@inproceedings{0d2bc7cf8086408196ee6ba3e8a67efa,
title = "Identifying Early Opinion Leaders on COVID-19 on Twitter",
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.",
author = "Zahra Hatami and Margeret Hall and Neal Thorne",
year = "2021",
doi = "10.1007/978-3-030-90238-4_20",
language = "English",
isbn = "978-3-030-90237-7",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
number = "13094",
pages = "280 -- 297",
editor = "{Constantine Stephanidis et al.}",
booktitle = "HCI International 2021 - Late Breaking Papers",
address = "Germany",
}