Evidence map›Paper›PMID 35602240›Full record

ArticleThe Annals of regional science2022

Online citizen petitions related to COVID-19 in South Korean cities: a big data analysis.

Taedong Lee, Wooyeal Paik, Sangyoung Lim, Sang Yup Lee

Abstract read
In one paragraph

Article in The Annals of regional science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Taedong LeeDepartment of Political Science, Yonsei University, 105 Yonhee Hall, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722 South Korea.
Wooyeal PaikDepartment of Political Science and Diplomacy, Yonsei University, 307-2 Yonhee Hall, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722 South Korea.
Sangyoung LimGraduate School of Digital Analytics, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722 South Korea.
Sang Yup LeeDepartment of Communication, Yonsei University, 109 Billingsley Hall, 50 Yonsei-ro, Seodaemun-gu, Seoul, South Korea 03722.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

What do citizens demand of their governing bodies to cope with the spread of emerging infectious diseases after recognizing the growing danger? What are the similarities and differences in political participation via online citizen petitions regarding COVID-19 across cities with different degrees of pandemic experience? This study aims to answer these questions by examining citizen petitions regarding the COVID-19 pandemic in urban areas of South Korea. The pattern of citizens' requests is a part of integrative socio-ecological and political systems with spatial and temporal dimensions. We compare the pattern of online citizen petitions in four Korean cities, namely Seoul, Busan, Daegu, and Incheon, some of which were epicenters of the COVID-19 outbreak. By applying relevant big data analysis techniques such as text mining, topic modeling, and network analysis, we compare the characteristics of citizen petitions on COVID-19 in the four cities, particularly whether (and how) they want financial or welfare support or COVID-19 prevention. We find that cities that experience a rapid spread are likely to have more petitions for prevention than for support. By comparison, cities without such experience are likely to have more petitions for support. This study contributes by tracing citizen and local government interactions in response to emerging infectious diseases by empirically analyzing the related big data on petitions. Policy implications suggest that urban authorities should listen to analyze and respond to the urgent needs of citizens.

Identifiers

PMID35602240
PMCPMC9110940

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.