EmoTFIDF 1.1.5

A library to extract emotions using two methods, 1- Using lexicon based, counting frequency of emotion2- Integrating TFIDF to add a contextNote that lexicon license is for research purposes only.

EmoTFIDF is an emotion detection library (Lexicon approach) based in the National Research Council Canada (NRC) and this package is for research purposes only. Source: [lexicons for research] (http://sentiment.nrc.ca/lexicons-for-research/)

#This library provides two types of emotions:

1- Lexicon based emotions which counting the frequency of the emotion based on the lexicon 2- Integrating TFIDF to add a context to the emotions.

#Installation

pip install EmoTFIDF

#List of emotions

-fear -anger -anticipation -trust -surprise -positive -negative -sadness -disgust -joy

#Example of usage ##Get emotions from a sentence

from emotfidf import EmoTFIDF

comment = "I had a GREAT week, thanks to YOU! I am very happy today."

emTFIDF  = EmoTFIDF()

emTFIDF.set_text(comment)
print(emTFIDF.em_frequencies)

##Get emotions factorising TFIDF, you will need to add a context

Below is an example in pandas assuming you have a list of tweets/text and you would want to get emotions

emTFIDF  = EmoTFIDF()
def getEmotionsTFIDF(s,emTFIDF):
  emTFIDF.set_text(s)
  emTFIDF.get_emotfidf()
  return emTFIDF.em_tfidf


emTFIDF.computeTFIDF(df['text'])
df['emotions'] = new_df.apply(lambda x: getEmotionsTFIDF(x['text'], emTFIDF), axis=1)#em_tfidf
df2 = df['emotions'].apply(pd.Series)
final_df = pd.concat([df,df2],axis=1)

##Update 1.0.7

Thanks to artofchores, from Reddit for his feedback.

Added a set_lexicon_path option if you would like to use your own lexicon Remember to keep the same structure as the original emotions lexicon which located here

emTFIDF.set_lexicon_path("other_lexicon.json")

##Update 1.1.1

Updated the lexical db with some help from ChatGPT