library(malaytextr)
There is a data frame of Malay root words that can be used as a dictionary:
head(malayrootwords)
#> Col Word Root Word
#> 1 pengabadian abadi
#> 2 pengabdian abdi
#> 3 pengacaraan acara
#> 4 pengadangan adang
#> 5 pengadilan adil
#> 6 pengairan air
stem_malay()
will find the root words in a dictionary,
in which the malayrootwords
data frame can be used, then it
will remove “extra suffix”“,”prefix” and lastly “suffix”
To stem word “banyaknya”. It will return a data frame with the word “banyaknya” and the stemmed word “banyak”:
stem_malay(word = "banyaknya", dictionary = malayrootwords)
#> 'Root Word' is now returned instead of 'root_word'
#> Col Word Root Word
#> 1 banyaknya banyak
To stem words in a data frame:
<- data.frame(text = c("banyaknya","sangat","terkedu", "pengetahuan"))
x
stem_malay(word = x,
dictionary = malayrootwords,
col_feature1 = "text")
#> 'Root Word' is now returned instead of 'root_word'
#> Col Word Root Word
#> 1 banyaknya banyak
#> 2 sangat sangat
#> 3 terkedu kedu
#> 4 pengetahuan tahu
remove_url will remove all urls found in a string
<- c("test https://t.co/fkQC2dXwnc", "another one https://www.google.com/ to try")
x
remove_url(x)
#> [1] "test " "another one to try"
There is a data frame of Malay stop words:
head(malaystopwords)
#> # A tibble: 6 × 1
#> stopwords
#> <chr>
#> 1 ada
#> 2 sampai
#> 3 sana
#> 4 itu
#> 5 sangat
#> 6 saya
This lexicon includes words that have been labelled as positive or negative. This is useful for tasks like sentiment analysis, which involves determining the overall sentiment expressed in a piece of text. To use the lexicon, process the text and check each word against the lexicon to determine its sentiment. To note, this sentiment lexicon was created based on a general corpus, sourced from news articles
head(sentiment_general)
#> # A tibble: 6 × 2
#> Word Sentiment
#> <chr> <chr>
#> 1 aduan Negative
#> 2 agresif Negative
#> 3 amaran Negative
#> 4 anarki Negative
#> 5 ancaman Negative
#> 6 aneh Negative