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Making sense of COVID-19 over time in New Zealand: Assessing the public conversation using Twitter.

ABSTRACT: COVID-19 has ruptured routines and caused breakdowns in what had been conventional practice and custom: everything from going to work and school and shopping in the supermarket to socializing with friends and taking holidays. Nonetheless, COVID-19 does provide an opportunity to study how people make sense of radically changing circumstances over time. In this paper we demonstrate how Twitter affords this opportunity by providing data in real time, and over time. In the present research, we collect a large pool of COVID-19 related tweets posted by New Zealanders-citizens of a country successful in containing the coronavirus-from the moment COVID-19 became evident to the world in the last days of 2019 until 19 August 2020. We undertake topic modeling on the tweets to foster understanding and sensemaking of the COVID-19 tweet landscape in New Zealand and its temporal development and evolution over time. This information can be valuable for those interested in how people react to emergent events, including researchers, governments, and policy makers.

SUBMITTER: Jafarzadeh H

PROVIDER: S-EPMC8673617 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Making sense of COVID-19 over time in New Zealand: Assessing the public conversation using Twitter.

Jafarzadeh Hamed H Pauleen David J DJ Abedin Ehsan E Weerasinghe Kasuni K Taskin Nazim N Coskun Mustafa M

PloS one 20211215 12

COVID-19 has ruptured routines and caused breakdowns in what had been conventional practice and custom: everything from going to work and school and shopping in the supermarket to socializing with friends and taking holidays. Nonetheless, COVID-19 does provide an opportunity to study how people make sense of radically changing circumstances over time. In this paper we demonstrate how Twitter affords this opportunity by providing data in real time, and over time. In the present research, we colle ...[more]

PMID: 34910732

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Project description:BackgroundVaccine hesitancy is a significant threat to global health. A key part of addressing hesitancy is to ensure that public health messaging prioritises information that is considered important to the public. This study aimed to examine how different vaccine characteristics affect public preferences for vaccines in New Zealand, what trade-offs they are willing to make between different vaccine characteristics, and how their preferences are affected by their vaccine-related conspiracy beliefs and COVID-19 vaccination status.MethodsAn online discrete choice experiment (DCE) was designed to elicit individual preferences about vaccines using the 1000minds platform. Members of the general population of New Zealand aged ≥ 18 years were invited to complete the DCE. Participants were asked to indicate their preference between two options showing different combinations of vaccine characteristics. Data on sociodemographic characteristics were collected. Beliefs were measured using the vaccine conspiracy beliefs scale (VCBS) with scores ≥ 19 indicating strong vaccine-related conspiracy beliefs. The DCE was analysed using the PAPRIKA method (Potentially All Pairwise RanKings of all possible Alternatives) and preferences compared between respondents with high versus low VCBS scores and vaccinated versus unvaccinated respondents for COVID-19.ResultsA total of 611 respondents from 15 regions completed the DCE. Mean (SD) age was 45.9 (14.7) years with most having had 2 or more doses of the coronavirus vaccine (86%). Mean (SD) VCBS score was 18.5 (12.4) indicating moderate vaccine-related conspiracy beliefs. Risk of severe adverse effects was the most highly valued vaccine characteristic, followed by vaccine effectiveness and duration of protection. Vaccine origin and route of administration were ranked least important. Respondents scoring high on the VCBS placed less value on the effectiveness of vaccines but greater value on development time and total number of doses (p < 0.001). COVID-19 unvaccinated respondents ranked development time and total number of doses more highly than those vaccinated respondents (p < 0.001).ConclusionsRisk of severe adverse effects, vaccine effectiveness and duration of protection were rated by the New Zealand public as the top three most important vaccine characteristics. This information is important for informing public health messaging to promote vaccine uptake and inform vaccine decision-making.

Project description:In recent years, the research and development of genome editing technology have been progressing rapidly, and the commercial use of genome-edited soybean started in the United States in 2019. A preceding study's results found that there is public concern with regard to the safety of high-tech foods, such as genetically modified foods and genome-edited foods. Twitter, one of the most popular social networks, allows users to post their opinions instantaneously, making it an extremely useful tool to collect what people are actually saying online in a timely manner. Therefore, it was used for collecting data on the users' concerns with and expectations of high-tech foods. This study collected and analyzed Twitter data on genome-edited foods and their labeling from May 25 to October 15 in 2019. Of 14,066 unique user IDs, 94.9% posted 5 or less tweets, whereas 64.8% tweeted only once, indicating that the majority of users who tweeted on this issue are not as intense, as they posted tweets consistently. After a process of refining, there were 28,722 tweets, of which 2,536 tweets (8.8%) were original, 326 (1.1%) were replies, and 25,860 (90%) were retweets. The numbers of tweets increased in response to government announcements and news content in the media. A total of six prominent peaks were detected during the investigation period, proving that Twitter could serve as a tool for monitoring degree of users' interests in real time. The co-occurrence network of original and reply tweets provided different words from various tweets that appeared with a certain frequency. However, the network derived from all tweets seemed to concentrate on words from specific tweets with negative overtones. As a result of sentiment analysis, 54.5% to 62.8% tweets were negative about genome-edited food and the labeling policy of the Consumer Affairs Agency, respectively, indicating a strong demand for mandatory labeling. These findings are expected to contribute to the communication strategy of genome-edited foods toward social implementation by government officers and science communicators.

Dataset Information

Making sense of COVID-19 over time in New Zealand: Assessing the public conversation using Twitter.

Publications

Making sense of COVID-19 over time in New Zealand: Assessing the public conversation using Twitter.

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