Generates valence scores for each row in a given column of text.

score_valence(
 df,
 text_var = Message,
 valence_limits = c(-Inf, Inf),
 remove_terms = NULL,
 highlight = FALSE
)

Arguments

df

A dataframe.

text_var

The variable containing the text to be scored.

valence_limits

Numerical lower and upper bounds for valence scores.

remove_terms

Vector of terms to remove from the Jockers-Rinker valence library.

highlight

Logical indicating whether highlighted text should be returned.

Value

Adds 3 variables to the supplied data: ave_sentiment, word_count, sd.

Examples

score_valence( df = sprinklr_export, text_var = Message, valence_limits = c(-2, 2), remove_terms = c("foo", "bar"), highlight = FALSE )
#> # A tibble: 6,018 × 58 #> message_id UniversalMessageId SocialNetwork SenderUserId SenderScreenName #> <int> <chr> <chr> <chr> <chr> #> 1 1 INSTAGRAM_36_19027908… INSTAGRAM ude_aku ude_aku #> 2 2 INSTAGRAM_36_19027826… INSTAGRAM ude_aku ude_aku #> 3 3 TWITTER_4_10578602917… TWITTER 100818788 pragmaticmom #> 4 4 TWITTER_2_10578458995… TWITTER 2777150217 LAVCPrez #> 5 5 TWITTER_4_10578280142… TWITTER 2366576322 Valley_Vikings #> 6 6 TWITTER_2_10578220833… TWITTER 1723468759 PearceAVID #> 7 7 TWITTER_4_10578180262… TWITTER 328184177 JohnHSandbach #> 8 8 TWITTER_2_10578147941… TWITTER 1515570781 Miriam_A3 #> 9 9 TWITTER_2_10578031519… TWITTER 1449659010 CypressCreekHS #> 10 10 TWITTER_2_10578030531… TWITTER 1449659010 CypressCreekHS #> # … with 6,008 more rows, and 53 more variables: SenderListedName <chr>, #> # SenderProfileImgUrl <chr>, SenderProfileLink <lgl>, #> # Sender Followers Count <dbl>, SenderInfluencerScore <lgl>, SenderAge <lgl>, #> # SenderGender <chr>, Title <chr>, Message <chr>, MessageType <chr>, #> # CreatedTime <dttm>, Language <chr>, LanguageCode <chr>, CountryCode <chr>, #> # MediaTypeList <chr>, Permalink <chr>, Domain <chr>, Retweets <dbl>, #> # Tweet Generator <chr>, Favorites <dbl>, ReceiverId <lgl>, …