college companies constantly continued
## 1 1 1 1
## country cyster datetimestamp david
## 1 1 1 1
## department description desperately developed
## 1 1 1 1
## downtown economic elementary employees
## 1 1 1 1
## engineering entities ers esp
## 1 1 1 1Question 4 answer: There is no sequence “struggling but the” in whole corpus. I try with struggling and any other 3, 2 and 1 words in sequence. The answer is “defense” because this word have sense in the sentence.
–Question 5—
result_05<-Next_Word("date at the ", "([Dd]ate+ +[Aa]t+ +[Tt]he+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_05## [[1]]
## character(0), end time "cwrong
## 5 5 3 1
## 0), 121, 20, 25,
## 1 1 1 1
## 26, 39.9228720664978, 46, app
## 1 1 1 1
## art bottom braves cake
## 1 1 1 1
## character(0))) cheese datetimestamp description
## 1 1 1 1
## driskill four grocery", heading
## 1 1 1 1
## hour isdst lake language
## 1 1 1 1
## list(author list(content list(sec mday
## 1 1 1 1
## meta min mon movie
## 1 1 1 1
## naval next origin palafox
## 1 1 1 1
## prado prestigious republican rex
## 1 1 1 1
## wday whiskey yday year
## 1 1 1 1
## "en") list(language list()
## 1 1 1The correct answer is “beach”, because this word have sense in teh sentence.
–Question 6—
result_06<-Next_Word("be on my ", "([Bb]e+ +[Oo]n+ +[Mm]y+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_06## [[1]]
## way mind show best
## 32 12 8 5
## character(0), list game ipod
## 5 5 4 4
## radio background side top
## 4 3 3 3
## youtube back couch dick
## 3 2 2 2
## facebook feet first friends
## 2 2 2 2
## last next phone porch
## 2 2 2 2
## screen terms "cna 0),
## 2 2 1 1
## 121, 20, 25, 26,
## 1 1 1 1
## 46, 51.8344950675964, album annual
## 1 1 1 1
## bad bday belly birthday
## 1 1 1 1
## blog board break bus
## 1 1 1 1
## career channel character(0))) children
## 1 1 1 1
## christmas college computer couch",
## 1 1 1 1
## cuz dads daily datetimestamp
## 1 1 1 1
## day description deserved dissertation
## 1 1 1 1
## dolo dsixl etsy fantasy
## 1 1 1 1
## favorite final flight grave
## 1 1 1 1
## grind guilty heading holiday
## 1 1 1 1
## hour icloud ihome isdst
## 1 1 1 1
## knees language lap laptop
## 1 1 1 1
## linked list(author list(content list(sec
## 1 1 1 1
## lostken mday melodifestivalen menu
## 1 1 1 1
## meta min mobile moms
## 1 1 1 1
## mon mouth new official
## 1 1 1 1
## origin personal pone pure
## 1 1 1 1The correct answer is “way”. –Question 7—
result_07<-Next_Word("quite some ", "([Qq]uite+ +[Ss]ome+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_07 ## [[1]]
## time character(0), company distance
## 274 5 2 2
## people way "ctime 0),
## 2 2 1 1
## 121, 20, 25, 26,
## 1 1 1 1
## 47, 5.92976808547974, character(0))) datetimestamp
## 1 1 1 1
## description extras freedom fun
## 1 1 1 1
## hair heading hour improvement
## 1 1 1 1
## interesting isdst language list(author
## 1 1 1 1
## list(content list(sec mday meta
## 1 1 1 1
## min mon months na",
## 1 1 1 1
## news origin terrible things
## 1 1 1 1
## tradition wday yday year
## 1 1 1 1
## years "en") list(language list()
## 1 1 1 1The answer is “time”, that make sense in the sentence.
–Question 8—
result_08<-Next_Word("his little ", "([Hh]is+ +[Ll]ittle+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_08 ## [[1]]
## girl guy boy gem blog
## 89 60 42 33 28
## one brother beauty man sister
## 27 22 21 18 18
## cutie project baby bit piece
## 16 16 15 14 12
## piggy kid corner head number
## 12 11 10 10 10
## thing book dog heart lady
## 10 9 9 9 9
## game house blue angel body
## 8 8 7 6 6
## box face finger hand hands
## 6 6 6 6 6
## league light old person tidbit
## 6 6 6 6 6
## video white break card character(0),
## 6 6 5 5 5
## ditty dude family girls legs
## 5 5 5 5 5
## life note tiny bag brothers
## 5 5 5 4 4
## car child feet fella film
## 4 4 4 4 4
## fingers journey nugget ones place
## 4 4 4 4 4
## princess scene son spot story
## 4 4 4 4 4
## sweetheart sweetie town yellow ass
## 4 4 4 4 3
## belly bird bundle chair daughter
## 3 3 3 3 3
## exercise eyes gift girly group
## 3 3 3 3 3
## idea kitty list mama miracle
## 3 3 3 3 3
## monkey peek personality pink post
## 3 3 3 3 3
## quilt quiz series table trip
## 3 3 3 3 3The answer is “fingers” that make sense in the sentence. –Question 9—
result_09<-Next_Word("during the ", "([Dd]uring+ +[TT]he+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_09 ## [[1]]
## character(0), amendment biggest day
## 5 2 2 2
## "cna 0), 121, 20,
## 1 1 1 1
## 25, 26, 33.0719590187073, 47,
## 1 1 1 1
## act believetour big birthday
## 1 1 1 1
## bloody booth born buccos
## 1 1 1 1
## centennial character(0))) cnn communist
## 1 1 1 1
## datetimestamp description first great
## 1 1 1 1
## heading hour isdst language
## 1 1 1 1
## last lion list(author list(content
## 1 1 1 1
## list(sec lonely lovely mday
## 1 1 1 1
## meta min mon movie
## 1 1 1 1
## na", notebook origin oscars
## 1 1 1 1
## palio rise saga wday
## 1 1 1 1
## width yday year "en")
## 1 1 1 1
## list(language list()
## 1 1The answer is “bad”. –Question 10-
result_10<-Next_Word("must be ", "([Mm]ust+ +[Bb]e+ +[^ ]+ )" ) ## Warning in tm_map.SimpleCorpus(corpus, content_transformer(tolower)):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removePunctuation): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, stripWhitespace): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, removeWords, stopwords("english")):
## transformation drops documents## Warning in tm_map.SimpleCorpus(corpus, removeNumbers): transformation drops
## documents## Warning in tm_map.SimpleCorpus(corpus, PlainTextDocument): transformation drops
## documentsresult_10 ## [[1]]
## able done something taken made nice
## 105 84 80 60 59 59
## following getting really one willing like
## 56 50 50 46 43 37
## good going pretty said hard prepared
## 36 33 32 32 29 27
## true submitted given seen received careful
## 27 25 24 24 23 22
## crazy lived close new time paid
## 22 21 20 20 20 19
## born feeling kept wrong present ready
## 18 18 18 18 17 17
## used put stopped tired destroyed felt
## 17 16 16 16 15 15
## followed read watching addressed aware completed
## 15 15 15 14 14 14
## considered removed allowed bored held part
## 14 14 13 13 13 13
## quite talking thinking wondering coming tough
## 13 13 13 13 12 12
## just noted protected someone understood accompanied
## 11 11 11 11 11 10
## free great honest mad met right
## 10 10 10 10 10 10
## strong treated another around dealt driven
## 10 10 9 9 9 9
## old placed provided sick using almost
## 9 9 9 9 9 8
## balanced based better big broken completely
## 8 8 8 8 8 8
## important involved missing open preserved real
## 8 8 8 8 8 8
## replaced sent set sought
## 8 8 8 8The answer is “insane”, that make sense in the sentence.