Data_Sheet_1_Spatiotemporal variations of public opinion on social distancing in the Netherlands: Comparison of Twitter and longitudinal survey data.PDF

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 quantif... Mehr ...

Verfasser: Chao Zhang
Shihan Wang
Erik Tjong Kim Sang
Marieke A. Adriaanse
Lars Tummers
Marijn Schraagen
Ji Qi
Mehdi Dastani
Henk Aarts
Dokumenttyp: Dataset
Erscheinungsdatum: 2022
Schlagwörter: Mental Health Nursing / Midwifery / Nursing not elsewhere classified / Aboriginal and Torres Strait Islander Health / Aged Health Care / Care for Disabled / Community Child Health / Environmental and Occupational Health and Safety / Epidemiology / Family Care / Health and Community Services / Health Care Administration / Health Counselling / Health Information Systems (incl. Surveillance) / Health Promotion / Preventive Medicine / Primary Health Care / Public Health and Health Services not elsewhere classified / Nanotoxicology / Health and Safety / Medicine / Nursing and Health Curriculum and Pedagogy / COVID-19 / social distancing / spatiotemporal analysis / public opinion / social media data / stance analysis / longitudinal survey
Sprache: unknown
Permalink: https://search.fid-benelux.de/Record/base-26805579
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doi.org/10.3389/fpubh.2022.856825.s001

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 (n = 1,200) was conducted between July and November 2020 to measure opinions on social distancing weekly. From the same period, near 100,000 Dutch tweets were categorized as supporting or rejecting social distancing based on a model trained with annotated data. Average stances for the 12 Dutch provinces and over the 20 weeks were computed from the two data sources and were compared through visualizations and statistical analyses. 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 ...