Lin Bian

1.9k total citations · 1 hit paper
7 papers, 1.1k citations indexed

About

Lin Bian is a scholar working on Sociology and Political Science, Cognitive Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Lin Bian has authored 7 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Sociology and Political Science, 3 papers in Cognitive Neuroscience and 3 papers in Experimental and Cognitive Psychology. Recurrent topics in Lin Bian's work include Social and Intergroup Psychology (4 papers), Child and Animal Learning Development (3 papers) and Gender Diversity and Inequality (2 papers). Lin Bian is often cited by papers focused on Social and Intergroup Psychology (4 papers), Child and Animal Learning Development (3 papers) and Gender Diversity and Inequality (2 papers). Lin Bian collaborates with scholars based in United States and South Korea. Lin Bian's co-authors include Sarah‐Jane Leslie, Andrei Cimpian, Renée Baillargeon, Rose M. Scott, Mary C. Murphy, Stephanie Sloane and Kyong‐sun Jin and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and American Psychologist.

In The Last Decade

Lin Bian

7 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

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.

Gender stereotypes about intellectual ability emerge early and influence children’s interests

2017 691 citations Lin Bian, Sarah‐Jane Leslie et al. Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lin Bian United States	6	328	299	294	289	288	7	1.1k
Edward P. Freeland United States	4	302 0.9×	107 0.4×	267 0.9×	202 0.7×	295 1.0×	5	964
David M. Marx United States	13	336 1.0×	86 0.3×	218 0.7×	371 1.3×	265 0.9×	23	1.1k
Talia Ben‐Zeev United States	11	336 1.0×	105 0.4×	221 0.8×	381 1.3×	304 1.1×	17	1.1k
Margaret L. Signorella United States	20	627 1.9×	164 0.5×	341 1.2×	226 0.8×	226 0.8×	42	1.3k
Sarah E. Martiny Norway	18	258 0.8×	75 0.3×	244 0.8×	385 1.3×	195 0.7×	56	1.1k
Jean‐Claude Croizet France	18	315 1.0×	101 0.3×	366 1.2×	593 2.1×	328 1.1×	38	1.5k
Erica S. Weisgram United States	17	443 1.4×	126 0.4×	299 1.0×	181 0.6×	233 0.8×	20	1.0k
Benjamin J. Drury United States	6	433 1.3×	113 0.4×	167 0.6×	191 0.7×	174 0.6×	6	931
Evava S. Pietri United States	17	267 0.8×	74 0.2×	238 0.8×	204 0.7×	98 0.3×	38	897
Amanda M. Johnston United States	5	319 1.0×	113 0.4×	255 0.9×	226 0.8×	324 1.1×	8	991

Countries citing papers authored by Lin Bian

Since Specialization

Citations

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

Fields of papers citing papers by Lin Bian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lin Bian

This figure shows the co-authorship network connecting the top 25 collaborators of Lin Bian. A scholar is included among the top collaborators of Lin Bian 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 Lin Bian. Lin Bian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Bian, Lin, et al.. (2025). Gender Bias Against Women and Girls in Brilliance-Required Contexts: Evidence from Korean Adults. Sex Roles. 91(10). 1 indexed citations

2.

Bian, Lin & Renée Baillargeon. (2022). When Are Similar Individuals a Group? Early Reasoning About Similarity and In-Group Support. Psychological Science. 33(5). 752–764. 10 indexed citations

3.

Bian, Lin, Sarah‐Jane Leslie, Mary C. Murphy, & Andrei Cimpian. (2018). Messages about brilliance undermine women's interest in educational and professional opportunities. Journal of Experimental Social Psychology. 76. 404–420. 121 indexed citations

4.

Bian, Lin, Sarah‐Jane Leslie, & Andrei Cimpian. (2018). Evidence of bias against girls and women in contexts that emphasize intellectual ability.. American Psychologist. 73(9). 1139–1153. 71 indexed citations

5.

Bian, Lin, Stephanie Sloane, & Renée Baillargeon. (2018). Infants expect ingroup support to override fairness when resources are limited. Proceedings of the National Academy of Sciences. 115(11). 2705–2710. 71 indexed citations

6.

Bian, Lin, Sarah‐Jane Leslie, & Andrei Cimpian. (2017). Gender stereotypes about intellectual ability emerge early and influence children’s interests. Science. 355(6323). 389–391. 691 indexed citations breakdown →

7.

Baillargeon, Renée, Rose M. Scott, & Lin Bian. (2015). Psychological Reasoning in Infancy. Annual Review of Psychology. 67(1). 159–186. 139 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.

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