Song Jin

11 papers and 354 indexed citations i.

About

Song Jin is a scholar working on Geophysics, Artificial Intelligence and Mechanical Engineering. According to data from OpenAlex, Song Jin has authored 11 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Geophysics, 4 papers in Artificial Intelligence and 2 papers in Mechanical Engineering. Recurrent topics in Song Jin’s work include Geological and Geochemical Analysis (6 papers), earthquake and tectonic studies (5 papers) and Geochemistry and Geologic Mapping (4 papers). Song Jin is often cited by papers focused on Geological and Geochemical Analysis (6 papers), earthquake and tectonic studies (5 papers) and Geochemistry and Geologic Mapping (4 papers). Song Jin collaborates with scholars based in China and France. Song Jin's co-authors include Wen Zeng, Hanwen Zhou, Hua Xiang, Li Zhang, Zengqiu Zhong, Rui Liu, Rui Liu, Chunzhong Li, Wenjie Pei and Shilong Wang and has published in prestigious journals such as Nanoscale, Energy and Lithos.

In The Last Decade

Co-authorship network of co-authors of Song Jin i

Fields of papers citing papers by Song Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Song Jin. 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 Song Jin. The network helps show where Song Jin may publish in the future.

Countries citing papers authored by Song Jin

Since Specialization
Citations

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

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2025