#Textblob - Twitter Hashtag

6 months ago

TextBlob NaiveBayesAnalyzer giving unexpected results: "I hate this" → positive "I love this product" → negative Model limitation or dataset bias? #Python #NLTK #TextBlob @ThePSF

AnuragBhad63967's tweet photo. TextBlob NaiveBayesAnalyzer giving unexpected results:

"I hate this" → positive
"I love this product" → negative

Model limitation or dataset bias?

#Python #NLTK #TextBlob
@ThePSF https://t.co/ErTTHAmtZG

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Wikipedia Quality @WikiQuality

over 1 year ago

#Sentiment Analysis of #Wikipedia Articles About Companies: A Comparison of Different Models. Comparative study of several #sentiment-analysis methods: #TextBlob, #VADER, #RoBERTa, #DistilBERT, #PySentimiento. https://t.co/KmAAMWLdV6

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Milvus

@milvusio

about 2 years ago

8/ #TextBlob A simple library for processing textual data, designed to provide an easy-to-use API for common #NLP tasks 👥Suitable for beginners and for quickly prototyping NLP applications.

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Ayush Barnwal | Building

@Col_ASY

almost 3 years ago

#Day15 & #Day16 of #100DaysOfCode: Worked with #Python3 to develop a translator, using #googletrans & #textblob modules Although the code to develop the basic model was easy, but it made a thing pretty clear to me that I need to work more upon my UI/UX skills😅 #translator1_0

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Ayesha Irshad @Ayeshairshad124

about 3 years ago

Day 8 of #100DaysOfCode 🌟: Exploring the power of n-grams with #TextBlob for enhanced language analysis! 📊🔍 Uncovering patterns in language using n-grams for more in-depth insights! 📚🔠 #NLP #DataAnalysis #Python #CodeNewbie #LearningInProgress #Day8

Ayeshairshad124's tweet photo. Day 8 of #100DaysOfCode 🌟:
Exploring the power of n-grams with #TextBlob for enhanced language analysis! 📊🔍
Uncovering patterns in language using n-grams for more in-depth insights! 📚🔠 #NLP #DataAnalysis #Python #CodeNewbie #LearningInProgress #Day8 https://t.co/TFlBuRY9uf

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Ayesha Irshad @Ayeshairshad124

about 3 years ago

Day 6 of #100DaysOfCode in NLP: Delving into tokenization! 📝🔠 Unlocking the power of tokenization across different libraries! 🗝️📊 #NLP #Tokenization #Python #CodeNewbie #LearningInProgress #Day6 #Spacy #textblob

Ayeshairshad124's tweet photo. Day 6 of #100DaysOfCode in NLP: Delving into tokenization! 📝🔠
Unlocking the power of tokenization across different libraries! 🗝️📊 #NLP #Tokenization #Python #CodeNewbie #LearningInProgress #Day6 #Spacy #textblob https://t.co/yXaA3YRjoC

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H2ES INSTITUTE @h2es_institute

over 3 years ago

Découvrez la puissance de #textblob !!! Dans cette vidéo, nous allons vous guider dans l'exploration des fonctionnalités de #textblob à travers des exemples pratiques. #h2esInstittute #datascience #nlp https://t.co/jUzFxDtl0k

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Grant Hadlich

@GrantHadlich

almost 4 years ago

I analyzed the sentiment on Twitter for each state + DC from the last week using a pretrained #TextBlob model. Which state had the most positive mentions this week? It was #Colorado! #NLP #Python #ML

GrantHadlich's tweet photo. I analyzed the sentiment on Twitter for each state + DC from the last week using a pretrained #TextBlob model.
Which state had the most positive mentions this week? It was #Colorado!
#NLP #Python #ML https://t.co/CYhs0W6AxJ

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Fabian Williams 👨🏾‍💻

@fabianwilliams

almost 4 years ago · Copenhagen

👋🏽u attending my #ESPC22 #Microsoft365 #Python session tomorrow? We’ve a game for u… we’ll use #Pandas & #Matplotlib & #Textblob to do reasoning over the co-presenter email text body & whether emails are read or unread…at session start u will send a bunch of kind/angry emails

fabianwilliams's tweet photo. 👋🏽u attending my #ESPC22 #Microsoft365 #Python session tomorrow? We’ve a game for u… we’ll use #Pandas & #Matplotlib & #Textblob to do reasoning over the co-presenter email text body & whether emails are read or unread…at session start u will send a bunch of kind/angry emails https://t.co/R3ux4i0BjX

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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 #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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Vibhor Gupta @vibhor_gupta_

almost 4 years ago

Today's learning: TextBlob A python library to make Natural Language Processing ( NLP ) tasks simple and easy. Kudos to the developers and the propagators of the library. #Python #DataScience #NLP #BeginningNLP #TextBlob #python3

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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 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

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 303 tweets from my home feed using a pretrained #TextBlob model. A majority (58.1%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 303 tweets from my home feed using a pretrained #TextBlob model. A majority (58.1%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/wyK9K1uPcV

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 308 tweets from my home feed using a pretrained #TextBlob model. A majority (53.2%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 308 tweets from my home feed using a pretrained #TextBlob model. A majority (53.2%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/WNJ02h4DVt

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on Twitter for each state + DC from the last week using a pretrained #TextBlob model. Which state had the most positive mentions this week? It was #Maine! #NLP #Python #ML

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 276 tweets from my home feed using a pretrained #TextBlob model. A majority (50.4%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 276 tweets from my home feed using a pretrained #TextBlob model. A majority (50.4%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/9gG9akRnFh

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 338 tweets from my home feed using a pretrained #TextBlob model. A majority (53.0%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 338 tweets from my home feed using a pretrained #TextBlob model. A majority (53.0%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/ZoZ10bYZhv

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Grant Hadlich

@GrantHadlich

about 4 years ago

I analyzed the sentiment on the last 302 tweets from my home feed using a pretrained #TextBlob model. A majority (51.3%) were classified as negative. #Python #NLP #Classification #Sentiment #GrantBot

GrantHadlich's tweet photo. I analyzed the sentiment on the last 302 tweets from my home feed using a pretrained #TextBlob model. A majority (51.3%) were classified as negative.
#Python #NLP #Classification #Sentiment #GrantBot https://t.co/06lyMOtfLs

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