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.
The Tipping Point: How Little Things Can Make a Big Difference
Countries citing papers authored by Danny Meadows-Klue
Since Specialization
Citations
This map shows the geographic impact of Danny Meadows-Klue'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 Danny Meadows-Klue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danny Meadows-Klue more than expected).
Fields of papers citing papers by Danny Meadows-Klue
This network shows the impact of papers produced by Danny Meadows-Klue. 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 Danny Meadows-Klue. The network helps show where Danny Meadows-Klue may publish in the future.
Danny Meadows-Klue is a scholar working on Marketing, Information Systems and Management and Sociology and Political Science, having authored 9 papers that have together received 1.5k indexed citations. Recurring topics across this work include Digital Marketing and Social Media (4 papers), Marketing and Advertising Strategies (3 papers) and Technology Adoption and User Behaviour (1 paper). The work is most often cited by research in Communication (137 citations), Statistical and Nonlinear Physics (139 citations) and Sociology and Political Science (484 citations). Danny Meadows-Klue has collaborated with scholars based in United States. Their work appears in journals such as Journal of Direct Data and Digital Marketing Practice and The business & management collection..
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.