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Is your proposal related to a problem? Please describe.
Currently, the sentiment analysis module in our project analyzes news headlines using basic polarity and subjectivity metrics. To enhance the accuracy and effectiveness of sentiment analysis, especially for predicting stock market trends based on news sentiment, we propose implementing advanced techniques and models.
Add any other context or screenshots about the proposal request here.
Textual Analysis
#Functions to get the subjectivity and polarity
def getSubjectivity(text):
return TextBlob(text).sentiment.subjectivity
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Is your proposal related to a problem? Please describe.
Currently, the sentiment analysis module in our project analyzes news headlines using basic polarity and subjectivity metrics. To enhance the accuracy and effectiveness of sentiment analysis, especially for predicting stock market trends based on news sentiment, we propose implementing advanced techniques and models.
Add any other context or screenshots about the proposal request here.
Textual Analysis
#Functions to get the subjectivity and polarity
def getSubjectivity(text):
return TextBlob(text).sentiment.subjectivity
def getPolarity(text):
return TextBlob(text).sentiment.polarity
#Adding subjectivity and polarity columns
ndf['Subjectivity'] = ndf['News'].apply(getSubjectivity)
ndf['Polarity'] = ndf['News'].apply(getPolarity)
ndf
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