Twitter Sentiment analyzer

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.

Why a Custom model 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.

Install

!pip install twittersentiment

Examples

• Using pretrained model

• You can also train your own mode with custom dataset and your choice of word embedding, see examples