The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Comparing the Behaviour of Two Topic-Modelling Algorithms in COVID-19 Vaccination Tweets: LDA vs. LSA
|
|
Author(s): Jordan Thomas Bignell (Coventry University, UK), Georgios Chantziplakis (Coventry University, UK)and Alireza Daneshkhah (Coventry University, UK)
Copyright: 2022
Volume: 5
Issue: 1
Pages: 20
Source title:
International Journal of Strategic Engineering (IJoSE)
Editor(s)-in-Chief: Amin Hosseinian-Far (University of Hertfordshire, UK)
DOI: 10.4018/IJoSE.292445
PurchaseView on the publisher's website for pricing and purchasing information.
|
Abstract
Coronavirus is a newly developed infectious disease that has triggered a pandemic due to its ease of transmission as of early 2020. Several groups from various countries have been working on a vaccine to prevent and avoid the spread of the virus in this outbreak. In this article, the main objective is to compare LDA against LSA to gain a better understanding of the Tweets and which Topic Modelling technique fits best for this task, additionally if the feedback of the Tweets were positive or negative sentiment. It was concluded that LDA was a better-unsupervised technique for categorizing the raw text in 12 topics.
Related Content
|
Ali Hosseinpour, Reza Montasari.
© 2022.
10 pages.
|
|
Andrew Mangle.
© 2022.
9 pages.
|
|
Jordan Thomas Bignell, Georgios Chantziplakis, Alireza Daneshkhah.
© 2022.
20 pages.
|
|
Souhail Dhouib.
© 2022.
12 pages.
|
|
Yasin Yousefi, Petra Gratton, Dilshad Sarwar.
© 2021.
18 pages.
|
|
Brian J. Galli.
© 2021.
14 pages.
|
|
Carol Matirangana Verner, Dilshad Sarwar.
© 2021.
22 pages.
|
|
|