https://rpubs.com/koyobib/bm12 ã®ç¶ã
library(readr)
library(openxlsx)
library(stringr)
library(stringdist)
library(dplyr)
library(RMeCab)
library(igraph)
library(rvest)
library(gt)
library(gtExtras)
library(openxlsx)
library(purrr)
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çŸä»£çããŒãºãžã®å¯Ÿå¿ã«ã€ããŠã®ïŒããã®ååãšæè²å·¥åŠãšã®æ¥ç¹
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ãšã©ãŒã¯ç¡èŠããŠåé¡ãªã
keywords <- read.xlsx("../Keywords/Keywords.xlsx")
DT::datatable(keywords)
jjer <- read.csv("../Data_nkf/JJER_ABST.csv") #æè²åŠç ç©¶
head(jjer)
## X Journal Year Volume Number Page DOI Class Incld
## 1 1 JJER 2022 89 4 514 kyoiku.89.4_514 ç¹é åé
## 2 2 JJER 2022 89 4 526 kyoiku.89.4_526 ç¹é åé
## 3 3 JJER 2022 89 4 539 kyoiku.89.4_539 ç¹é åé
## 4 4 JJER 2022 89 4 552 kyoiku.89.4_552 ç¹é åé
## 5 5 JJER 2022 89 4 565 kyoiku.89.4_565 ç¹é åé
## 6 6 JJER 2022 89 4 579 kyoiku.89.4_579 ç¹é åé
## JYVNP
## 1 JJER_2022_89_4_514
## 2 JJER_2022_89_4_526
## 3 JJER_2022_89_4_539
## 4 JJER_2022_89_4_552
## 5 JJER_2022_89_4_565
## 6 JJER_2022_89_4_579
## Abst
## 1 ç·å¥³ã®ç¹æ§è«ã¯ãææ²»å幎ãç·å¥³åæš©è«ãšç·å°å¥³åã®äž¡æ¹ãåŠå®ãããã®ãšããŠæç«ããæŠåã®å¥³åæè²ã®äž»èŠãªæè²ç念ãšãªã£ããç¹æ§è«ã¯æŠåŸã®ç·å¥³å
±åŠå¶ã«ãããŠãç¶æãããæè²èª²çšã®ç·å¥³æ Œå·®ã¯ãç·å¥³ã®æ¬è³ªçå¹³çãä¿éããããã®åççãªå·®ç°ãšèŠãªãããã1985幎ã®å¥³æ§å·®å¥æ€å»æ¡çŽã®æ¹åãšãžã§ã³ããŒè«ã®æ®åã«ããç¹æ§è«ã¯çµçãããã仿¥ãç·å¥³ãåºå¥ããããšèªäœããå·®å¥ããšèŠãªãããäžã§ã女åæè²ã®ååšæçŸ©ãæ¹ããŠåãããŠããã
## 2 å°æ°æŽŸã®èŠªã®ææãã©ã®ããã«äœçœ®ã¥ããããšããå
¬ç§äºå
è«å顿ãã«æ§æè²è«äºãçè§£ããããšã¯ã§ããªããå®æãæ±ã£ãŠãããæ§ãããŸãè¿ä»£ç€ŸäŒãç§çãªããšãããšãããæ§ãããå
¬æè²ã§ç©æ¥µçã«æ±ãã®ãæ§æè²ã ããã ãæè²å
容ã®ã¿ãªããæ§æè²ã®å®æœãã®ãã®ã«åæã§ããªã宿é¢ä¿è
ãªã©ããã®æ¹å€ãç»å ŽããŠæ§æè²è«äºãšãªããæ¬çš¿ã§ã¯ãã€ã®ãªã¹ãã¢ã¡ãªã«ããã³æ¥æ¬ã®æ§æè²è«äºã®ç¹åŸŽãšãã®è«ç¹ãžã®å¯ŸåŠæ¹æ³ãæŽçããã
## 3 æ¬ç ç©¶ã¯ããã€ãã®å¹Œå
æè²çãçœåŒããŠããæè²çµç¹ã§ãããã¹ã¿ãããã»ãã¬ãŒãã«ããŠã¹ã®ææ³ãšãããºã ãšã®é¢ä¿ãæ€èšããããšã«ããã女æ§ã®ç€ŸäŒç掻èºã®æŽ»è·¯ã幌å
æè²ã«èŠåºããæ¯æ§ã®è«çã¯ããã¹ã¿ãããã»ãã¬ãŒãã«ããŠã¹ã«ãããåã©ããšå®¶æãäžäœåãããææ³ãæ¯ãããã®ã§ãã£ãã幌å
æè²ã¯å®¶æã«æºãããã®ãšäœçœ®ä»ããããåŠæ ¡æè²äœç³»ããåæããããããã«ãã幌å
æè²ã¯å®¶æãè³è³ãããããºã ã®è«çãšã·ãŒã ã¬ã¹ã«æ¥åããŠããããšãšãªã£ãã
## 4 倧åŠã©ã³ã¯ãåŠéšåŠç§ã®å°æ»ã«ãããç·å¥³å·®ãåæããåŸæ¥ã®ç ç©¶ã¯ã倧åŠã©ã³ã¯ãšå°æ»ãå¥ã
ã«åæããŠããããããã倧åŠã©ã³ã¯ãå°æ»ã浪人ãšããéžæãªã©ã®å€æ§ãªå€æ°ãåæã«èæ
®ããªããã°ã倧åŠé²åŠãšãžã§ã³ããŒã®é¢ä¿æ§ã¯ã¿ããŠããªãã®ã§ã¯ãªãããããã§æ¬çš¿ã§ã¯å€é察å¿åæãçšããŠããããã®å€æ°éã®ãé¢ä¿ã®ç¶²ããåæ§ç¯ããããã®çµæã人ã
ã®ãåççãªéžæããä¿ããŠãžã§ã³ããŒäžå¹³çãæç¶ãããå¶åºŠçæèãæããã«ãªãã
## 5 æ¬çš¿ã¯ã代衚æ§ã®ããå€§èŠæš¡ãªå¥³æ§ã®ã©ã€ããã¹ããªãŒã»ããŒã¿ãçšããŠãåºçã³ãŒããŒãå¥ã«å¹Žéœ¢ããšã®è·æ¥çå°äœãåæ§æããæ¹æ³ã玹ä»ãããã®ææ³ã«ãã£ãŠèç©ããŠããèšè¿°çãªåæçµæãããæ¥æ¬äººå¥³æ§ã®ã©ã€ãã³ãŒã¹ã®é·æçãªå€åã説æããããšãã«æŠæäœå¶äžã®1940幎代ååã1970幎代åã°ã®ç³æ²¹ã·ã§ãã¯ä»¥åŸã1990幎代åã°ä»¥éã®ã倱ããã10幎ãã®3ã€ã®è»¢ææã«çç®ããŠãMååã®ç»å Žãå®çãå€å®¹ãæ€èšããŠããã
## 6 æ¬çš¿ã¯ããã©ã°ããã£ãºã ã®äžå¿æŠå¿µã®äžã€ã§ãããç¿æ
£ïŒhabitïŒãã®èгç¹ããããžã§ã³ããŒãèå¯ãããç¿æ
£ãšãããã©ã°ããã£ãºã ã®æŠå¿µã¯ããžã§ã³ããŒãç§ãã¡ã®èº«äœçãªååšãæ§æããæ§é ã§ããããšçè§£ãããããããããã«ãªãã¥ã©ã ãç ç©¶ã¯ãæå®€ã®äžã§ã»ã¯ã·ãºã ãäŒããããŠããããšãæããã«ããããã©ã°ããã£ãºã ã®ãç¿æ
£ãæŠå¿µã¯ãã»ã¯ã·ãºã ã®å
æã®ããã»ã¹ã«ã€ããŠç§ãã¡ã®çè§£ãããã«æ·±ããããšã«è²¢ç®ããã
kws <- keywords$Order
for (i in kws){
varname <- paste("kw_", i, sep = "")
appear <- str_detect(jjer$Abst, pattern = keywords[i,7])
appear <- data.frame(as.numeric(appear))
colnames(appear) <- varname
assign(varname, appear)
}
jjer.doi <- jjer$DOI
jjer.res <- dplyr::bind_cols(jjer.doi,
kw_1, kw_2, kw_3, kw_4, kw_5, kw_6, kw_7, kw_8,
kw_9, kw_10, kw_11, kw_12, kw_13, kw_14, kw_15,
kw_16, kw_17, kw_18, kw_19, kw_20, kw_21, kw_22,
kw_23, kw_24, kw_25, kw_26, kw_27, kw_28, kw_29,
kw_30, kw_31, kw_32, kw_33, kw_34, kw_35, kw_36,
kw_37, kw_38, kw_39, kw_40, kw_41, kw_42, kw_43,
kw_44, kw_45, kw_46, kw_47, kw_48, kw_49, kw_50,
kw_51, kw_52, kw_53, kw_54, kw_55, kw_56, kw_57,
kw_58, kw_59, kw_60, kw_61, kw_62, kw_63, kw_64,
kw_65, kw_66, kw_67, kw_68, kw_69, kw_70, kw_71,
kw_72, kw_73, kw_74, kw_75, kw_76, kw_77, kw_78,
kw_79, kw_80, kw_81, kw_82, kw_83, kw_84, kw_85,
kw_86, kw_87, kw_88, kw_89, kw_90, kw_91, kw_92,
kw_93, kw_94, kw_95, kw_96, kw_97, kw_98, kw_99,
kw_100, kw_101, kw_102, kw_103, kw_104, kw_105,
kw_106, kw_107, kw_108, kw_109, kw_110, kw_111,
kw_112, kw_113, kw_114, kw_115, kw_116, kw_117,
kw_118, kw_119, kw_120, kw_121, kw_122, kw_123,
kw_124, kw_125, kw_126, kw_127, kw_128, kw_129,
kw_130, kw_131, kw_132, kw_133, kw_134, kw_135,
kw_136, kw_137, kw_138, kw_139, kw_140, kw_141,
kw_142, kw_143, kw_144, kw_145, kw_146, kw_147,
kw_148, kw_149, kw_150, kw_151, kw_152, kw_153,
kw_154, kw_155, kw_156, kw_157, kw_158, kw_159,
kw_160, kw_161, kw_162, kw_163, kw_164, kw_165,
kw_166, kw_167, kw_168, kw_169, kw_170, kw_171,
kw_172, kw_173, kw_174, kw_175, kw_176, kw_177,
kw_178, kw_179, kw_180, kw_181, kw_182, kw_183,
kw_184, kw_185, kw_186, kw_187, kw_188, kw_189)
jjer.res$sum <- jjer.res %>% select(contains("kw_")) %>% rowSums
write.csv(jjer.res, "../Tagged/jjer_tag.csv") # DOIãšã¿ã°ã®ããŒã¿ãä¿å
# æŸãããã®
jjer.doi.kw <- jjer.res %>% dplyr::filter(sum > 0)
jjer.doi.kw <- jjer.doi.kw[c(1)]
colnames(jjer.doi.kw) <- c("DOI")
jjer.abst.kw_ <- jjer[c("DOI", "Abst")]
jjer.abst.kw <- dplyr::inner_join(jjer.doi.kw, jjer.abst.kw_, by = "DOI")
write.csv(jjer.abst.kw, "../kakunin/jjer_abst_kw.csv")
# æŸããªãã£ããã®
# æŸãããã®
jjer.doi.zero <- jjer.res %>% dplyr::filter(sum == 0)
jjer.doi.zero <- jjer.doi.zero[c(1)]
colnames(jjer.doi.zero) <- c("DOI")
jjer.abst.zero_ <- jjer[c("DOI", "Abst")]
jjer.abst.zero <- dplyr::inner_join(jjer.doi.zero, jjer.abst.zero_, by = "DOI")
write.csv(jjer.abst.zero, "../kakunin/jjer_abst_zero.csv")
jjep <- read.csv("../Data_nkf/JJEP_ABST.csv") # æè²å¿çåŠç ç©¶
head(jjep)
## X Journal Year Volume Number Page DOI Class Incld JYVNP
## 1 1 jjep 2022 70 4 333 jjep.70.333 åè åé JJEP_2022_70_4_333
## 2 2 jjep 2022 70 4 347 jjep.70.347 åè åé JJEP_2022_70_4_347
## 3 3 jjep 2022 70 4 362 jjep.70.362 åè åé JJEP_2022_70_4_362
## 4 4 jjep 2022 70 4 376 jjep.70.376 åè åé JJEP_2022_70_4_376
## 5 5 jjep 2022 70 4 389 jjep.70.389 å®è·µ åé JJEP_2022_70_4_389
## 6 6 jjep 2022 70 4 404 jjep.70.404 å®è·µ åé JJEP_2022_70_4_404
## Abst
## 1 ææè
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床ãã¹ãã«ã®åäžãããããšããå¿çæè²ããã°ã©ã ïŒSOS ã®åºãæ¹ã»åãæ¢ãæ¹ã«é¢ããæè²ïŒã®å¹æãæ€èšãïŒä»åŸã®èªæ®ºäºé²æè²ãžã®ç€ºåãåŸãããšãç®çãšãããèš2åã®ææ¥ããæ§æãããããã°ã©ã ãåŠçŽåäœã§å®æœãïŒåäººã»æåž«ã«å¯Ÿãã被æŽå©å¿åæ§ïŒæŽå©èŠè«ã¹ãã«ïŒå人ã«å¯ŸããæŽå©ã¹ãã«ã枬å®ãã尺床ãçšããèªèšåŒè³ªåçŽã«ãã广æ€èšãè¡ã£ãã察象ãšãªã£ãå°åŠ5, 6幎ç111åã®ããŒã¿ãçšããŠè§£æãè¡ã£ãçµæïŒæŽå©èŠè«ã¹ãã«ãå人ã«å¯ŸããæŽå©ã¹ãã«ãªã©ã«ãããŠããã°ã©ã ã®è¯å®çãªå¹æã瀺ãããäžæ¹ïŒå人ã«å¯Ÿãã被æŽå©å¿åæ§ã®äžéšã®äžäœå°ºåºŠã§ã¯ç·åå
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## 6 èªç«çã«æ·±ãåŠã¶åã®è²æã¯ïŒæ°æè²èª²çšã«ãããŠåŒ·èª¿ãããŠããéèŠãªæè²ç®æšã§ãããæ°åã³ãããŠã€ã«ã¹ææçïŒCOVID-19ïŒã®æ¡å€§ã«ããïŒå®¶åºã§èªãåŠç¿ããæéãå¢å ããããšããïŒä»¥åã«ããŸããŠãã®åã®éèŠæ§ããé«ãŸã£ãŠãããäžæ¹ã§ïŒåŠç¿è
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¬ç«é«æ ¡ã«ãããŠïŒå
¬ç«é«æ ¡1幎ç33åã察象ã«ïŒèªåŠèªç¿ãæ¯æŽããããªã³ã©ã€ã³åŠç¿æ³è¬åº§ïŒå
š6åïŒããå®è·µãããæ¬å®è·µãéçºããã«ãããïŒãªã³ã©ã€ã³ãªãã§ã¯ã®æå°äžã®å·¥å€«ãå°å
¥ãããšãšãã«ïŒãªã³ã©ã€ã³ãåæãšããªãåŸæ¥ã®æå°æ³äžã®å·¥å€«ãã©ã®ããã«çµ±åãã¹ããã«ã€ããŠãæ€èšãããè¬åº§ã宿œããçµæïŒãªã³ã©ã€ã³ãŠãã®å®æœã§ã¯ãã£ããïŒçåŸã«è¬åº§ã®è¶£æšããååã«äŒãã£ãŠããæ§åã確èªããããšãšãã«ïŒé«ãæºè¶³åºŠãåŸãããããŸãïŒäžéšã®çåŸã§ã¯ãããã®ã®è€æ°ã®è¬åº§ãçµ±åçã«å©çšããæ§åãïŒåŠæ ¡çŸå Žã®æå°æ³ã®å€åã確èªãããã
kws <- keywords$Order
for (i in kws){
varname <- paste("kw_", i, sep = "")
appear <- str_detect(jjep$Abst, pattern = keywords[i,7])
appear <- data.frame(as.numeric(appear))
colnames(appear) <- varname
assign(varname, appear)
}
jjep.doi <- jjep$DOI
jjep.res <- dplyr::bind_cols(jjep.doi,
kw_1, kw_2, kw_3, kw_4, kw_5, kw_6, kw_7, kw_8,
kw_9, kw_10, kw_11, kw_12, kw_13, kw_14, kw_15,
kw_16, kw_17, kw_18, kw_19, kw_20, kw_21, kw_22,
kw_23, kw_24, kw_25, kw_26, kw_27, kw_28, kw_29,
kw_30, kw_31, kw_32, kw_33, kw_34, kw_35, kw_36,
kw_37, kw_38, kw_39, kw_40, kw_41, kw_42, kw_43,
kw_44, kw_45, kw_46, kw_47, kw_48, kw_49, kw_50,
kw_51, kw_52, kw_53, kw_54, kw_55, kw_56, kw_57,
kw_58, kw_59, kw_60, kw_61, kw_62, kw_63, kw_64,
kw_65, kw_66, kw_67, kw_68, kw_69, kw_70, kw_71,
kw_72, kw_73, kw_74, kw_75, kw_76, kw_77, kw_78,
kw_79, kw_80, kw_81, kw_82, kw_83, kw_84, kw_85,
kw_86, kw_87, kw_88, kw_89, kw_90, kw_91, kw_92,
kw_93, kw_94, kw_95, kw_96, kw_97, kw_98, kw_99,
kw_100, kw_101, kw_102, kw_103, kw_104, kw_105,
kw_106, kw_107, kw_108, kw_109, kw_110, kw_111,
kw_112, kw_113, kw_114, kw_115, kw_116, kw_117,
kw_118, kw_119, kw_120, kw_121, kw_122, kw_123,
kw_124, kw_125, kw_126, kw_127, kw_128, kw_129,
kw_130, kw_131, kw_132, kw_133, kw_134, kw_135,
kw_136, kw_137, kw_138, kw_139, kw_140, kw_141,
kw_142, kw_143, kw_144, kw_145, kw_146, kw_147,
kw_148, kw_149, kw_150, kw_151, kw_152, kw_153,
kw_154, kw_155, kw_156, kw_157, kw_158, kw_159,
kw_160, kw_161, kw_162, kw_163, kw_164, kw_165,
kw_166, kw_167, kw_168, kw_169, kw_170, kw_171,
kw_172, kw_173, kw_174, kw_175, kw_176, kw_177,
kw_178, kw_179, kw_180, kw_181, kw_182, kw_183,
kw_184, kw_185, kw_186, kw_187, kw_188, kw_189)
jjep.res$sum <- jjep.res %>% select(contains("kw_")) %>% rowSums
write.csv(jjep.res, "../Tagged/jjep_tag.csv") # DOIãšã¿ã°ã®ããŒã¿ãä¿å
# æŸãããã®
jjep.doi.kw <- jjep.res %>% dplyr::filter(sum > 0)
jjep.doi.kw <- jjep.doi.kw[c(1)]
colnames(jjep.doi.kw) <- c("DOI")
jjep.abst.kw_ <- jjep[c("DOI", "Abst")]
jjep.abst.kw <- dplyr::inner_join(jjep.doi.kw, jjep.abst.kw_, by = "DOI")
write.csv(jjep.abst.kw, "../kakunin/jjep_abst_kw.csv")
# æŸããªãã£ããã®
# æŸãããã®
jjep.doi.zero <- jjep.res %>% dplyr::filter(sum == 0)
jjep.doi.zero <- jjep.doi.zero[c(1)]
colnames(jjep.doi.zero) <- c("DOI")
jjep.abst.zero_ <- jjep[c("DOI", "Abst")]
jjep.abst.zero <- dplyr::inner_join(jjep.doi.zero, jjep.abst.zero_, by = "DOI")
write.csv(jjep.abst.zero, "../kakunin/jjep_abst_zero.csv")
jset <- read.csv("../Data_nkf/JSET_ABST.csv") # æè²å·¥åŠäŒè«æèª
head(jset)
## X Journal Year Volume Number Page DOI Class Incld
## 1 1 JSET 2022 46 4 46135 jjet.46135 ç·èª¬ åé
## 2 2 JSET 2022 46 4 46136 jjet.46136 屿 åé
## 3 3 JSET 2022 46 4 46021 jjet.46021 è«æ åé
## 4 4 JSET 2022 46 4 46022 jjet.46022 è«æ åé
## 5 5 JSET 2022 46 4 46024 jjet.46024 è«æ åé
## 6 6 JSET 2022 46 4 46032 jjet.46032 è«æ åé
## JYVNP
## 1 JSET_2022_46_4_46135
## 2 JSET_2022_46_4_46136
## 3 JSET_2022_46_4_46021
## 4 JSET_2022_46_4_46022
## 5 JSET_2022_46_4_46024
## 6 JSET_2022_46_4_46032
## Abst
## 1 æ¬çš¿ã§ã¯ïŒæè²å·¥åŠã«ããããªã³ã©ã€ã³æè²ã®ç ç©¶ååãæŠèŠ³ããããšãç®çãšããïŒãŸãïŒãªã³ã©ã€ã³æè²ã«é¢é£ããç ç©¶ã®ããŒã¯ãŒããšããŠïŒé éæè²ïŒe ã©ãŒãã³ã°ïŒãã¬ã³ãã£ããã©ãŒãã³ã°ïŒãªã³ã©ã€ã³æè²ã«çŠç¹ãçµãïŒæµ·å€äžŠã³ã«æ¥æ¬ã®ç ç©¶ååã«ã€ããŠãŸãšããïŒæ¬¡ã«ïŒæ¥æ¬ã®é«çæè²ã®ãªã³ã©ã€ã³åã10幎ããšã«åãïŒ1990幎代ã黿æïŒ2000幎代ãçºå±æïŒ2010å¹Žä»£ãæ¡åŒµæïŒ2020幎以éã驿°æãšãïŒãªã³ã©ã€ã³æè²ã«é¢ããç ç©¶ã®å€é·ãèå¯ããïŒ
## 2 COVID-19ã®æææ¡å€§ã®åœ±é¿ã«ããïŒãªã³ã©ã€ã³åŠç¿ãåºç¯ãã€å€§èŠæš¡ã«å®æœãããäžã§ïŒãã®å©ç¹ãåºãåšç¥ãããããã«ãªã£ãïŒããã«äŒŽãïŒãªã³ã©ã€ã³åŠç¿ãšå¯Ÿé¢åŠç¿ãïŒãããã¯ïŒåæååŠç¿ãšéåæååŠç¿ã广çã«çµã¿åããããã¬ã³ãã£ããã©ãŒãã³ã°ã¯ïŒãæè²ã®ãã¥ãŒããŒãã«ããšããŠæ¹ããŠæ³šç®ãããŠããïŒãã¬ã³ãã£ããã©ãŒãã³ã°ã«ããææéçšãæé©åãåŠç¿å¹æãåäžããæè²å®è·µã¯åœå
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kws <- keywords$Order
for (i in kws){
varname <- paste("kw_", i, sep = "")
appear <- str_detect(jset$Abst, pattern = keywords[i,7])
appear <- data.frame(as.numeric(appear))
colnames(appear) <- varname
assign(varname, appear)
}
jset.doi <- jset$DOI
jset.res <- dplyr::bind_cols(jset.doi,
kw_1, kw_2, kw_3, kw_4, kw_5, kw_6, kw_7, kw_8,
kw_9, kw_10, kw_11, kw_12, kw_13, kw_14, kw_15,
kw_16, kw_17, kw_18, kw_19, kw_20, kw_21, kw_22,
kw_23, kw_24, kw_25, kw_26, kw_27, kw_28, kw_29,
kw_30, kw_31, kw_32, kw_33, kw_34, kw_35, kw_36,
kw_37, kw_38, kw_39, kw_40, kw_41, kw_42, kw_43,
kw_44, kw_45, kw_46, kw_47, kw_48, kw_49, kw_50,
kw_51, kw_52, kw_53, kw_54, kw_55, kw_56, kw_57,
kw_58, kw_59, kw_60, kw_61, kw_62, kw_63, kw_64,
kw_65, kw_66, kw_67, kw_68, kw_69, kw_70, kw_71,
kw_72, kw_73, kw_74, kw_75, kw_76, kw_77, kw_78,
kw_79, kw_80, kw_81, kw_82, kw_83, kw_84, kw_85,
kw_86, kw_87, kw_88, kw_89, kw_90, kw_91, kw_92,
kw_93, kw_94, kw_95, kw_96, kw_97, kw_98, kw_99,
kw_100, kw_101, kw_102, kw_103, kw_104, kw_105,
kw_106, kw_107, kw_108, kw_109, kw_110, kw_111,
kw_112, kw_113, kw_114, kw_115, kw_116, kw_117,
kw_118, kw_119, kw_120, kw_121, kw_122, kw_123,
kw_124, kw_125, kw_126, kw_127, kw_128, kw_129,
kw_130, kw_131, kw_132, kw_133, kw_134, kw_135,
kw_136, kw_137, kw_138, kw_139, kw_140, kw_141,
kw_142, kw_143, kw_144, kw_145, kw_146, kw_147,
kw_148, kw_149, kw_150, kw_151, kw_152, kw_153,
kw_154, kw_155, kw_156, kw_157, kw_158, kw_159,
kw_160, kw_161, kw_162, kw_163, kw_164, kw_165,
kw_166, kw_167, kw_168, kw_169, kw_170, kw_171,
kw_172, kw_173, kw_174, kw_175, kw_176, kw_177,
kw_178, kw_179, kw_180, kw_181, kw_182, kw_183,
kw_184, kw_185, kw_186, kw_187, kw_188, kw_189)
jset.res$sum <- jset.res %>% select(contains("kw_")) %>% rowSums
write.csv(jset.res, "../Tagged/jset_tag.csv") # DOIãšã¿ã°ã®ããŒã¿ãä¿å
# æŸãããã®
jset.doi.kw <- jset.res %>% dplyr::filter(sum > 0)
jset.doi.kw <- jset.doi.kw[c(1)]
colnames(jset.doi.kw) <- c("DOI")
jset.abst.kw_ <- jset[c("DOI", "Abst")]
jset.abst.kw <- dplyr::inner_join(jset.doi.kw, jset.abst.kw_, by = "DOI")
write.csv(jset.abst.kw, "../kakunin/jset_abst_kw.csv")
# æŸããªãã£ããã®
# æŸãããã®
jset.doi.zero <- jset.res %>% dplyr::filter(sum == 0)
jset.doi.zero <- jset.doi.zero[c(1)]
colnames(jset.doi.zero) <- c("DOI")
jset.abst.zero_ <- jset[c("DOI", "Abst")]
jset.abst.zero <- dplyr::inner_join(jset.doi.zero, jset.abst.zero_, by = "DOI")
write.csv(jset.abst.zero, "../kakunin/jset_abst_zero.csv")
rjem <- read.csv("../Data_nkf/RJEM_ABST.csv") # æè²æ¹æ³åŠç ç©¶
head(rjem)
## X Journal Year Volume Number Page DOI Class Incld
## 1 1 RJEM 2022 47 1 1 nasemjournal.47.0_1 è«æ åé
## 2 2 RJEM 2022 47 1 13 nasemjournal.47.0_13 è«æ åé
## 3 3 RJEM 2022 47 1 25 nasemjournal.47.0_25 è«æ åé
## 4 4 RJEM 2022 47 1 35 nasemjournal.47.0_35 è«æ åé
## 5 5 RJEM 2022 47 1 47 nasemjournal.47.0_47 è«æ åé
## 6 6 RJEM 2021 46 1 1 nasemjournal.46.0_1 è«æ åé
## JYVNP
## 1 RJEM_2022_47_1
## 2 RJEM_2022_47_13
## 3 RJEM_2022_47_25
## 4 RJEM_2022_47_35
## 5 RJEM_2022_47_47
## 6 RJEM_2021_46_1
## Abst
## 1 æ¬ç ç©¶ã¯ïŒåé¡è§£æ±ºåŠç¿ã«ãããåã©ãå士ã®è°è«ã«çç®ãïŒç€ŸäŒãåµé ããæå¿ã«éãããäž»äœçãªäŸ¡å€èª¿æŽã®éçšã®æ§çžãšæç«èŠå ãè§£æããããšãç®çãšããŠïŒéèªèšé²ã«ããšã¥ãææ¥åæãè¡ã£ãã åæå¯Ÿè±¡ã¯ïŒã察ç«ãšåæããå¹çãšå
¬æ£ãã®èŠæ¹ãèãæ¹ãé€ãããšãããããšããïŒäžåŠæ ¡ïŒå¹Žç€ŸäŒç§å
¬æ°ã®å®è·µã§ãããæ¬å®è·µã¯ïŒå°åã®å¹¹ç·éè·¯æ¡åŒµãšæ©éæ©èšçœ®ãææãšããŠãããåç¯åãã«ããææ¥ã®å±ééçšãæŽçããäžã§ïŒçޝç©çžå¯ŸåºŠæ°ã°ã©ãã«ããè°è«ã«åºçŸãããå¹çããšãå
¬æ£ãã®äŸ¡å€ã®å€é·ãå¯èŠåãïŒçºèšè§£éã«ãã䟡å€èª¿æŽã®å
·äœãšèŠå ãèå¯ããã åæããïŒæ¬æã®è°è«ã«ãããïŒå¹çâå
¬æ£âçžäºã®é¢é£âå
¬æ£âçžäºã®é¢é£âå
¬æ£ãšãã䟡å€ã®å€é·ãæããã«ãªã£ããçåŸã¯ïŒçŽæ¥ã«èŠèãããåœäºè
ã®å£°ã代åŒããŠïŒç€ŸäŒç決å®ã«ãããéèŠãªäŸ¡å€ãè°è«ã«åŒã³æ»ãïŒåœäºè
ã®å¿æ
ã䟡å€ã®éã¿ã«ãå¯ãæ·»ã£ã䟡å€èª¿æŽãè¡ã£ãŠããããšã瀺ããããããã«ïŒç€ŸäŒçæææ±ºå®ã§ã®äŸ¡å€ã®ä»£åŒã¯ïŒæå®€ãšããæ¬äŒŒçãªç€ŸäŒç©ºéã§ãã£ãŠãïŒã©ã®äŸ¡å€ãèæ
®ãã¹ããã«ã€ããŠã®ææã®è¡šæã§ãããšåæã«ïŒä»è
ã®å©å®³ãå·Šå³ãã責任ã®åæã§ããããã®ç¹ã§ïŒæ¬å®è·µã§ã®è°è«ã¯ãããã瀟äŒãåµé ããããšããæå¿ã«éãããŠãããšèããããã 以äžããïŒåé¡è§£æ±ºåŠç¿ã«ããã䟡å€èª¿æŽã¯ïŒåœäºè
ã®å
±æççè§£ãšããèŠå ã«ãã£ãŠïŒäŸ¡å€ã®éã¿ã®åãçŽãã䌎ãïŒç€ŸäŒåµé ã®æå¿ã«éãããããšã瀺ãããã
## 2 æ¬çš¿ã®ç®çã¯ïŒåœéãã«ãã¬ã¢ïŒIBïŒæè²ã®å²åŠçãªåºç€ã圢æãããšãããããŒã¿ãŒãœã³ã®è©äŸ¡èгãïŒåœŒãèããæè²ã®ç®æšãšã«ãªãã¥ã©ã ãšã®é¢ä¿ã«æ³šç®ããŠæ€èšããããšã§ããã圌ã¯1950幎代åŸåã«ã€ã®ãªã¹ã®ã·ãã¯ã¹ã»ãã©ãŒã æ¹é©ã«æºãã£ãŠããéã«æ¹å€ã®å¯Ÿè±¡ãšããŠããã詊éšïŒexaminationïŒããïŒ1960幎代åŸå以éïŒIB ã®ã«ãªãã¥ã©ã éçºæã«ã¯æè²ã®ç®æšãå
·äœåããææ®µãšããŠèšè¿°ããããã®è»¢æã«æ³šç®ãïŒåœŒã®æè²ã®ç®æšã®å
容åã³æè²ã®ç®æšãšã詊éšããšã®é¢ä¿ãïŒèäœãããšã«åæããã æè²ã«æºããéçšã®äžã§ïŒããŒã¿ãŒãœã³ã¯ãèªèº«ãšèªèº«ãçãã瀟äŒãçè§£ãïŒç€ŸäŒãšé¢ããïŒèªèº«ãçããäžçãæ¥œããããšã®æè²ã®ç®æšãäžè²«ããŠæ²ããŠããããã®æè²ã®ç®æšããå°ãåºããã圌ã®è©äŸ¡èгã¯ïŒãèªå·±èªèã®æ©äŒããšããŠã®è©äŸ¡ã§ããããããåœåïŒåœŒãçšããã詊éšãã®èªå¥ã¯ïŒãã®è©äŸ¡èгã ååã«è¡šãããšãã§ããªãã£ãã圌ã¯IB ã®ã«ãªãã¥ã©ã éçºã«æºããäžã§ãè©äŸ¡ïŒassessmentïŒãã®èªå¥ãç²åŸãïŒæè²ã®ç®æšãšåèŽããè©äŸ¡èгãã«ãªãã¥ã©ã ã«æç€ºãïŒå¶åºŠçã«æ§ç¯ããŠãã£ãã è©äŸ¡ã®ãã€ã¹ãã€ã¯ã¹åãåé¡ãšãªãäžïŒåãããã®ã¯å®éã«æè²ã«æºããæåž«ãšåŠã¶çåŸã®è©äŸ¡èгã§ãããæè²ã®ç®æšã«åºã¥ãïŒçåŸã®åŠç¿ãšæåž«ã®æå°ïŒè©äŸ¡ã®ããã¿ãæ§ç¯ããIB æè²ã«ãããŠïŒæåž«ãçåŸãããã«è©äŸ¡ãæããŠããã®ãã«ã€ããŠã®æ€èšãïŒããããè©äŸ¡å®è·µã®ããã®ä»åŸã®éèŠãªèª²é¡ãšãªãã ããã
## 3 æ¬è«èã®ç®çã¯ïŒãã«ããŠã«ãã£ãŠç€ºããããç·Žç¿ãã®æçŸ©ãçŸè±¡åŠçèŠåº§ãã忀èšããããšã«ãã£ãŠïŒç·Žç¿ã®æ¬æ¥çæçŸ©ãæããã«ããããšã§ãã£ãããã®ç®çã®éæã®ããã«ãŸãïŒãã«ããŠã人éåŠçãªèŠåº§ããèŠããç·Žç¿ã®ç²Ÿç¥ãã®ããããæŽçããããšã«ãã£ãŠãã«ããŠãæããã«ãããç·Žç¿ãã®æè²çæçŸ©ã確èªãïŒããã«ïŒããã«å¯Ÿããå
è¡ç ç©¶ãæŠèŠ³ããããšã«ãã£ãŠãç·Žç¿ã®ç²Ÿç¥ãã«ãããæ®ããã課é¡ã確èªãããæ¬¡ã«ïŒãã«ããŠã®ã人éåŠçã«èŠãæè²åŠãã«ãããçŸè±¡åŠïŒãšããããããµãŒã«çŸè±¡åŠã«ãããçºçççŸè±¡åŠã®äœçœ®ã¥ãã確èªãïŒãã®çºçççŸè±¡åŠã®èŠåº§ããæããªããããç·Žç¿ãã®æè²çæçŸ©ãæ€èšããããããµãŒã«çŸè±¡åŠã®çºççåæã§ã¯ïŒãè±æ§ç¯ãïŒAbbauïŒãšåŒã°ããæèåæã®æ¹æ³ãçšãããïŒããã«ãã£ãŠå¯Ÿè±¡æå³ã®åºã¥ãæ§é ã®ãã¡ïŒäžå±€ã鮿ããå Žåã«ãäžå±€ãæãç«ã€ãã©ãããè§£æãããããã®ãããªçºççåæãšããŠã®ãç·Žç¿ãã¯èªå·±ã®èªå·±èªèº«ãšã®å¯Ÿè©±ã®ãããªæ§é ããã£ãŠãããããã«ãããŠãç·Žç¿ãã«ã¯èªå·±ãç·Žç¿å
容ãšã察話ãããªããïŒãã®ãããæ¹ãïŒBewegungsweiseïŒã®èªåšåã®æ¥µã¿ãç¡éã«è¿œç©¶ãããšããæå³ã§ã®è±ç®ççãªå
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é¢ã®èªç±ãã«è³ãããã®æè²ãååšããŠããããšã確èªãããã
## 4 æ¬éè¯å©ã¯ïŒæ°å³ç»æè²äŒã«å±ããŠå±±æ¬éŒã®èªç±ç»æè²ãæ¹å€ãïŒåºç€çè«ã«ããã€ã€åã©ãèªèº«ã詊è¡é¯èª€ããŠãã®ç¥èæèœã身ã«ã€ããŠãããåµäœäž»çŸ©å³ç»æè²ããæå±ãã人ç©ã§ãããæ¬ç ç©¶ã§ã¯ïŒæ¬éã®å³ç»æè²ã«é¢ããææ³ãåºã«ïŒã©ã®ãããªè£çž«æè²è«ãæ§æ³ããã®ããæããã«ããããããŠïŒãã®è£çž«æè²è«ãè£çž«æè²æ¹é©ã®äžã§ïŒèžè¡ãšã®é¢é£ãããã®æçŸ©ãåãçŽãç³»èã«å±ããããšãææããã æ¬éã®ãåµé 䞻矩è£çž«æè²ãè«ã®ç¹è²ã¯ïŒã€ãããïŒã€ç®ã¯ïŒç£æ¥åœå®¶ã建èšããæèœãšããŠïŒä»ã®å·¥äœãšè£çž«ãåæ Œã®ãã®ãšããŠæããããšã§ãããè£çž«ãå®¶åºå
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¬çãªå·¥äœãšããŠæãçŽãããïŒã€ç®ã¯ïŒåè£ã»æŽè£ã®åºå¥ãªãïŒåœ¢è±¡æè²ã®ïŒã€ãšããŠè£çž«ãæããããšã§ããã 圢象æè²ãšã¯ïŒå³ç»ãè£çž«ïŒç¿åãªã©åœ¢è±¡ãæ±ãæç§ãã¹ãŠãå
æããæè²ã§ããããããŠïŒã€ç®ã¯ïŒè²åœ©è«ãéèŠããè£çž«æè²ãææ¡ããããšã§ãããè²åœ©è«ãéèŠããããšã§ïŒåã©ãèªèº«ã峿¡äœæããããšã®å¯èœæ§ã瀺ãããæ¬éã®è£çž«æè²è«ã¯ïŒãã·ã§ããªã¹ãã£ãã¯ãªææ³ãåå°ãšãã€ã€ãïŒè£çž«ãšããåéã«åããããã®ã¥ããäžè¬ãšããŠæ§æ³ãããããšã«ããïŒåœæã®å®è·µå®¶ã®ææ³ãšã¯ç°ãªãè£çž«æè²ã®åœ¢ã瀺ããŠããã
## 5 æ¬ç ç©¶ã®ç®çã¯ïŒããŒã¿ãŒãŒã³ã«ãããèªåŸçæè²ç§åŠã®æ§æ³ã®ç¹è³ªãšéçãæããã«ããããšã«ããã ãã®éïŒåœŒã®æè²åŠçäºå®ç ç©¶ãšåŠè¡çãªæåž«æè²ãžã®åçµã«çç®ãïŒæè²åŠãç§åŠãšããŠèªåŸãããããšã«äœãæåŸ
ãããŠããã®ãã«è«ç©¶ãããæ¬ç ç©¶ã§ã¯ïŒç¬¬äžã«ããŒã¿ãŒãŒã³ã«ãããæè²åŠã®ç§åŠçæ§æ Œãæããã«ãïŒç¬¬äºã«æè²åŠçäºå®ç ç©¶ãšåŠæ ¡æ¹é©ãšã®é¢ä¿ãæ€èšããäžã§ïŒç¬¬äžã«æè²åŠçäºå®ç ç©¶ãæããããšããåŠè¡çãªæåž«æè²ãžã®åçµãè«ããã æ¬ç ç©¶ãéããŠïŒããŒã¿ãŒãŒã³ã®æè²ç§åŠã®æ§æ³ã®ç¹è³ªãšããŠïŒâ æè²åŠã粟ç¥ç§åŠçæè²åŠãããå®èšŒäž»çŸ©çæè²åŠãããè·é¢ãåã£ãçŸå®ç§åŠãšããŠæããããšïŒâ¡æè²åŠçäºå®ç ç©¶ãéããŠåŠè¡çãªæåž«æè²ãšçµã³ã€ããããšïŒâ¢å°æ¥ã®å®è·µã«ã¢ãããŒãããããšã§ãèªç±ã§äžè¬çãªåœæ°åŠæ ¡ããšããåŠæ ¡æ¹é©ã®ç念ãçŸå®åããæããããšããŠããããšïŒãæãããšãªã£ãã仿¹ã§ïŒãã®éçãšããŠïŒååšãããã®ããååšãã¹ããã®ãå°ãåºããããªåŸªç°æ§ãæããæèæ çµã¿ãä¹ãè¶ããããªãããšãææããã ããŒã¿ãŒãŒã³ãæåž«æè²ãå«ãã æè²åŠã®å°çšã§åŠæ ¡æ¹é©ã«ã¢ãããŒãããŠããããšããïŒåŠæ ¡æ¹é©ãè«ããè«ç¹ãšããŠïŒåŠãšããŠã®æè²åŠã®ããæ¹ãåãããããšã®éèŠæ§ã«èšåããã
## 6 æ¬çš¿ã¯ïŒãã€ã¹ã»ãµãã©ãŒã«ãã圢æçã¢ã»ã¹ã¡ã³ãè«ãæ€èšãããã®ã§ãããè¿å¹ŽïŒè©äŸ¡æŽ»åãéããŠïŒæåž«ãšåŠç¿è
ãååçã«åŠç¿ãæ¹åããŠãã圢æçã¢ã»ã¹ã¡ã³ãã®èãæ¹ãè¡ç®ãéããŠãããããããèãæ¹ã®çè«çã«ãŒãã®äžã€ã¯ïŒãµãã©ãŒã«ãã圢æçã¢ã»ã¹ã¡ã³ãè«ïŒ1989幎ïŒã«ãããšãããããããïŒæ°ã¯ïŒåœ¢æçã¢ã»ã¹ã¡ã³ãã®èãæ¹ãäžççã«åºããã«ã€ããŠïŒæšä»ã®åœ¢æçã¢ã»ã¹ã¡ã³ãã®è«èª¿ã«å¯ŸããŠã©ãã£ã«ã«ãªæ¹å€ãå±éãå§ããŠãããããã§æ¬çš¿ã¯ïŒãããããã©ããã·ã«ã«ãªç¶æ³ã«éã¿ãŠïŒïŒ1ïŒâ
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ã®éèçŒãé¬ç£šããããšã䞻軞ãšããã¢ãããŒãã«ãã£ãŠïŒåœ¢æçã¢ã»ã¹ã¡ã³ãè«ãåãæãããšãã詊ã¿ãšããŠæããããšãã§ããã
kws <- keywords$Order
for (i in kws){
varname <- paste("kw_", i, sep = "")
appear <- str_detect(rjem$Abst, pattern = keywords[i,7])
appear <- data.frame(as.numeric(appear))
colnames(appear) <- varname
assign(varname, appear)
}
rjem.doi <- rjem$DOI
rjem.res <- dplyr::bind_cols(rjem.doi,
kw_1, kw_2, kw_3, kw_4, kw_5, kw_6, kw_7, kw_8,
kw_9, kw_10, kw_11, kw_12, kw_13, kw_14, kw_15,
kw_16, kw_17, kw_18, kw_19, kw_20, kw_21, kw_22,
kw_23, kw_24, kw_25, kw_26, kw_27, kw_28, kw_29,
kw_30, kw_31, kw_32, kw_33, kw_34, kw_35, kw_36,
kw_37, kw_38, kw_39, kw_40, kw_41, kw_42, kw_43,
kw_44, kw_45, kw_46, kw_47, kw_48, kw_49, kw_50,
kw_51, kw_52, kw_53, kw_54, kw_55, kw_56, kw_57,
kw_58, kw_59, kw_60, kw_61, kw_62, kw_63, kw_64,
kw_65, kw_66, kw_67, kw_68, kw_69, kw_70, kw_71,
kw_72, kw_73, kw_74, kw_75, kw_76, kw_77, kw_78,
kw_79, kw_80, kw_81, kw_82, kw_83, kw_84, kw_85,
kw_86, kw_87, kw_88, kw_89, kw_90, kw_91, kw_92,
kw_93, kw_94, kw_95, kw_96, kw_97, kw_98, kw_99,
kw_100, kw_101, kw_102, kw_103, kw_104, kw_105,
kw_106, kw_107, kw_108, kw_109, kw_110, kw_111,
kw_112, kw_113, kw_114, kw_115, kw_116, kw_117,
kw_118, kw_119, kw_120, kw_121, kw_122, kw_123,
kw_124, kw_125, kw_126, kw_127, kw_128, kw_129,
kw_130, kw_131, kw_132, kw_133, kw_134, kw_135,
kw_136, kw_137, kw_138, kw_139, kw_140, kw_141,
kw_142, kw_143, kw_144, kw_145, kw_146, kw_147,
kw_148, kw_149, kw_150, kw_151, kw_152, kw_153,
kw_154, kw_155, kw_156, kw_157, kw_158, kw_159,
kw_160, kw_161, kw_162, kw_163, kw_164, kw_165,
kw_166, kw_167, kw_168, kw_169, kw_170, kw_171,
kw_172, kw_173, kw_174, kw_175, kw_176, kw_177,
kw_178, kw_179, kw_180, kw_181, kw_182, kw_183,
kw_184, kw_185, kw_186, kw_187, kw_188, kw_189)
rjem.res$sum <- rjem.res %>% select(contains("kw_")) %>% rowSums
write.csv(rjem.res, "../Tagged/rjem_tag.csv") # DOIãšã¿ã°ã®ããŒã¿ãä¿å
# æŸãããã®
rjem.doi.kw <- rjem.res %>% dplyr::filter(sum > 0)
rjem.doi.kw <- rjem.doi.kw[c(1)]
colnames(rjem.doi.kw) <- c("DOI")
rjem.abst.kw_ <- rjem[c("DOI", "Abst")]
rjem.abst.kw <- dplyr::inner_join(rjem.doi.kw, rjem.abst.kw_, by = "DOI")
write.csv(rjem.abst.kw, "../kakunin/rjem_abst_kw.csv")
# æŸããªãã£ããã®
# æŸãããã®
rjem.doi.zero <- rjem.res %>% dplyr::filter(sum == 0)
rjem.doi.zero <- rjem.doi.zero[c(1)]
colnames(rjem.doi.zero) <- c("DOI")
rjem.abst.zero_ <- rjem[c("DOI", "Abst")]
rjem.abst.zero <- dplyr::inner_join(rjem.doi.zero, rjem.abst.zero_, by = "DOI")
write.csv(rjem.abst.zero, "../kakunin/rjem_abst_zero.csv")
# ããŒã¯ãŒãã®è¡å
kw.code <- c("kw_1", "kw_2", "kw_3", "kw_4", "kw_5", "kw_6", "kw_7", "kw_8",
"kw_9", "kw_10", "kw_11", "kw_12", "kw_13", "kw_14", "kw_15",
"kw_16", "kw_17", "kw_18", "kw_19", "kw_20", "kw_21", "kw_22",
"kw_23", "kw_24", "kw_25", "kw_26", "kw_27", "kw_28", "kw_29",
"kw_30", "kw_31", "kw_32", "kw_33", "kw_34", "kw_35", "kw_36",
"kw_37", "kw_38", "kw_39", "kw_40", "kw_41", "kw_42", "kw_43",
"kw_44", "kw_45", "kw_46", "kw_47", "kw_48", "kw_49", "kw_50",
"kw_51", "kw_52", "kw_53", "kw_54", "kw_55", "kw_56", "kw_57",
"kw_58", "kw_59", "kw_60", "kw_61", "kw_62", "kw_63", "kw_64",
"kw_65", "kw_66", "kw_67", "kw_68", "kw_69", "kw_70", "kw_71",
"kw_72", "kw_73", "kw_74", "kw_75", "kw_76", "kw_77", "kw_78",
"kw_79", "kw_80", "kw_81", "kw_82", "kw_83", "kw_84", "kw_85",
"kw_86", "kw_87", "kw_88", "kw_89", "kw_90", "kw_91", "kw_92",
"kw_93", "kw_94", "kw_95", "kw_96", "kw_97", "kw_98", "kw_99",
"kw_100", "kw_101", "kw_102", "kw_103", "kw_104", "kw_105",
"kw_106", "kw_107", "kw_108", "kw_109", "kw_110", "kw_111",
"kw_112", "kw_113", "kw_114", "kw_115", "kw_116", "kw_117",
"kw_118", "kw_119", "kw_120", "kw_121", "kw_122", "kw_123",
"kw_124", "kw_125", "kw_126", "kw_127", "kw_128", "kw_129",
"kw_130", "kw_131", "kw_132", "kw_133", "kw_134", "kw_135",
"kw_136", "kw_137", "kw_138", "kw_139", "kw_140", "kw_141",
"kw_142", "kw_143", "kw_144", "kw_145", "kw_146", "kw_147",
"kw_148", "kw_149", "kw_150", "kw_151", "kw_152", "kw_153",
"kw_154", "kw_155", "kw_156", "kw_157", "kw_158", "kw_159",
"w_160", "kw_161", "kw_162", "kw_163", "kw_164", "kw_165",
"kw_166", "kw_167", "kw_168", "kw_169", "kw_170", "kw_171",
"kw_172", "kw_173", "kw_174", "kw_175", "kw_176", "kw_177",
"kw_178", "kw_179", "kw_180", "kw_181", "kw_182", "kw_183",
"kw_184", "kw_185", "kw_186", "kw_187", "kw_188", "kw_189")
kw.keyword <- data.frame(keywords$keyword)
colnames(kw.keyword) <- c("Keyword")
rownames(kw.keyword) <- kw.code
# æè²åŠç ç©¶
jjer.kw.freq <- data.frame(colSums(jjer.res[c(2:190)]))
colnames(jjer.kw.freq) <- c("JJER")
# æè²å¿çåŠç ç©¶
jjep.kw.freq <- data.frame(colSums(jjep.res[c(2:190)]))
colnames(jjep.kw.freq) <- c("JJEP")
# æè²å·¥åŠäŒè«æèª
jset.kw.freq <- data.frame(colSums(jset.res[c(2:190)]))
colnames(jset.kw.freq) <- c("JSET")
# æè²æ¹æ³åŠç ç©¶
rjem.kw.freq <- data.frame(colSums(rjem.res[c(2:190)]))
colnames(rjem.kw.freq) <- c("RJEM")
# ãŸãšã
kw.freq <- dplyr::bind_cols(kw.keyword,
jjer.kw.freq, jjep.kw.freq,
jset.kw.freq, rjem.kw.freq)
write.xlsx(kw.freq, "../Tagged/kw_freq.xlsx")
DT::datatable(kw.freq)
## user system elapsed
## 1.919 0.141 2.317