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How Positive was Your Year with TensorFlow.js and Twilio

Blog post from Twilio

Post Details
Company
Date Published
Author
Lizzie Siegle
Word Count
1,514
Company Posts That Month
40
Language
English
Hacker News Points
1
Post removed?
No
Summary

This post uses TensorFlow.js to analyze the sentiment of Twilio text messages for the year 2019, providing an objective measure of whether the user's time was positive or negative. The model uses a pre-trained Convolutional Neural Network (CNN) trained on a set of 25,000 movie reviews from IMDB. The code retrieves old text messages from the Twilio API, cleans input with regular expressions, and performs sentiment analysis on texts using TensorFlow.js in JavaScript. The output provides a decimal score showing how positive or negative the model thinks the text is, along with a classification as positive, neutral, or negative based on the score. The author invites readers to explore other applications of sentiment analysis with this technique.

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