Priyanka! This was so clearly explained with examples. Grrrreat job! I have a question for you, is it always necessary to remove stop words for analyzing tweets with Vader? Thanks a lot.
Thanks @Ruchita Kulkarni It is not always necessary to remove stop words. I found out that often stop words like not, but are useful for better analysis of negative sentiments. It also depends upon the data set one is working with. Vader often gives a good score compared to TextBlob. For further reading and clarification you can refer to this blog: medium.com/data-science-blogs/stopwords-and-lexicon-normalization-for-sentiment-analysis-f9f10f0d4108
How to handle these types of sentences "No problems with it and does job well. Using it for Apple TV and works great. I would buy again no problem" as in vader it is consider as negative sentence
Best tutor amazing Love it
Thank you so much. 😊
Top video, you explain amazingly!
Thank you 😊 🙏
This is absolutely incredible breakdown. Thank you so much. This will help me with the second portion of my second midterm in NLP sentiment analysis.
Sure 👍
Priyanka! This was so clearly explained with examples. Grrrreat job! I have a question for you, is it always necessary to remove stop words for analyzing tweets with Vader? Thanks a lot.
Thanks @Ruchita Kulkarni
It is not always necessary to remove stop words.
I found out that often stop words like not, but are useful for better analysis of negative sentiments.
It also depends upon the data set one is working with.
Vader often gives a good score compared to TextBlob.
For further reading and clarification you can refer to this blog:
medium.com/data-science-blogs/stopwords-and-lexicon-normalization-for-sentiment-analysis-f9f10f0d4108
This is the best. If helps me a lot. Thank you so much.
Glad to hear that!
Really informative! Thanks!
Glad it was helpful! Rajat.
Is there bombing outside?
HAHA It was Diwali, Indian Festival that we celebrate.
How to aggregate this sentiment scores at product level ?
Which algorithm have you used like naive baies,svm, etc.. plz reply
I have used the VADER library for this. Worked on a pre-trained model.
for user-friendly, i want to show also neutral also based on compound value, for that what should I need to do? please reply to my message.
thank you
Thanks a lot..this was very helpful
Thank u for d video...
Welcome 😊 Ria Bari
Can i implement this in django
Yes, you would have to connect the code with the front end using HTML code and implement is using django
Mam can you please help me to implement naive Bayes classifier and Knn classifier in python using food analysis
I need this code how to get
Hi
Links are there in the description please check them.
How to handle these types of sentences "No problems with it and does job well. Using it for Apple TV and works great. I would buy again no problem" as in vader it is consider as negative sentence
Hi
one option is you can re-phrase the sentence and the use it as input.