Molly Sauer

25 papers receiving 679 citations

Molly Sauer's Hit Papers

Building trust while influencing online COVID-19 content in the social media world 2020 · 238 citations
2380+2+4Years since publication50100150200

Peers

Molly Sauer
Comparison fields: 5 of 93
  • Health 196
  • Modeling and Simulation 63
  • Communication 77
  • Infectious Diseases 135
  • Sociology and Political Science 223
Replace Irene A. Harmsen with:
Irene A. Harmsen Netherlands
Jessica Jaiswal United States
Basmattee Boodram United States
Trenton M. White Spain
Drew A. Westmoreland United States
Maryline Vivion Canada
Ayat Al-Haidar Jordan
Philip M. Massey United States
Huda Eid Jordan
Ayodele Samuel Jegede Nigeria
Molly Sauer relative to Irene A. Harmsen Netherlands Irene A. Harmsen's profile →
Citations per field
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Irene A. Harmsen · 1×
Citations per year

Countries citing papers authored by Molly Sauer

Since Specialization
Citations

This map shows the geographic impact of Molly Sauer'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 Molly Sauer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Molly Sauer more than expected).

Fields of papers citing papers by Molly Sauer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Molly Sauer. 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 Molly Sauer. The network helps show where Molly Sauer may publish in the future.

Co-authors

The 25 scholars most cited alongside Molly Sauer, 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 Molly Sauer Line = papers co-authored together Molly Sauer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Building trust while influencing online COVID-19 content in the social media world
Hit paper breakdown →
2020238
2 202158
3 202055
4 202154
5 201839
6 201936
7 201431
8 202129
9 202028
10 202224
11 202120
12 202018
13 202214
14 202014
15 20237
16 20237
17 20227
18 20235
19 20235
20 20205

About Molly Sauer

Molly Sauer is a scholar working on Health, Infectious Diseases, Sociology and Political Science, Epidemiology and Safety Research, having authored 27 papers that have together received 706 indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (12 papers), Viral gastroenteritis research and epidemiology (4 papers), Hepatitis Viruses Studies and Epidemiology (3 papers), COVID-19 epidemiological studies (3 papers), Poverty, Education, and Child Welfare (3 papers), Misinformation and Its Impacts (3 papers), Global Health and Surgery (2 papers) and Child Nutrition and Water Access (2 papers). The work is most often cited by research in Health (196 citations), Modeling and Simulation (63 citations), Communication (77 citations), Infectious Diseases (135 citations) and Sociology and Political Science (223 citations). Molly Sauer has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include Rupali J. Limaye, Brian Wahl, Alain Labrique, Justin Bernstein, Joseph Ali, Anne Barnhill, Mathuram Santosham, Shaun Truelove, Taylor A. Holroyd and Maria Deloria Knoll. Their work appears in journals such as Vaccine, Human Vaccines & Immunotherapeutics, PLoS ONE, Global Health Research and Policy and Expert Review of Vaccines.

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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