Sentiment twitter Kursus Prakerja
Realrapplication/Bambangpe
2020-04-24
Seperti yang diketahui tercatat ada sebanyak 5.965.048 pengguna (user) yang melakukan pendaftaran program Kartu Prakerja tahap I. Dari jumlah tersebut sebanyak 168.111 orang berhasil lolos seleksi penerima program kartu prakerja gelombang I.Nantinya setiap peserta akan mendapat paket manfaat senilai Rp 3,55 juta. Adapun paket bantuan tersebut terdiri dari bantuan pelatihan sebesar Rp 1 juta dan insentif pasca pelatihan sebesar Rp 600.000 per bulan untuk empat bulan, serta insentif survei bekerja senilai total Rp 150.000.
Dikutip dari situs prakerja.go.id (16/4), 7 nama startup tersebut yakni Tokopedia, Bukalapak, Pintaria, Pijar Mahir, MauBelajarApa, Skill Academy, dan Sekolahmu.
Disini akan diambil beberapa kursus: Pintaria, Pijar Mahir, MauBelajarApa, Skill Academy/Ruangguru, dan Sekolahmu, bagaimana reaksi netizen terhadap akun twitter mereka?
Apakah benar mereka yang berhasil lolos seleksi penerima program kartu prakerja gelombang I memanfaatkan untuk daftar kursus prakerja?Library
library(twitteR)## Warning: package 'twitteR' was built under R version 3.5.3library(ROAuth)## Warning: package 'ROAuth' was built under R version 3.5.3library(httr)## Warning: package 'httr' was built under R version 3.5.3library(plyr)## Warning: package 'plyr' was built under R version 3.5.2##
## Attaching package: 'plyr'## The following object is masked from 'package:twitteR':
##
## idlibrary(stringr)## Warning: package 'stringr' was built under R version 3.5.2library(ggplot2)## Warning: package 'ggplot2' was built under R version 3.5.3Twitter Authentication
## [1] "Using direct authentication"Grab latest tweets
Pintaria <- searchTwitter("@pintariaid",n = 150)## Warning in doRppAPICall("search/tweets", n, params = params, retryOnRateLimit =
## retryOnRateLimit, : 150 tweets were requested but the API can only return 148Pijarmahir <- searchTwitter("@Pijarmahir",n = 150)## Warning in doRppAPICall("search/tweets", n, params = params, retryOnRateLimit =
## retryOnRateLimit, : 150 tweets were requested but the API can only return 54Skillacademy <- searchTwitter("@skillacademy_id",n = 150)
Maubelajarapa <- searchTwitter("@MauBelajarApa",n = 150)
Sekolahmu <- searchTwitter("@sekolahmuid",n = 150)## Warning in doRppAPICall("search/tweets", n, params = params, retryOnRateLimit =
## retryOnRateLimit, : 150 tweets were requested but the API can only return 135Loop over tweets and extract text
feed_Pintaria <- laply(Pintaria, function(t) t$getText())
feed_Pijarmahir <- laply(Pijarmahir, function(t) t$getText())
feed_Skillacademy <- laply(Skillacademy , function(t) t$getText())
feed_Maubelajarapa<- laply(Maubelajarapa, function(t) t$getText())
feed_Sekolahmu <- laply(Sekolahmu, function(t) t$getText())score.sentiment <- function(sentences, good_text, bad_text, .progress='none')
{
require(plyr)
require(stringr)
# we got a vector of sentences. plyr will handle a list
# or a vector as an "l" for us
# we want a simple array of scores back, so we use
# "l" + "a" + "ply" = "laply":
scores = laply(sentences, function(sentence, good_text, bad_text) {
# clean up sentences with R's regex-driven global substitute, gsub():
sentence = gsub('[[:punct:]]', '', sentence)
sentence = gsub('[[:cntrl:]]', '', sentence)
sentence = gsub('\\d+', '', sentence)
#to remove emojis
sentence <- iconv(sentence, 'UTF-8', 'ASCII')
sentence = tolower(sentence)
# split into words. str_split is in the stringr package
word.list = str_split(sentence, '\\s+')
# sometimes a list() is one level of hierarchy too much
words = unlist(word.list)
# compare our words to the dictionaries of positive & negative terms
pos.matches = match(words, good_text)
neg.matches = match(words, bad_text)
# match() returns the position of the matched term or NA
# we just want a TRUE/FALSE:
pos.matches = !is.na(pos.matches)
neg.matches = !is.na(neg.matches)
# and conveniently enough, TRUE/FALSE will be treated as 1/0 by sum():
score = sum(pos.matches) - sum(neg.matches)
return(score)
}, good_text, bad_text, .progress=.progress )
scores.df = data.frame(score=scores, text=sentences)
return(scores.df)
}Retreive scores and add candidate name
##
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|======================================================================| 100%Merge into one dataframe for plotting
plotdat <- rbind(theSkillacademy,thePijarmahir,thePintaria,theMaubelajarapa,theSekolahmu)Cut the text, just gets in the way
plotdat <- plotdat[c("name", "score")]
# Remove neutral values of 0
plotdat <- plotdat[!plotdat$score == 0, ]
# Remove anything less than -3 or greater than 3
plotdat <- plotdat[!plotdat$score > 5, ]
plotdat <- plotdat[!plotdat$score < (-5), ]Nice little quick plot
library(ggplot2)
library(gridExtra)## Warning: package 'gridExtra' was built under R version 3.5.2q1 <- qplot(factor(score), data=plotdat, geom="bar",
fill=factor(name),
xlab = "Sentiment Score")
ep <- plotdat %>%
ggplot(aes(x = score, fill = name)) +
geom_bar(binwidth = 1) +
scale_fill_manual(values = c("#0067F7","#FFFF00", "#CD853F", "#6B8E23","#F70000")) +
theme_classic(base_size = 12) +
scale_x_continuous(name = "Sentiment Score") +
scale_y_continuous(name = "Text count of tweets") +
ggtitle("Sentimen Twitter Kursus Pra Kerja",subtitle = "24 April 2020, Jam 9.00 WIB, Crafted by Bambangpe")## Warning: `geom_bar()` no longer has a `binwidth` parameter. Please use
## `geom_histogram()` instead.theme(axis.title.y = element_text(face="bold", colour="#000000", size=10),
axis.title.x = element_text(face="bold", colour="#000000", size=8),
axis.text.x = element_text(angle=16, vjust=0, size=8))## List of 3
## $ axis.title.x:List of 11
## ..$ family : NULL
## ..$ face : chr "bold"
## ..$ colour : chr "#000000"
## ..$ size : num 8
## ..$ hjust : NULL
## ..$ vjust : NULL
## ..$ angle : NULL
## ..$ lineheight : NULL
## ..$ margin : NULL
## ..$ debug : NULL
## ..$ inherit.blank: logi FALSE
## ..- attr(*, "class")= chr [1:2] "element_text" "element"
## $ axis.title.y:List of 11
## ..$ family : NULL
## ..$ face : chr "bold"
## ..$ colour : chr "#000000"
## ..$ size : num 10
## ..$ hjust : NULL
## ..$ vjust : NULL
## ..$ angle : NULL
## ..$ lineheight : NULL
## ..$ margin : NULL
## ..$ debug : NULL
## ..$ inherit.blank: logi FALSE
## ..- attr(*, "class")= chr [1:2] "element_text" "element"
## $ axis.text.x :List of 11
## ..$ family : NULL
## ..$ face : NULL
## ..$ colour : NULL
## ..$ size : num 8
## ..$ hjust : NULL
## ..$ vjust : num 0
## ..$ angle : num 16
## ..$ lineheight : NULL
## ..$ margin : NULL
## ..$ debug : NULL
## ..$ inherit.blank: logi FALSE
## ..- attr(*, "class")= chr [1:2] "element_text" "element"
## - attr(*, "class")= chr [1:2] "theme" "gg"
## - attr(*, "complete")= logi FALSE
## - attr(*, "validate")= logi TRUEgrid.arrange(q1,ep)
1.Cara melihat grafik, sebelah kanan 0(nol) artinya positif, sebelah kiri 0, artinya negatif.
2.Dari lima tempat kursus tsb, yang terlihat mendapat tanggapan positiv ternyata baru dua yaitu Kursus Skill Academi/Ruangguru,
Dan Kursus Mau Belajar apa
3.Belum kelihatan signifikan jika dilihat cuitan di akun twitter mereka, padahal jumlah peserta yang lolos ada 168 ribu lebih
dan harus menggunakan kesempatan untuk mendaftar kursus(diberi tempo 1 bulan), karena jika tidak akan hangus dananya,
otomatis uang bantuan 600rb/bl selama 4bulan juga tidak akan didapat.