University of Oulu

Sunday Adewale OLALEYE, Oluwafemi Samson BALOGUN and Bukola SALAMI “Trend of Social Media News: A Viewpoint Of COVID-19 Tweets Using Natural Language Processing” Proceedings of the 36th International Business Information Management Association (IBIMA), ISBN: 978-0-9998551-5-7, 4-5 November 2020, Granada, Spain.

Trend of social media news : a viewpoint of COVID-19 tweets using natural language processing

Saved in:
Author: Olaleye, Sunday Adewale1; Balogun, Oluwafemi Samson2; Salami, Bukola2
Organizations: 1Department of Marketing, Management and International Business, Oulu Business School, Erkki Koiso-Kanttilan Katu, Oulu 90570, Finland
2School of Computing, University of Eastern Finland, FI-70211, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.5 MB)
Persistent link:
Language: English
Published: International business information management association, 2020
Publish Date: 2020-12-17


The meteoric rise of social media news during the ongoing COVID-19 is worthy of advanced research. Freedom of speech in many parts of the world, especially the developed countries and liberty of socialization, calls for noteworthy information sharing during the panic pandemic. However, as a communication intervention during crises in the past, social media use is remarkable; the Tweets generated via Twitter during the ongoing COVID-19 is incomparable with the former records. This study examines social media news trends and compares the Tweets on COVID-19 as a corpus from Twitter. By deploying Natural Language Processing (NLP) methods on tweets, we were able to extract and quantify the similarities between some tweets over time, which means that some people say the same thing about the pandemic while other Twitter users view it differently. The tools we used are Spacy, Networkx, WordCloud, and Re. This study contributes to the social media literature by understanding the similarity and divergence of COVID-19 tweets of the public and health agencies such as the World Health Organization (WHO). The study also sheds more light on the COVID-19 sparse and densely text network and their implications for the policymakers. The study explained the limitations and proposed future studies.

see all

ISBN: 978-0-9998551-5-7
Pages: 5957 - 5975
Host publication: Proceedings of the 36th International Business Information Management Association (IBIMA), Granada, Spain, 4-5 November, 2020
Conference: IBIMA Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
518 Media and communications
Copyright information: © 2020 The Autrhos. Published by International business information management association. Creative Commons Attribution License 4.0 Unported.