Releases will be numbered with the following semantic versioning format:
<major>.<minor>.<patch>
And constructed with the following guidelines:
BUG FIXES
freq_first_names
cantained a missing (NA
) value that has been removed.
Spotted thanks to Martin Cadek; see issue #34.NEW FEATURES
MINOR FEATURES
IMPROVEMENTS
CHANGES
BUG FIXES
hash_emoticons
had '3' as 'laughing' when it should have been '=3'. This
has been corrected.NEW FEATURES
cliches
added for comparison of common cliche phrases.MINOR FEATURES
hash_nrc_emotion
added as a token to emotion lookup table.CHANGES
profanity_zac_anger
contained 2 regexes marked as UTF-8 strings. These were
dropped.
key_corporate_social_responsibility
contained 5 regexes & 5 tokens marked as
Latin-1 strings. These were pretty apostrophes that were converted to ASCII
apostrophes.
BUG FIXES
hash_lemmas
had the lemma of as
to be a
. This was incorrect (spotted by
Jonathan Bratt).
hash_lemmas
had Spaces before 2 tokens (" furtherst", " skilled") meaning.
This extra white space has been stripped.
The hash_sentiment_senticnett
dictionary contained "sparsely" which is also
contained in hash_valence_shifters
. This term has been dropped from the
hash_sentiment_senticnett
dictionary. See # 12 for more info.
NEW FEATURES
profanity_zac_anger
added to provide a longer list of profane words.
profanity_racist
added to provide a profane list that is specific for
detecting racist terms.
key_regressive_imagery
added to provide R users with access to Colin
Martindale's (1975, 1990) English Regressive Imagery Dictionary (RID). The
Regressive Imagery Dictionary (RID) is a text analysis coding taxonomy that
can be used to measure the degree to which a text is primordial vs.
conceptual.
key_corporate_social_responsibility
added to provide R users with access to
Pencle & Mălăescu's Corporate Social Responsibility (CSR) Dictionary.
MINOR FEATURES
available_data
picks up a regex
argument to search for specific substrings
and return matching rows.IMPROVEMENTS
hash_sentiment_jockers_rinker
now contains the word 'fuckin'. Additionally,
the word 'fucking' has a milder negative value because this word, though often
used as a negator, is also used as a amplifier. By reducing it's weight it
allows more positive words to have more pull but if no polarized words exist
'fucking' will still keep the typical negative direction of the clause.Add the following code to your website.
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