Sentiment analysis is the task of determining the sentiment of a given expression in natural language, It is essentially a multiclass text classification text where the given input text is classified into positive, neutral, or negative sentiment. But the number of classes can vary according to the nature of the training dataset. This project aims to build a sentiment analyzer specifically for twitter domain.
Simply put, a Tweet is a message sent on Twitter. Most of the tweets do not follow normal English grammar and vocabulary mainly due to the limitation of the number of characters allowed in a tweet. This requires special care to yield better performance, hence this project.
!pip install twittersentiment
FAQs
A python package for sentiment analysis written using pytorch framework
We found that twittersentiment demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
In this segment of the Risky Business podcast, Feross Aboukhadijeh and Patrick Gray discuss the challenges of tracking malware discovered in open source softare.
Research
Security News
A threat actor's playbook for exploiting the npm ecosystem was exposed on the dark web, detailing how to build a blockchain-powered botnet.
Security News
NVD’s backlog surpasses 20,000 CVEs as analysis slows and NIST announces new system updates to address ongoing delays.
