Identifying Early Opinion Leaders on COVID-19 on Twitter

Zahra Hatami, Margeret Hall, Neal Thorne

Publication: Chapter in book/Conference proceedingContribution to conference proceedings

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
Title of host publicationHCI International 2021 - Late Breaking Papers
Subtitle of host publicationDesign and User Experience ; 23rd HCI International Conference, HCII 2021 Virtual Event, July 24–29, 2021 Proceedings
Editors Constantine Stephanidis et al.
Place of PublicationCham
PublisherSpringer
Pages280 - 297
ISBN (Electronic)978-3-030-90238-4
ISBN (Print)978-3-030-90237-7
DOIs
Publication statusPublished - 2021

Publication series

SeriesLecture Notes in Computer Science
Number13094

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102

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