How negative was my Twitter feed in the last few hours? In the replies are a few models that analyze the sentiment of my home timeline feed on Twitter for the last 24 hours using the Twitter API.
GitHub: github.com/ghadlich/Daily…
#NLP #Python
I analyzed the sentiment on the last 378 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (68.0%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot
I analyzed the sentiment on the last 378 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (60.3%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot
I analyzed the sentiment on the last 378 tweets from my home feed using a #NaiveBayes model from #NLTK. A majority (61.4%) were classified as positive.
#Python #NLP #Classification #Sentiment #GrantBot
I analyzed the sentiment on the last 378 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (50.8%) were classified as negative.
#Python #NLP #PyTorch #Sentiment #GrantBot
I analyzed the sentiment on the last 377 tweets from my home feed using a trained #DistilBert model from #huggingface. A majority (51.7%) were classified as positive.
#Python #NLP #PyTorch #Sentiment #GrantBot
I analyzed the sentiment on the last 377 tweets from my home feed using a pretrained #TextBlob model. A majority (52.8%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot

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More from @GrantHadlich

8 Aug
Each week I pull ~51000 tweets on US State mentions. Here's a collection of word clouds from tweets pulled on 2021-08-07. Each state + DC can be found in the replies!
#Python #USA #WordCloud #TwitterData Image
Each week I pull ~51000 tweets on US State mentions. Here's the word cloud for #Alabama from tweets pulled on 2021-08-07!
#Python #WordCloud #TwitterData Image
Each week I pull ~51000 tweets on US State mentions. Here's the word cloud for #Alaska from tweets pulled on 2021-08-07!
#Python #WordCloud #TwitterData Image
Read 52 tweets
8 Aug
How negative was my Twitter feed in the last few hours? In the replies are a few models that analyze the sentiment of my home timeline feed on Twitter for the last 24 hours using the Twitter API.
GitHub: github.com/ghadlich/Daily…
#NLP #Python Image
I analyzed the sentiment on the last 253 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (70.0%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot Image
I analyzed the sentiment on the last 253 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (56.1%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot Image
Read 7 tweets
8 Aug
How negative was my Twitter feed in the last few hours? In the replies are a few models that analyze the sentiment of my home timeline feed on Twitter for the last 24 hours using the Twitter API.
GitHub: github.com/ghadlich/Daily…
#NLP #Python
I analyzed the sentiment on the last 272 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (69.9%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot
I analyzed the sentiment on the last 272 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (57.0%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot
Read 7 tweets
7 Aug
Each week I pull ~51000 tweets on US State mentions and do sentiment analysis. Most positive state was #Maine according to an ensemble model! In the replies are the individual models.
GitHub: github.com/ghadlich/State…
#NLP #Python #ML
I analyzed the sentiment on Twitter for each state + DC from the last week using a pretrained #BERT model from #huggingface.
Which state had the most positive mentions this week? It was #Maine!
#NLP #Python #ML
I analyzed the sentiment on Twitter for each state + DC from the last week using a pretrained #VADER model from #NLTK.
Which state had the most positive mentions this week? It was #DistrictofColumbia!
#NLP #Python #ML
Read 7 tweets
7 Aug
How negative was my Twitter feed in the last few hours? In the replies are a few models that analyze the sentiment of my home timeline feed on Twitter for the last 24 hours using the Twitter API.
GitHub: github.com/ghadlich/Daily…
#NLP #Python
I analyzed the sentiment on the last 476 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (70.0%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot
I analyzed the sentiment on the last 476 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (60.5%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot
Read 7 tweets
6 Aug
How negative was my Twitter feed in the last few hours? In the replies are a few models that analyze the sentiment of my home timeline feed on Twitter for the last 24 hours using the Twitter API.
GitHub: github.com/ghadlich/Daily…
#NLP #Python Image
I analyzed the sentiment on the last 528 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (68.0%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot Image
I analyzed the sentiment on the last 528 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (58.9%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot Image
Read 7 tweets

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