Python – Sentiment Analysis using Affin
Last Updated :
17 Feb, 2023
Afinn is the simplest yet popular lexicons used for sentiment analysis developed by Finn Ã…rup Nielsen. It contains 3300+ words with a polarity score associated with each word. In python, there is an in-built function for this lexicon.
Let’s see its syntax-
Installing the library:
python3
print ("GFG")
pip install afinn /
pip3 install afinn /
!pip install afinn
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Code: Python code for sentiment analysis using Affin
python3
from afinn import Afinn
import pandas as pd
afn = Afinn()
news_df = [ 'les gens pensent aux chiens' , 'i hate flowers' ,
'he is kind and smart' , 'we are kind to good people' ]
scores = [afn.score(article) for article in news_df]
sentiment = [ 'positive' if score > 0
else 'negative' if score < 0
else 'neutral'
for score in scores]
df = pd.DataFrame()
df[ 'topic' ] = news_df
df[ 'scores' ] = scores
df[ 'sentiments' ] = sentiment
print (df)
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Output:
topic scores sentiments
0 les gens pensent aux chiens 0.0 neutral
1 i hate flowers -3.0 negative
2 he is kind and smart 3.0 positive
3 we are kind to good people 5.0 positive
The best part of this library package is that one can find score sentiment of different languages as well.
python3
afn = Afinn(language = 'da' )
afn.score( 'du er den mest modbydelige tæve' )
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Output:
-5.0
Thus, Afinn can we used easily to get scores immediately.
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