Open AccessData Extraction and Sentimental Analysis from “Twitter” using Web Scrapping
Author(s) -
Mehul Jain,
Supriya Vaish,
Madhura Patil,
Mahadev A. Gawas
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a2226.109119
Subject(s) - lexical analysis , computer science , spell , sentiment analysis , sample (material) , natural language processing , artificial intelligence , information retrieval , world wide web , data mining , data science , chemistry , chromatography , sociology , anthropology
In this paper , we attempt to do the sentimental analysis of the 2016 US presidential elections. Sentimental analysis requires the data to be extracted from websites or sources where people present their opinions, views ,complaints about the subjects that need to analyzed .Furthermore, it is necessary to ensure that the sample size of the data is large enough to get conclusive results .It is also necessary to ensure that the data is cleaned before it is used to make predictions. Cleaning is done using common techniques like tokenization, spell check ,etc. Sentimental Analysis is one of the by-products of Natural Language Processing . This paper includes data collection as well as classification of textual data based on machine learning.