Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Natural Products as Sources of New Drugs from 1981 to 2014
This map shows the geographic impact of David Newman'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 David Newman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Newman more than expected).
This network shows the impact of papers produced by David Newman. 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 David Newman. The network helps show where David Newman may publish in the future.
Co-authorship network of co-authors of David Newman
This figure shows the co-authorship network connecting the top 25 collaborators of David Newman.
A scholar is included among the top collaborators of David Newman 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 David Newman. David Newman is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Eastwood, J. P., David Newman, Xiao‐Jia Zhang, et al.. (2016). Ion and electron kinetic physics associated with magnetotail dipolarization fronts. EGU General Assembly Conference Abstracts.1 indexed citations
Li, Chen, et al.. (2012). Analysis of Instant Search Query Logs.. 7–12.6 indexed citations
9.
Lau, Jey Han, Karl Grieser, David Newman, & Timothy Baldwin. (2011). Automatic Labelling of Topic Models. Meeting of the Association for Computational Linguistics. 1536–1545.114 indexed citations
10.
Lau, Jey Han, David Newman, Sarvnaz Karimi, & Timothy Baldwin. (2010). Best Topic Word Selection for Topic Labelling. Minerva Access (University of Melbourne). 605–613.43 indexed citations
Newman, David, Sarvnaz Karimi, & Lawrence Cavedon. (2009). External evaluation of topic models. RMIT Research Repository (RMIT University Library). 1–8.43 indexed citations
13.
Buckley, Michael, David Newman, Leonard Liebes, et al.. (2005). Para-aminobenzoic acid (PABA) enhances the in-vitro tumor response of ovarian cancer to Topotecan (TTN) through mitochondrial-mediated apoptosis. Cancer Research. 65. 1258–1258.3 indexed citations
14.
O’Riordan, Shelagh, David Simpson, Michelle Webb, et al.. (2002). Pharmacology. Age and Ageing. 31(suppl 1). 38–38.
Newman, David. (1960). Another proof of the minimax theorem. Proceedings of the American Mathematical Society. 11(5). 692–693.2 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.