DOI: 10.1016/j.amepre.2021.01.
008 link
PMID: 33773862
OpenAlex ID: W3131933807
Category: Biomedical
Title: Willingness to Vaccinate Against COVID-19 in the U.S.: Representative Longitudinal Evidence From April to October 2020
Authors: Michael Daly, Eric Robinson
Publishing date: 01-Jun-2021
YCR = 2021 / 149 / 13.05
Version 1.00 Year / Citations / Relative
Metric | Value | Date of Calculation |
---|---|---|
Citations count |
149 |
30-May-2024 |
Relative |
13.05 |
04-Aug-2024 |
Article Expected CPY (Citations per Year): 3.81 Expected CPY Help
Article Actual CPY: 49.67 Actual CPY Help
Article Co-Citation FCR (Field Citation Rate): 5.63 FCR Help
Article Co-Citation Network Size: 6509 Co-Citation Network Size Help
Article Topics: Factors Affecting Vaccine Hesitancy and Acceptance, The Spread of Misinformation Online, Modeling the Dynamics of COVID-19 Pandemic Topics help
Article Keywords: Vaccination Intention, Vaccine Hesitancy Keywords Help
Journal: American journal of preventive medicine
Journal IF-ycr: 5.558 Journal IF-ycr Help
Journal short code: NA
Journal ISSN: 0749-3797
Journal OA-ID: 195759676
Expected CPY Help: Predicted citations per year for this article, derived from its Field Citation Rate (FCR) using a benchmark regression of NIH-funded papers. Values above actual CPY indicate under-performance; below indicate over-performance. Used as the denominator of the Relative Citation Ratio.
Back to topActual CPY Help: Average yearly citations the article has received from publication through the current year, adjusted for partial years. Used as the numerator of the Relative Citation Ratio.
Back to topFCR Help: Mean journal citation rate for all papers in the article's co-citation network. For each network paper we substitute its journal’s impact factor (calculated from open data) as a proxy for citations per year, then average these values. This captures the citation intensity of the article's immediate research field and forms the basis for computing expected CPY.
Back to topCo-Citation Network Size Help: Number of unique papers co-cited with this article by its citing papers; larger networks yield more stable field estimates when calculating FCR and expected CPY.
Back to topTopics Help: OpenAlex assigns topics to each paper with an AI model that considers the title, abstract, journal, and citation links. Tags are chosen from about 4,500 research areas, and the highest-confidence tag becomes the paper's primary topic. Every topic sits in a hierarchy of domain, field, and subfield, so you can see exactly where the work fits in the wider map of science.
Back to topKeywords Help: Keywords are generated automatically from the paper's assigned topics. The OpenAlex system selects candidate terms, then keeps up to five that match closely with the title or abstract. These keywords highlight specific concepts or methods and give a quick complement to the broader topic tags.
Back to topJournal IF-ycr Help: Journal IF-ycr is a two-year impact factor recalculated from OpenAlex's open citation data. For a given journal and year Y, we:
- Count citations made in year Y by any paper to items that the journal published in years Y-1 and Y-2 (excluding the current year).
- Divide that citation count by the number of articles the journal published in those same two years.