Twitter Sentimental Analysis based on Ordinal Regression

Autor:	M. Geetha Yadav, Rajashekar Nennuri, Goda Sairam Prabhas, V Rajashree, Y Sai Vahini
Rok vydání:	2021
Předmět:	History Computer science Statistics Sentiment analysis Ordinal regression Computer Science Applications Education
Zdroj:	Journal of Physics: Conference Series. 1979:012069
ISSN:	1742-6596 1742-6588
Popis:	For associations and people with a profound social, political, or monetary Sinterest in keeping up and fortifying their clout and notoriety, Twitter has become a goldmine. Sentiment analysis is the way toward characterizing and classifying the considerations and sentiments communicated in a source record. By performing this assessment investigation in a meticulous space, it is feasible to decide the force of area data on notion order. For feeling examination order, the proposed system utilizes the calculations Support Vector Regression (SVR), Decision Trees (DTs), and Random Forest (RF). The real execution of this structure depends on a twitter dataset unveiled by the NLTK corpora devices. The proposed approach will precisely identify ordinal relapse utilizing AI procedures.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8633b57cef3c3226451684537557ab78 https://doi.org/10.1088/1742-6596/1979/1/012069 Zobrazit plný text záznamu