
Sentiment Analysis - An Assessment of Online Public Opinion: A Conceptual Review
Author(s) -
Garima Sainger
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i5.2266
Subject(s) - generalizability theory , computer science , sentiment analysis , data collection , reliability (semiconductor) , domain (mathematical analysis) , data science , the internet , artificial intelligence , data mining , information retrieval , world wide web , psychology , mathematical analysis , developmental psychology , power (physics) , statistics , physics , mathematics , quantum mechanics
This conceptual paper discusses sentiment analysis as a technique of research. It is a tool support decision for textual data collection and analysis available on the internet. It is also considered as a technique of data mining. It uses machine learning language to evaluate textual content. As a method of research, it is computational by nature and identify and categories opinions in the form of text. It targets a large data without any delay and hurdle and also facilitates the collection of data and its analysis. It helps domain leaders to collect real time data about emotions, opinion and attitude, without compromising, validity, reliability and generalizability. The paper also presents this as a way to divide quantitative and qualitative data through real time innovative ways of collection and analysis of data. The paper also discusses limitations one experience when applying this in their domain of research.