Identifying Early Opinion Leaders on COVID-19 on Twitter

Zahra Hatami, Margeret Hall, Neil Thorne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study aims to empirically identify opinion leaders on Twitter from the lens of Innovation Diffusion theory. We analyzed pandemic-specific tweets from casual users as well as from the US President to map their conversation for the purpose of finding opinion leaders over a three month period at the onset of the pandemic. By applying network analysis following with cluster enrichment as well as sentiment analysis, we recognize potential thought leaders, but we could not find strong evidence for opinion leaders according to the Innovation Diffusion theory. We interpret that users tweet for two different purposes - tweets to elicit agreement and tweets to elicit debate.

Original languageEnglish (US)
Title of host publicationHCI International 2021 - Late Breaking Papers
Subtitle of host publicationDesign and User Experience - 23rd HCI International Conference, HCII 2021, Proceedings
EditorsConstantine Stephanidis, Marcelo M. Soares, Marcelo M. Soares, Elizabeth Rosenzweig, Aaron Marcus, Sakae Yamamoto, Hirohiko Mori, Pei-Luen Patrick Rau, Gabriele Meiselwitz, Xiaowen Fang, Abbas Moallem
PublisherSpringer Science and Business Media Deutschland GmbH
Pages280-297
Number of pages18
ISBN (Print)9783030902377
DOIs
StatePublished - 2021
Event23rd International Conference on Human-Computer Interaction , HCII 2021 - Virtual, online
Duration: Jul 24 2021Jul 29 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13094 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Human-Computer Interaction , HCII 2021
CityVirtual, online
Period7/24/217/29/21

Keywords

  • Network analysis
  • Opinion leaders
  • Sentiment analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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