Cognitive networks identify the content of English and Italian popular
posts about COVID-19 vaccines: Anticipation, logistics, conspiracy and loss
of trust
- URL: http://arxiv.org/abs/2103.15909v1
- Date: Mon, 29 Mar 2021 19:38:13 GMT
- Title: Cognitive networks identify the content of English and Italian popular
posts about COVID-19 vaccines: Anticipation, logistics, conspiracy and loss
of trust
- Authors: Massimo Stella, Michael S. Vitevitch and Federico Botta
- Abstract summary: We focus on 4765 unique popular tweets in English or Italian about COVID-19 vaccines.
One popular English tweet was liked up to 495,000 times.
English semantic frame of "vaccine" was highly polarised between trust/anticipation and anger/sadness.
Italian tweets framed "vaccine" by crucially replacing earlier levels of trust with deep sadness.
- Score: 0.5801044612920815
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Monitoring social discourse about COVID-19 vaccines is key to understanding
how large populations perceive vaccination campaigns. We focus on 4765 unique
popular tweets in English or Italian about COVID-19 vaccines between 12/2020
and 03/2021. One popular English tweet was liked up to 495,000 times, stressing
how popular tweets affected cognitively massive populations. We investigate
both text and multimedia in tweets, building a knowledge graph of
syntactic/semantic associations in messages including visual features and
indicating how online users framed social discourse mostly around the logistics
of vaccine distribution. The English semantic frame of "vaccine" was highly
polarised between trust/anticipation (towards the vaccine as a scientific asset
saving lives) and anger/sadness (mentioning critical issues with dose
administering). Semantic associations with "vaccine," "hoax" and conspiratorial
jargon indicated the persistence of conspiracy theories and vaccines in
massively read English posts (absent in Italian messages). The image analysis
found that popular tweets with images of people wearing face masks used
language lacking the trust and joy found in tweets showing people with no
masks, indicating a negative affect attributed to face covering in social
discourse. A behavioural analysis revealed a tendency for users to share
content eliciting joy, sadness and disgust and to like less sad messages,
highlighting an interplay between emotions and content diffusion beyond
sentiment. With the AstraZeneca vaccine being suspended in mid March 2021,
"Astrazeneca" was associated with trustful language driven by experts, but
popular Italian tweets framed "vaccine" by crucially replacing earlier levels
of trust with deep sadness. Our results stress how cognitive networks and
innovative multimedia processing open new ways for reconstructing online
perceptions about vaccines and trust.
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