Evidence map›Paper›PMID 34751239›Full record

ArticleSustainable cities and society2022

Toward human-centric urban infrastructure: Text mining for social media data to identify the public perception of COVID-19 policy in transportation hubs.

June Young Park, Evan Mistur, Donghwan Kim, Yunjeong Mo, Richard Hoefer

Open access · greenAbstract read
In one paragraph

Article in Sustainable cities and society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
16.6field-weighted citation impact, top 1% of its field
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

9 citing papers in PubMed, 83 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

5 authors at 2 institutions in 1 country.

June Young ParkDepartment of Civil Engineering, The University of Texas at Arlington, Arlington, TX, USA.
Evan MisturDepartment of Public Affairs and Planning, The University of Texas at Arlington, Arlington, TX, USA.
Donghwan KimNBBJ, Architectural Design Firm, Washington, DC, USA.
Yunjeong MoDepartment of Construction Management, University of North Florida, Jacksonville, FL, USA.
Richard HoeferSchool of Social Work, The University of Texas at Arlington, Arlington, TX, USA.
The University of Texas at Arlington · USUniversity of North Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has made transportation hubs vulnerable to public health risks. In response, policies using nonpharmaceutical interventions have been implemented, changing the way individuals interact within these facilities. However, the impact of building design and operation on policy efficacy is not fully discovered, making it critical to investigate how these policies are perceived and complied in different building spaces. Therefore, we investigate the spatial drivers of user perceptions and policy compliance in airports. Using text mining, we analyze 103,428 Google Maps reviews of 64 major hub airports in the US to identify representative topics of passenger concerns in airports (i.e., Staff, Shop, Space, and Service). Our results show that passengers express having positive experiences with Staff and Shop, but neutral or negative experiences with Service and Space, which indicates how building design has impacted policy compliance and the vulnerability of health crises. Furthermore, we discuss the actual review comments with respect to 1) spatial design and planning, 2) gate assignment and operation, 3) airport service policy, and 4) building maintenance, which will construct the foundational knowledge to improve the resilience of transportation hubs to future health crises.

Indexed as

COVID-19 policyHuman-building interationsHuman-centric urban infrastructuresPublic perceptionSocial media dataText mining

Identifiers

PMID34751239
PMCPMC8566222
OpenAlexW3209666692

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.