Tim K. Mackey

8.3k total citations · 2 hit papers
219 papers, 4.9k citations indexed

About

Tim K. Mackey is a scholar working on Public Health, Environmental and Occupational Health, Economics and Econometrics and Sociology and Political Science. According to data from OpenAlex, Tim K. Mackey has authored 219 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Public Health, Environmental and Occupational Health, 59 papers in Economics and Econometrics and 40 papers in Sociology and Political Science. Recurrent topics in Tim K. Mackey's work include Pharmaceutical Economics and Policy (53 papers), Pharmaceutical Quality and Counterfeiting (42 papers) and Pharmaceutical industry and healthcare (32 papers). Tim K. Mackey is often cited by papers focused on Pharmaceutical Economics and Policy (53 papers), Pharmaceutical Quality and Counterfeiting (42 papers) and Pharmaceutical industry and healthcare (32 papers). Tim K. Mackey collaborates with scholars based in United States, Canada and Germany. Tim K. Mackey's co-authors include Bryan A. Liang, Raphael Cuomo, Gaurvika M. L. Nayyar, Jiawei Li, Qing Xu, Vidya Purushothaman, Neal Shah, Mingxiang Cai, Kevin A. Clauson and Takeo Katsuki and has published in prestigious journals such as Science, Cell and JAMA.

In The Last Decade

Tim K. Mackey

203 papers receiving 4.7k citations

Hit Papers

A review of existing and emerging digital technologies to... 2017 2026 2020 2023 2017 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tim K. Mackey United States 37 1.4k 1.0k 989 932 572 219 4.9k
Su Golder United Kingdom 41 891 0.6× 266 0.3× 1.4k 1.4× 1.1k 1.2× 1.2k 2.1× 152 8.1k
Eric G. Campbell United States 47 2.3k 1.6× 336 0.3× 2.0k 2.1× 613 0.7× 2.4k 4.1× 166 8.8k
Michael Parker United Kingdom 45 2.5k 1.7× 857 0.8× 552 0.6× 751 0.8× 1.3k 2.3× 239 7.7k
David Blumenthal United States 28 1.1k 0.8× 162 0.2× 1.1k 1.1× 471 0.5× 1.4k 2.5× 83 5.3k
Robert P. Dellavalle United States 41 743 0.5× 300 0.3× 210 0.2× 543 0.6× 1.0k 1.8× 298 9.3k
Kenneth D. Mandl United States 62 2.5k 1.7× 497 0.5× 905 0.9× 1.2k 1.3× 2.5k 4.4× 299 12.9k
Ahmed Al‐Jabir United Kingdom 11 535 0.4× 349 0.3× 2.2k 2.2× 1.1k 1.2× 831 1.5× 26 9.3k
Zaid Alsafi United Kingdom 12 556 0.4× 351 0.3× 2.1k 2.2× 1.1k 1.2× 810 1.4× 18 9.0k
Barbara Prainsack United Kingdom 38 1.4k 1.0× 331 0.3× 278 0.3× 831 0.9× 787 1.4× 177 4.3k
Bryan A. Liang United States 30 827 0.6× 184 0.2× 593 0.6× 346 0.4× 472 0.8× 201 3.0k

Countries citing papers authored by Tim K. Mackey

Since Specialization
Citations

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

Fields of papers citing papers by Tim K. Mackey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim K. Mackey. 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 Tim K. Mackey. The network helps show where Tim K. Mackey may publish in the future.

Co-authorship network of co-authors of Tim K. Mackey

This figure shows the co-authorship network connecting the top 25 collaborators of Tim K. Mackey. A scholar is included among the top collaborators of Tim K. Mackey 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 Tim K. Mackey. Tim K. Mackey 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.
Purnat, Tina D, et al.. (2024). Evaluating the Influence of Role-Playing Prompts on ChatGPT’s Misinformation Detection Accuracy: Quantitative Study. PubMed. 4. e60678–e60678. 5 indexed citations
3.
Liang, Bryan A., et al.. (2023). Understanding Medical Malpractice Lawsuits. Stroke. 54(3). e95–e99.
4.
Li, Jiawei, et al.. (2023). Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis. SHILAP Revista de lepidopterología. 3. e40575–e40575. 6 indexed citations
5.
Purushothaman, Vidya, et al.. (2022). Content Analysis of Nicotine Poisoning (Nic Sick) Videos on TikTok: Retrospective Observational Infodemiology Study. Journal of Medical Internet Research. 24(3). e34050–e34050. 16 indexed citations
6.
Purushothaman, Vidya, et al.. (2022). Content and trend analysis of user-generated nicotinesickness tweets: A retrospective infoveillance study. Tobacco Induced Diseases. 20(March). 1–9.
7.
Purushothaman, Vidya, Raphael Cuomo, Eric C. Leas, et al.. (2022). Longitudinal analysis of tobacco and vape retail density in California. Tobacco Induced Diseases. 20(October). 1–12. 1 indexed citations
9.
Cuomo, Raphael, et al.. (2022). Estimating County-Level Overdose Rates Using Opioid-Related Twitter Data: Interdisciplinary Infodemiology Study. JMIR Formative Research. 7. e42162–e42162. 5 indexed citations
10.
Nali, Matthew, et al.. (2022). Synthetic Cannabinoids in Prisons: Content Analysis of TikToks. SHILAP Revista de lepidopterología. 2(1). e37632–e37632. 2 indexed citations
11.
Hasselgren, Anton, Marcela Tuler de Oliveira, Hortensia De la Corte‐Rodríguez, et al.. (2021). Test, Trace, and Put on the Blockchain?: A Viewpoint Evaluating the Use of Decentralized Systems for Algorithmic Contact Tracing to Combat a Global Pandemic. JMIR Public Health and Surveillance. 7(4). e26460–e26460. 7 indexed citations
12.
Yang, Joshua, Raphael Cuomo, Vidya Purushothaman, et al.. (2021). Campus Smoking Policies and Smoking-Related Twitter Posts Originating From California Public Universities: Retrospective Study. JMIR Formative Research. 5(12). e33331–e33331. 2 indexed citations
13.
Mackey, Tim K., Vidya Purushothaman, Jiawei Li, et al.. (2020). Machine Learning to Detect Self-Reporting of Symptoms, Testing Access, and Recovery Associated With COVID-19 on Twitter: Retrospective Big Data Infoveillance Study. JMIR Public Health and Surveillance. 6(2). e19509–e19509. 101 indexed citations
14.
Yang, Joshua, Virginia Kotzias, Eric Crosbie, & Tim K. Mackey. (2020). COVID-19 and a Window of Opportunity: Guiding Principles for a Health-Promoting Trade Agenda. International Journal of Health Policy and Management. 11(8). 1604–1607. 1 indexed citations
15.
Mackey, Tim K., Jiawei Li, Vidya Purushothaman, et al.. (2020). Big Data, Natural Language Processing, and Deep Learning to Detect and Characterize Illicit COVID-19 Product Sales: Infoveillance Study on Twitter and Instagram. JMIR Public Health and Surveillance. 6(3). e20794–e20794. 67 indexed citations
16.
Mackey, Tim K., Jillian Clare Köhler, Maureen Lewis, & Taryn Vian. (2017). Combating corruption in global health. Science Translational Medicine. 9(402). 19 indexed citations
18.
Mackey, Tim K., et al.. (2016). Gadolinium-based Contrast Agents: Patient Safety Concerns.. PubMed. 87(5). 552M–6M.
19.
Mackey, Tim K., Bryan A. Liang, Amir Attaran, & Jillian Clare Köhler. (2015). Ensuring the Future of Health Information Online. SSRN Electronic Journal.
20.
Liang, Bryan A. & Tim K. Mackey. (2011). Off Label Promotion Reform: A Legislative Proposal Addressing Vulnerable Patient Drug Access and Limiting Inappropriate Pharmaceutical Marketing. SSRN Electronic Journal.

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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