Can you please how to execute twitter sentiment analysis based on ordinal regression project...

I'm really happy that the videos could be useful 🙂

Thanks a ton! I'm so happy that you found the videos helpful :-)

Thank you very much for the nice words and the suggestion :-)

Those 'corrupter emojis' you're seeing are probably just utf8 encoded

🤦 He has tutorial on getting tweets without api

Glad you enjoyed it!

Thanks. Maybe you can try this code to get the max and its label: max_value = np.amax(scores) max_label = labels[np.argmax(scores)]

@@aispectrum Thanks for your help. Works great but if I try to add it to the dataframe (to have the label and prediction), it is the sames values for all rows. For example "Neutral" and "0,75" for the first row and same for the following ones :/ Sorry for my lack of skills

Hey I'm also trying to get every score for every tweet but I just can't seem to get it, would you mind explaining it to me how you did it? :)))

have you figured it out?

@@ethanboucher4682 not yet

@@limyong8823 Hola, lograste hacerlo?

Were you able to do this please

It is possible to do the same analysis for multiple tweets. After doing the preprocessing on the text (@username to user , etc), just pass the list of the tweets to the tokenizer (just make sure to specify the max_length, and padding=True,truncation=True) and get the encoded_tweet. After geting the output, you can get the scores by writing softmax(output[0].detach().numpy(), axis=1)

@Fixes and Updates [Muzaffar Seyed] Did you figure out?

​ @aispectrum encoded_tweet = tokenizer(tweet_proce, max_length = 100, padding = True, truncation = True, return_tensors= 'pt')

@@jesusbaug hi can u send the code of how we can give multiple tweets as input... I have written tweet = ['Great content subscribed' , 'Hiii sir' ] But when i am giving this in : For word in tweet.spli() it is throwing error, can you help please

use language translation in python, I came across a video in my language (Indonesia) that explained about it.

I believe because you have essential access, you cannot use the API v1.1 (tweepy.API). You could either request for an elevated access or try to use the API v2 instead (tweepy.Client).

Same here

If it's fine, you can try google colab. I have tried it with colab and had no problem.

@@aispectrum Your solution worked. Thank you! I know this is a very simple question, but how do I modify your code to apply to a df of tweets instead of a single tweet? Presently, I can only do it by creating new variables ('encoded_tweets'; 'scores'; etc.) as empty lists of length equal to the length of my df then iterating through those lists. In R, I would just use "mutate" and it would be incredibly simply and fast.

if anyone is interested: the above query can be achieved using following code (rest of the code stays the same) # sentiment analysis def SA(tweet_proc): encoded_tweet= tokenizer(tweet_proc,return_tensors='pt') output=model(**encoded_tweet) scores=output[0][0].detach().numpy() scores=softmax(scores) ind=np.argmax(scores,axis=0) return labels[ind] df['SA'] = df['Text'].apply(SA)

I have never worked with facebook. But I would first see if the facebook api can help in data collection, if not, you could try with web scraping.