View source: R/limpiar_stopwords.R
limpiar_stopwords | R Documentation |
The two lists - sentiment & topics, are very similar, in that most words are in both lists. However, sentiment analysis is sensitive to negation, so negation cues e.g. "no", "nada" etc. are not removed by the sentiment list. For most purposes, topics are the go-to lists, but care is always advised when removing stop words.
limpiar_stopwords(df, text_var = mention_content, stop_words)
df |
Name of Data Frame or Tibble object |
text_var |
name of the text variable |
stop_words |
"sentiment" or "topics" - sentiment retains negation cues |
stop word list is editable via data("sentiment_stops") or data("topic_stops").
the text variable with stop words from specified list removed
limpiar_examples %>% dplyr::select(mention_content)
limpiar_examples %>% limpiar_stopwords(stop_words = "topics") %>%
dplyr::select(mention_content) %>% limpiar_spaces()
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