Mark Ching‐Pong Poo
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Co-authorship network of co-authors of Mark Ching‐Pong Poo
This figure shows the co-authorship network connecting the top 25 collaborators of Mark Ching‐Pong Poo. A scholar is included among the top collaborators of Mark Ching‐Pong Poo 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 Mark Ching‐Pong Poo. Mark Ching‐Pong Poo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
Mark Ching‐Pong Poo
20 papers receiving 207 citations
Fields of papers citing papers by Mark Ching‐Pong Poo
This network shows the impact of papers produced by Mark Ching‐Pong Poo. 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 Mark Ching‐Pong Poo. The network helps show where Mark Ching‐Pong Poo may publish in the future.
Countries citing papers authored by Mark Ching‐Pong Poo
This map shows the geographic impact of Mark Ching‐Pong Poo'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 Mark Ching‐Pong Poo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Ching‐Pong Poo more than expected).
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.