Open AccessOpinion Mining and Trend Analysis on Twitter Data
Author(s) -
Anuj Kumar,
Hoshiyar Singh Kanyal,
Shivani Sharma,
Kaushal Singh,
Ayushi Dwivedi
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.a1547.059120
Subject(s) - popularity , social media , sentiment analysis , public opinion , the internet , world wide web , computer science , tracking (education) , entertainment , data science , politics , advertising , internet privacy , sociology , political science , business , artificial intelligence , pedagogy , law
With rise in Internet use across the global, there has been a trending increase in the online data. Every person from different profession gives their view from politics to entertainment, sports or economics. The web’s current evolution is a major pacesetter as it generates an effectual methodology to embed “smart data” into web pages and hence result in easy content implementation for authors. The web 2.0 has changed the way of communication on the web. Using Social Networks (SNs) they have become active participants by connecting, producing and sharing information, experiences and opinions with each other [1]. Public opinions extracted in the form of trends are interesting for researchers, sociologists, news reporters, marketing professionals and opinion tracking companies. The aim of this project is opinion mining and the analysis of the trends of the public statements gathered from different social media sources (specifically twitter). Here Binary sentiment analysis is performed on currently fetched data from twitter over various emotional quotients. W have also performed (i) Comparison between two users based on public reaction in the form of likes, shares and number of re-tweets; (ii) Visualization of comparison results by plotting graphs over popularity of social media (likes/re-tweets/shares).