Sentiment Analysis Text Extraction from Tweets with Spacy NER
Authors:-Pijush Pathak, Linson Thomas Verghese, Dr.G.Divya
Abstract-This project investigates sentiment analysis on Twit- ter data using spaCy, a flexible Natural Language Processing (NLP) framework. Our goal is to create algorithms that can recognize and extract text segments from Tweets that convey sentiment. This entails using tagged Twitter data to train two spaCy Named Entity Recognition (NER) models: one for positive sentiment and one for negative sentiment. Next, new Tweets are subjected to these models in order to predict user emotion and extract pertinent sentences. By identifying sentiment-infused text fragments, we are able to better comprehend the emotions around particular issues or phrases by gaining insights into the opinions and motivations of Twitter users.
