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.
Project description
About 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! If you need anything, please reach out."
emTFIDF = EmoTFIDF()
emTFIDF.set_text(comment) emTFIDF.get_emotions()
returns lists of emotions
#Return words list.
emTFIDF.words
##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_frequencies
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)
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