#GrantBot - Twitter Hashtag

almost 4 years ago

I analyzed the sentiment on the last 373 tweets from my home feed using a pretrained #TextBlob model. A majority (53.9%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 373 tweets from my home feed using a pretrained #TextBlob model. A majority (53.9%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/E2Up9zXBt8

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 373 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (61.9%) were classified as positive. #Python #NLP #PyTorch #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 373 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (61.9%) were classified as positive.
#Python #NLP #PyTorch #Sentiment #GrantBot https://t.co/msqYqBGBzP

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 373 tweets from my home feed using a #NaiveBayes model from #NLTK. A majority (58.4%) were classified as positive. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 373 tweets from my home feed using a #NaiveBayes model from #NLTK. A majority (58.4%) were classified as positive.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/wLeYw3MlrV

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 373 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (68.6%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 373 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (68.6%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/rMg1zWbKJa

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 299 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (58.5%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 299 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (58.5%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/4nIOOscBJO

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 196 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (54.1%) were classified as positive. #Python #NLP #PyTorch #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 196 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (54.1%) were classified as positive.
#Python #NLP #PyTorch #Sentiment #GrantBot https://t.co/gvILjdWvqw

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 196 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (57.1%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 196 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (57.1%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/IGQ0x5anDZ

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 396 tweets from my home feed using a trained #DistilBert model from #huggingface. A majority (68.7%) were classified as positive. #Python #NLP #PyTorch #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 396 tweets from my home feed using a trained #DistilBert model from #huggingface. A majority (68.7%) were classified as positive.
#Python #NLP #PyTorch #Sentiment #GrantBot https://t.co/HOMyFYYIh7

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 274 tweets from my home feed using a pretrained #TextBlob model. A majority (57.7%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 274 tweets from my home feed using a pretrained #TextBlob model. A majority (57.7%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/mH4ZtbOXBA

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 444 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (62.4%) were classified as positive. #Python #NLP #PyTorch #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 444 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (62.4%) were classified as positive.
#Python #NLP #PyTorch #Sentiment #GrantBot https://t.co/rkRKCQbtA3

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 205 tweets from my home feed using a pretrained #TextBlob model. A majority (54.6%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 205 tweets from my home feed using a pretrained #TextBlob model. A majority (54.6%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/kT11F24XIp

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 205 tweets from my home feed using a trained #DistilBert model from #huggingface. A majority (63.9%) were classified as positive. #Python #NLP #PyTorch #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 205 tweets from my home feed using a trained #DistilBert model from #huggingface. A majority (63.9%) were classified as positive.
#Python #NLP #PyTorch #Sentiment #GrantBot https://t.co/v2Wvn8AUOF

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 205 tweets from my home feed using a #NaiveBayes model from #NLTK. A majority (62.0%) were classified as positive. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 205 tweets from my home feed using a #NaiveBayes model from #NLTK. A majority (62.0%) were classified as positive.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/EGTleeHyyM

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on the last 205 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (65.9%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 205 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (65.9%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/zQ6f9u5pBl

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 428 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (68.5%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 428 tweets from my home feed using a pretrained #BERT model from #huggingface. A majority (68.5%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/OC6PTwYX25

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 177 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (64.4%) were classified as positive. #Python #NLP #PyTorch #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 177 tweets from my home feed using a pretrained #Flair model from #ZalandoSE. A majority (64.4%) were classified as positive.
#Python #NLP #PyTorch #Sentiment #GrantBot https://t.co/CnDiYQpMUq

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 203 tweets from my home feed using a pretrained #TextBlob model. A majority (60.6%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 203 tweets from my home feed using a pretrained #TextBlob model. A majority (60.6%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/BymPVq1Up2

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 203 tweets from my home feed using a trained #DistilBert model from #huggingface. A majority (72.4%) were classified as positive. #Python #NLP #PyTorch #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 203 tweets from my home feed using a trained #DistilBert model from #huggingface. A majority (72.4%) were classified as positive.
#Python #NLP #PyTorch #Sentiment #GrantBot https://t.co/z3x9s6ut0R

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 203 tweets from my home feed using a #NaiveBayes model from #NLTK. A majority (61.1%) were classified as positive. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 203 tweets from my home feed using a #NaiveBayes model from #NLTK. A majority (61.1%) were classified as positive.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/XjqDlknJhO

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 203 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (58.6%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 203 tweets from my home feed using a pretrained #VADER model from #NLTK. A majority (58.6%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/WAJ5NytDXk

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