arXiv AI September 10, 2026 By Yi Yang, Xiao Jia, Zeyun Dong, Chenzhang Wang, Zhanzhan Zhao

Mapping the Emerging Social Science of Large Language Models

The paper maps the nascent social‑science literature on large language models (LLMs) by analysing 198 curated papers and 47,719 field‑scale papers. It identifies three main domains—LLM as Social Minds, LLM Societies, and LLM‑Human Interactions—each containing 13 subcategories such as reasoning, bias, collective intelligence, and trust. The taxonomy is validated through clustering stability, author classification agreement, and topic mapping, revealing differing prominence across conference and journal venues.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

3d ago

The Emergence of Social Science of Large Language Models

arXiv:2509.24877v3 Announce Type: replace Abstract: The social science of large language models (LLMs) examines how these systems evoke mind attributions, interact with one another, and transform hum...

By Xiao Jia, Zhanzhan Zhao

llms rag agents safety

arXiv Computation and Language

Sep 2

Citing Less Critically: LLMs Reshape the Rhetoric and Reach of Scientific Citation

arXiv:2609.01432v1 Announce Type: cross Abstract: Scientific citations carry rhetorical intent. Scholars may cite prior work positively (supporting), negatively (contrasting), or neutrally (mentionin...

By Yixuan Liu, Lin Chen, Zhuoqi Liu, Jianglin Lu, Dakota Murray

llms nlp safety

arXiv AI

Aug 28

How LLMs Distort Our Written Language

Large language models (LLMs) are widely used to assist writing, but this study shows they alter both tone and meaning of human text. A user study found that heavy LLM use increased neutral essays by nearly 70% and made writers feel less creative and less in their voice. Even when prompted to make only grammar edits, LLMs changed the semantic content of essays and produced AI-generated scientific reviews that were less focused on clarity and significance and scored higher on average.

By Marwa Abdulhai, Isadora White, Yanming Wan, Ibrahim Qureshi, Joel Z. Leibo, Max Kleiman-Weiner, Natasha Jaques

llms

arXiv AI

Jun 11

Mapping Scientific Literature with Large Language Models and Topic Modeling

arXiv:2510. 16152v2 Announce Type: replace-cross Abstract: Scientific literature is increasingly fragmented by disciplinary boundaries, specialized terminology, and potentially sparse keyword systems, making it difficult to capture the evolving structure of modern science.

By Mason Smetana, Lev Khazanovich

llms nlp

arXiv AI

Jun 26

Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods

arXiv:2606. 26130v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to guide research methodology, yet their default methodological tendencies under minimal prompting remain unclear.

By Francesca Carlon, Brecht Verbeken, Vincent Ginis, Andres Algaba

llms benchmarks

arXiv Computation and Language

Sep 1

Do LLMs Change Their Minds Like Humans? Diagnosing Human--LLM Divergence in Single-Turn Persuasion Judgments

arXiv:2608.29803v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as proxies for human participants in social simulations, yet whether they update their beliefs...

By Lin Chen, Yitong Chen, Yong Li

llms

One email a morning, machine-written

Related stories

The Emergence of Social Science of Large Language Models

Citing Less Critically: LLMs Reshape the Rhetoric and Reach of Scientific Citation

How LLMs Distort Our Written Language

Mapping Scientific Literature with Large Language Models and Topic Modeling

Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods

Do LLMs Change Their Minds Like Humans? Diagnosing Human--LLM Divergence in Single-Turn Persuasion Judgments