Evidence map›Paper›PMID 35968468›Full record

ArticleFrontiers in public health2022

Spatiotemporal variations of public opinion on social distancing in the Netherlands: Comparison of Twitter and longitudinal survey data.

Chao Zhang, Shihan Wang, Erik Tjong Kim Sang, Marieke A Adriaanse, Lars Tummers, Marijn Schraagen, Ji Qi, Mehdi Dastani, Henk Aarts

Abstract read
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Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Chao ZhangDepartment of Psychology, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, Netherlands.
Shihan WangDepartment of Information and Computing Sciences, Faculty of Science, Utrecht University, Utrecht, Netherlands.
Erik Tjong Kim SangNetherlands eScience Center, Amsterdam, Netherlands.
Marieke A AdriaanseDepartment of Psychology, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, Netherlands.
Lars TummersDepartment of Public Governance and Management, Faculty of Social and Behavior Sciences, Utrecht University, Utrecht, Netherlands.
Marijn SchraagenDepartment of Information and Computing Sciences, Faculty of Science, Utrecht University, Utrecht, Netherlands.
Ji QiFaculty of Science, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands.
Mehdi DastaniDepartment of Information and Computing Sciences, Faculty of Science, Utrecht University, Utrecht, Netherlands.
Henk AartsDepartment of Psychology, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Social distancing has been implemented by many countries to curb the COVID-19 pandemic. Understanding public support for this policy calls for effective and efficient methods of monitoring public opinion on social distancing. Twitter analysis has been suggested as a cheaper and faster-responding alternative to traditional survey methods. The current empirical evidence is mixed in terms of the correspondence between the two methods. Objective: We aim to compare the two methods in the context of monitoring the Dutch public's opinion on social distancing. For this comparison, we quantified the temporal and spatial variations in public opinion and their sensitivities to critical events using data from both Dutch Twitter users and respondents from a longitudinal survey. Methods: A longitudinal survey on a representative Dutch sample ( Results: Both data sources suggested strong support for social distancing, but public opinion was much more varied among tweets than survey responses. Both data sources showed an increase in public support for social distancing over time, and a strong temporal correspondence between them was found for most of the provinces. In addition, the survey but not Twitter data revealed structured differences among the 12 provinces, while the two data sources did not correspond much spatially. Finally, stances estimated from tweets were more sensitive to critical events happened during the study period. Conclusions: Our findings indicate consistencies between Twitter data analysis and survey methods in describing the overall stance on social distancing and temporal trends. The lack of spatial correspondence may imply limitations in the data collections and calls for surveys with larger regional samples. For public health management, Twitter analysis can be used to complement survey methods, especially for capturing public's reactivities to critical events amid the current pandemic.

Indexed as

COVID-19Social MediaHumansLongitudinal StudiesNetherlandsPandemicsPhysical DistancingPublic OpinionCOVID-19longitudinal surveypublic opinionsocial distancingsocial media dataspatiotemporal analysisstance analysis

Identifiers

PMID35968468
PMCPMC9366395

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.