Becca Beets

671 citations
13 papers · 378 · 1 hit paper · h-index 6

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Public Relations and Crisis Communication
    • Social Media and Politics

Papers in

Becca Beets

10 papers receiving 357 citations

Becca Beets's Hit Papers

Fact-checking as risk communication: the multi-layered risk of misinformation in times of COVID-19 2020 · 252 citations
2520+2+4Years since publication50100150200250

Peers

Becca Beets
Comparison fields: 5 of 81
  • Health Informatics 41
  • Communication 99
  • Health 58
  • Sociology and Political Science 253
  • Modeling and Simulation 25
Replace Stephen Neely with:
Stephen Neely United States
Kaisheng Lai China
Niels G. Mede Switzerland
Wenjing Pian China
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Gabriel Lima South Korea
Wenxue Zou United States
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Becca Beets relative to Stephen Neely United States Stephen Neely's profile →
Citations per field
00.5×1.6×
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Citations per year

Countries citing papers authored by Becca Beets

Since Specialization
Citations

This map shows the geographic impact of Becca Beets's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Becca Beets with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Becca Beets more than expected).

Fields of papers citing papers by Becca Beets

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Becca Beets. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Becca Beets. The network helps show where Becca Beets may publish in the future.

Co-authors

The 24 scholars most cited alongside Becca Beets, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Becca Beets Line = papers co-authored together Becca Beets links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1
Fact-checking as risk communication: the multi-layered risk of misinformation in times of COVID-19
Hit paper breakdown →
2020252
2 202363
3 202016
4 202215
5 20229
6 20228
7 20254
8 20234
9 20253
10 20253
11
Predicting and describing the use of generative AI in science-related information search:Insights from a multinational survey
20241
12 20250
13 20230

About Becca Beets

Becca Beets is a scholar working on Sociology and Political Science, Health Informatics, Education, Communication and Molecular Biology, having authored 13 papers that have together received 378 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (4 papers), Climate Change Communication and Perception (4 papers), Misinformation and Its Impacts (3 papers), CRISPR and Genetic Engineering (2 papers), Media Influence and Health (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Service-Learning and Community Engagement (2 papers) and Public Relations and Crisis Communication (2 papers). The work is most often cited by research in Health Informatics (41 citations), Communication (99 citations), Health (58 citations), Sociology and Political Science (253 citations) and Modeling and Simulation (25 citations). Becca Beets has collaborated with scholars based in United States, Germany and Taiwan. Frequent co-authors include Dominique Brossard, Isabelle Freiling, Nicole M. Krause, Emily L. Howell, Luye Bao, Shiyu Yang, Todd P. Newman, Dietram A. Scheufele, Jo Handelsman and Noah Weeth Feinstein. Their work appears in journals such as Public Understanding of Science, Science Communication, The CRISPR Journal, Vaccine and Journal of Risk Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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