Data Science Lab: process and methods - Politecnico di Torino
Sentiment analysis is the process of classifying whether a block of text is positive, negative, or, neutral. Sentiment analysis is contextual mining of words which indicates the social sentiment of a brand and also helps the business to determine whether the product which they are manufacturing is going to make a demand in the market or not. The goal which Sentiment analysis tries to gain is to analyze people’s opinion in a way that it can help the businesses expand. It focuses not only on polarity (positive, negative & neutral) but also on emotions (happy, sad, angry, etc.). It uses various Natural Language Processing algorithms such as Rule-based, Automatic, and Hybrid.
In this project we introduce a possible approach to the Tweets Sentiment Classification problem. The proposed approach consists of choosing the most influntial features of the dataset and build a classification pipelone.
Please, refere to the related paper for further information.
Contributors to this project are: Frigiola Arcangelo, and La Malfa Gianluca.
A.Y. 2021/22