뽐뿌_차 관련 키워드 빈도 분석(의뢰)

의뢰 받아 진행한 차 관련 키워드 기반 데이터 수집 및 빈도 분석입니다.

install.packages('pacman')
library(pacman)
p_load('httr','rvest','RSelenium','dplyr','stringr','openxlsx','tm')
remotes::install_github('haven-jeon/KoNLP',upgrade='never',INSTALL_opts=c("--no-multiarch"))
#install.packages('Rcpp')
#library(Rcpp)
library(KoNLP)


make_url<-function(last_page,keyword){
  page=1:last_page
  url=c()
  for(i in page){
    url=append(url,paste0('https://www.ppomppu.co.kr/zboard/zboard.php?id=car&page=',i,'&search_type=sub_memo&keyword=',URLencode(keyword),'&divpage=160'))
  }
  return(url)
}


get_url=function(url){
  all_url=c()
  for(i in url){
    url_data=read_html(i,encoding='cp949') %>% html_nodes('.list_vspace')%>%html_nodes('a') %>% html_attr('href')
    url_data[grep('view.php',url_data)]
    
    all_url=append(all_url,url_data[grep('view.php',url_data)])
    print(i)
    
  }
  all_url=paste0('https://www.ppomppu.co.kr/zboard/',all_url)
  return(all_url)
}

page_url=make_url(13,'튜닝')
text_url=get_url(page_url)
data_all=data.frame()

now=1

for(i in text_url){
  
  #제목
  title=read_html(i,encoding='cp949') %>% html_nodes('.view_title2') %>% html_text()
  
  #등록일, 조회수
  temp=read_html(i,encoding='cp949') %>% html_nodes('.sub-top-text-box') %>% html_text2()
  date=str_split(str_extract(temp,'등록일:.*.\n') %>% str_extract('[0-9]+-[0-9]+-[0-9]+ [0-9]+:[0-9]+'),' ')[[1]][1]
  time=str_split(str_extract(temp,'등록일:.*.\n') %>% str_extract('[0-9]+-[0-9]+-[0-9]+ [0-9]+:[0-9]+'),' ')[[1]][2]
  temp1=str_extract(temp,'조회수:.*./')
  view=gsub('[^0-9]','',temp1)
  
  #본문
  
  body=read_html(i,encoding='cp949') %>% html_nodes('.board-contents') %>% html_text()
  
  
  #댓글
  chat_all=c()
  no=gsub('[^0-9]','',str_extract(i,'no=[0-9]+'))
  num=1
  repeat{
    chat_url = paste0('https://www.ppomppu.co.kr/zboard/comment.php?id=car&no=',no,'&c_page=',num,'&comment_mode=')
    num=num+1
    
    temp=read_html(chat_url,encoding='cp949') %>% html_nodes('.over_hide')
    temp1=temp[grep('commentContent',temp)] %>% html_text()
    if(length(temp1)==0){
      break
    }
    chat_all=append(chat_all,gsub('  | @[가-힣a-zA-Z0-9\\.]+','',temp1))
    print(chat_url)
    Sys.sleep(runif(1,2,3))
    
  }
  if(length(chat_all)==0){
    chat_all=NA
  }
  data_all = rbind(data_all,data.frame(title,date,time,body,chat_all))
  print(paste0(now,'/',length(text_url)))
  now=now+1
  Sys.sleep(runif(1,2,3))
}

data_id = data.frame(id=1:nrow(unique(data_all['title'])),title=unique(data_all['title']))

data=right_join(data_id,data_all)

write.xlsx(data,'데이터 수집.xlsx')

useNIADic()

library(tm)

ko.words <- function(doc){
  d <- as.character(doc)
  pos <- paste(SimplePos09(d))
  extracted <- str_match(pos, '([가-힣0-9]+)/[NP]')
  keyword <- extracted[,2]
  keyword[!is.na(keyword)]
}

################## title frequency
cps <- VCorpus(VectorSource(unique(data$title)))

tdm <- TermDocumentMatrix(cps,
                          control = list(weighting= weightBin, 
                                         tokenize=ko.words,
                                         removePunctuation = T,
                                         removeNumbers = T,
                                         stopwords = c()))

tdm <- as.matrix(tdm)
# View(tdm)

v <- sort(slam::row_sums(tdm), decreasing = T)
data <- data.frame(X=names(v),freq=v)
write.xlsx(data,'title_frequency.xlsx')



################## body_frequency
cps <- VCorpus(VectorSource(unique(data$body)))
tdm <- TermDocumentMatrix(cps,
                          control = list(weighting= weightBin, 
                                         tokenize=ko.words,
                                         removePunctuation = T,
                                         removeNumbers = T,
                                         stopwords = c()))

tdm <- as.matrix(tdm)
# View(tdm)

v <- sort(slam::row_sums(tdm), decreasing = T)
data1 <- data.frame(X=names(v),freq=v)
write.xlsx(data1,'body_frequency.xlsx')

################## comment_frequency
cps <- VCorpus(VectorSource(data$chat_all))
tdm <- TermDocumentMatrix(cps,
                          control = list(weighting= weightBin, 
                                         tokenize=ko.words,
                                         removePunctuation = T,
                                         removeNumbers = T,
                                         stopwords = c()))

tdm <- as.matrix(tdm)
# View(tdm)

v <- sort(slam::row_sums(tdm), decreasing = T)
data1 <- data.frame(X=names(v),freq=v)
write.xlsx(data1,'comment_frequency.xlsx')