Ashlynn R. Daughton

713 total citations
27 papers, 419 citations indexed

About

Ashlynn R. Daughton is a scholar working on Epidemiology, Sociology and Political Science and Molecular Biology. According to data from OpenAlex, Ashlynn R. Daughton has authored 27 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Epidemiology, 8 papers in Sociology and Political Science and 5 papers in Molecular Biology. Recurrent topics in Ashlynn R. Daughton's work include Data-Driven Disease Surveillance (16 papers), Misinformation and Its Impacts (8 papers) and Influenza Virus Research Studies (5 papers). Ashlynn R. Daughton is often cited by papers focused on Data-Driven Disease Surveillance (16 papers), Misinformation and Its Impacts (8 papers) and Influenza Virus Research Studies (5 papers). Ashlynn R. Daughton collaborates with scholars based in United States, United Kingdom and Singapore. Ashlynn R. Daughton's co-authors include Michael J. Paul, Reid Priedhorsky, Geoffrey Fairchild, Alina Deshpande, Nicholas Generous, Dave Osthus, Abeed Sarker, Karen O’Connor, Arjun Magge and Graciela Gonzalez‐Hernandez and has published in prestigious journals such as PLoS ONE, Scientific Reports and Nature Protocols.

In The Last Decade

Ashlynn R. Daughton

26 papers receiving 399 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ashlynn R. Daughton United States 12 129 120 117 77 69 27 419
Todd Bodnar United States 6 122 0.9× 204 1.7× 76 0.6× 14 0.2× 84 1.2× 10 435
Nicholas Generous United States 13 70 0.5× 285 2.4× 51 0.4× 58 0.8× 180 2.6× 26 536
Ai Kawazoe Japan 10 74 0.6× 206 1.7× 171 1.5× 165 2.1× 22 0.3× 18 447
Geoffrey Fairchild United States 12 125 1.0× 305 2.5× 76 0.6× 36 0.5× 189 2.7× 29 681
Julie A. Keating United States 9 193 1.5× 54 0.5× 24 0.2× 46 0.6× 45 0.7× 23 544
Natasha Markuzon United States 12 96 0.7× 77 0.6× 67 0.6× 15 0.2× 109 1.6× 21 441
Tim Nguyen Switzerland 10 199 1.5× 135 1.1× 45 0.4× 11 0.1× 48 0.7× 36 460
Shashank Khandelwal United States 4 292 2.3× 336 2.8× 132 1.1× 30 0.4× 160 2.3× 5 799
Fengchen Liu United States 12 67 0.5× 128 1.1× 27 0.2× 28 0.4× 85 1.2× 35 377
Hyekyung Woo South Korea 10 95 0.7× 137 1.1× 39 0.3× 11 0.1× 43 0.6× 39 389

Countries citing papers authored by Ashlynn R. Daughton

Since Specialization
Citations

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

Fields of papers citing papers by Ashlynn R. Daughton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashlynn R. Daughton. 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 Ashlynn R. Daughton. The network helps show where Ashlynn R. Daughton may publish in the future.

Co-authorship network of co-authors of Ashlynn R. Daughton

This figure shows the co-authorship network connecting the top 25 collaborators of Ashlynn R. Daughton. A scholar is included among the top collaborators of Ashlynn R. Daughton based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ashlynn R. Daughton. Ashlynn R. Daughton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gilbert, Michael, et al.. (2025). Social Listening for Patient Experiences With Stopping Extended-Release Buprenorphine: Content Analysis of Reddit Messages. Journal of Medical Internet Research. 27. e71245–e71245. 2 indexed citations
2.
Parikh, Nidhi, et al.. (2021). “Thought I’d Share First” and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study. JMIR Public Health and Surveillance. 7(4). e26527–e26527. 54 indexed citations
3.
Daughton, Ashlynn R., et al.. (2021). Mining and Validating Social Media Data for COVID-19–Related Human Behaviors Between January and July 2020: Infodemiology Study. Journal of Medical Internet Research. 23(5). e27059–e27059. 7 indexed citations
4.
Parikh, Nidhi, et al.. (2020). Improving Detection of Disease Re-emergence Using a Web-Based Tool (RED Alert): Design and Case Analysis Study. JMIR Public Health and Surveillance. 7(1). e24132–e24132. 3 indexed citations
5.
Parikh, Nidhi, et al.. (2020). "Thought I'd Share First": An Analysis of COVID-19 Conspiracy Theories and Misinformation Spread on Twitter. arXiv (Cornell University). 1 indexed citations
6.
Daughton, Ashlynn R., Rumi Chunara, & Michael J. Paul. (2020). Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study. JMIR Public Health and Surveillance. 6(2). e14986–e14986. 9 indexed citations
7.
Daughton, Ashlynn R., et al.. (2019). Development of a Supervised Learning Algorithm for Detection of Potential Disease Reemergence: A Proof of Concept. Health Security. 17(4). 255–267. 1 indexed citations
8.
Osthus, Dave, Ashlynn R. Daughton, & Reid Priedhorsky. (2019). Even a good influenza forecasting model can benefit from internet-based nowcasts, but those benefits are limited. PLoS Computational Biology. 15(2). e1006599–e1006599. 19 indexed citations
9.
Velappan, Nileena, Ashlynn R. Daughton, Geoffrey Fairchild, et al.. (2019). Analytics for Investigation of Disease Outbreaks: Web-Based Analytics Facilitating Situational Awareness in Unfolding Disease Outbreaks. JMIR Public Health and Surveillance. 5(1). e12032–e12032. 4 indexed citations
10.
Priedhorsky, Reid, Ashlynn R. Daughton, Martha Barnard, Fiona O’Connell, & Dave Osthus. (2019). Estimating influenza incidence using search query deceptiveness and generalized ridge regression. PLoS Computational Biology. 15(10). e1007165–e1007165. 9 indexed citations
11.
Daughton, Ashlynn R., et al.. (2019). Zika discourse in the Americas: A multilingual topic analysis of Twitter. PLoS ONE. 14(5). e0216922–e0216922. 40 indexed citations
12.
Weissenbacher, Davy, Abeed Sarker, Arjun Magge, et al.. (2019). Overview of the Fourth Social Media Mining for Health (SMM4H) Shared Tasks at ACL 2019. 21–30. 70 indexed citations
13.
Daughton, Ashlynn R. & Michael J. Paul. (2019). Identifying Protective Health Behaviors on Twitter: Observational Study of Travel Advisories and Zika Virus. Journal of Medical Internet Research. 21(5). e13090–e13090. 33 indexed citations
14.
Fairchild, Geoffrey, Nicholas Generous, Ashlynn R. Daughton, et al.. (2018). Epidemiological Data Challenges: Planning for a More Robust Future Through Data Standards. Frontiers in Public Health. 6. 336–336. 38 indexed citations
15.
Daughton, Ashlynn R., Nicholas Generous, Reid Priedhorsky, & Alina Deshpande. (2017). An approach to and web-based tool for infectious disease outbreak intervention analysis. Scientific Reports. 7(1). 46076–46076. 18 indexed citations
16.
Han, Cliff, Mélanie Martin, Armand E. K. Dichosa, et al.. (2016). Salivary microbiomes of indigenous Tsimane mothers and infants are distinct despite frequent premastication. PeerJ. 4. e2660–e2660. 13 indexed citations
17.
Deshpande, Alina, Benjamin H. McMahon, Ashlynn R. Daughton, et al.. (2016). Surveillance for Emerging Diseases with Multiplexed Point-of-Care Diagnostics. Health Security. 14(3). 111–121. 9 indexed citations
18.
Margevicius, Kristen, Nicholas Generous, Esteban Abeyta, et al.. (2016). The Biosurveillance Analytics Resource Directory (BARD): Facilitating the Use of Epidemiological Models for Infectious Disease Surveillance. PLoS ONE. 11(1). e0146600–e0146600. 11 indexed citations
19.
Daughton, Ashlynn R., Nileena Velappan, Esteban Abeyta, Reid Priedhorsky, & Alina Deshpande. (2016). Novel Use of Flu Surveillance Data: Evaluating Potential of Sentinel Populations for Early Detection of Influenza Outbreaks. PLoS ONE. 11(7). e0158330–e0158330. 1 indexed citations
20.
Close, Devin, Fortunato Ferrara, Armand E. K. Dichosa, et al.. (2013). Using phage display selected antibodies to dissect microbiomes for complete de novo genome sequencing of low abundance microbes. BMC Microbiology. 13(1). 270–270. 15 indexed citations

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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