大模型时代的社会科学，何去何从？

doi:10.13366/j.dik.2023.06.006

Documentation, Informaiton & Knowledge ›› 2023, Vol. 40 ›› Issue (6): 6-9,30.doi: 10.13366/j.dik.2023.06.006

• Viewpoint and Perspective • Previous Articles Next Articles

The Landscape of Social Science in the Era of Large Language Models

XIE Tian¹, QIU Lin², LI Yutong², LUO Yin³, LIU Pan⁴

1. Department of Psychology, Philosophy School, Wuhan University, Wuhan, 430072;
2. School of Social Sciences, Nanyang Technological University, Singapore, 639798;
3. Interdisciplinary Graduate School–Global Asia, Nanyang Technological University, Singapore, 639798;
4.School of Public Administration, Hunan University, Changsha, 410082

Online:2023-11-10 Published:2023-12-10
Contact: Correspondence should be addressed to QIU Lin,Email: linqiu@ntu.edu.sg, ORCID：0000-0002-3587-5371
Supported by:
This is an outcome of the Major Project "Constructing the 'Circle of Friends' in Global Media from the Perspective of Intercultural Communication"（22JJD860013）supported by Key Research Base for Humanities and Social Sciences of the Ministry of Education, and the project "Multidisciplinary Integration Platform for Cultural Evolution"（WHTUDKUZZJ202306）supported by a grant from the Joint Research Platform Seed Foundation Supporting Program of Wuhan University-Duke Kunshan University in 2023.

Abstract

Abstract: Large language models（such as GPT）have brought unprecedented breakthroughs in the field of artificial intelligence. In this article, we briefly introduce large language models, and illustrate how such models have been applied in each stage of social science research, including literature review, theory formation, research design, data collection, and data analysis. We envision new research paradigms brought by large language models, and new challenges faced by social science researchers.

Key words: Artificial Intelligence, Large language models, GPT（Generative Pretrained Transformer）, Social science, Research methods, Research paradigm

XIE Tian, QIU Lin, LI Yutong, LUO Yin, LIU Pan. The Landscape of Social Science in the Era of Large Language Models[J]. Documentation, Informaiton & Knowledge, 2023, 40(6): 6-9,30.

[1]	PAN Yuchen, HU Wei, YANG Jianliang, XU Lu, LU Xiaobin. The Design of Artificial Intelligence Curriculum for Information Resources Management Under the New Liberal Arts [J]. Documentation, Informaiton & Knowledge, 2023, 40(6): 42-51, 67.
[2]	GONG Furong. The Impact of Generative AI like ChatGPT on Digital Literacy Education in University Libraries [J]. Documentation, Informaiton & Knowledge, 2023, 40(5): 97-106,156.
[3]	XIAO Peng. Using "Specialized Databases" as a Method: Reimagining Digital Humanities and Its Development Trends in the AI Era [J]. Documentation, Informaiton & Knowledge, 2023, 40(5): 16-27.
[4]	ZHANG Tongyang, WANG Chuhan, YU Chao, XU Jian. Academic Literature Data Sets Towards the AI Era: Characteristics and Development Direction [J]. Documentation, Informaiton & Knowledge, 2023, 40(5): 39-49.
[5]	ZHANG Xinxin, DING Jingjia. Technical Principles and Process Innovations of Generative Intelligent Publishing [J]. Documentation, Informaiton & Knowledge, 2023, 40(5): 68-76.
[6]	ZHANG Xinxin, HUANG Ruhua. Application Scenarios, Risk Challenges and Regulatory Pathways of Generative Intelligent Publishing [J]. Documentation, Informaiton & Knowledge, 2023, 40(5): 77-86,27.
[7]	MO Zuying, PAN Daqing, LIU Huan, ZHAO Yueming. Analysis on AIGC False Information Problem and Root Cause from the Perspective of Information Quality [J]. Documentation, Informaiton & Knowledge, 2023, 40(4): 32-40.
[8]	Niels Peter Thomas. Artificial Intelligence and Scholarly Publishing [J]. Documentation, Informaiton & Knowledge, 2023, 40(4): 6-9.
[9]	ZHU Yu, CHEN Guanze, LU Yongrong, FAN Wei. Generative Artificial Intelligence Governance Action Framework:Content Analysis Based on AIGC Incident Report Texts [J]. Documentation, Informaiton & Knowledge, 2023, 40(4): 41-51.
[10]	SONG Xiaokang, ZHAO Yuxiang, SONG Shijie, ZHU Qinghua. The Features, Theoretical Framework and Research Prospects of AI-enabled Surrogate Information Searching: A Sociotechnical System Paradigm [J]. Documentation, Informaiton & Knowledge, 2023, 40(4): 111-121.
[11]	. The Technical Features and Aromorphosis of Artificial Intelligence Generated Content (AIGC) [J]. Documentation, Informaiton & Knowledge, 2023, 40(1): 66-74.
[12]	. Application Scenarios and Development Opportunities of AIGC in the Digital Intelligence Integration Environment [J]. Documentation, Informaiton & Knowledge, 2023, 40(1): 75-85.
[13]	. Research Paradigm and Platform Construction of Digital Humanities [J]. Documentation, Informaiton & Knowledge, 2022, 39(1): 6-29.
[14]	. Study on Epidemic Information Management in the Age of Artificial Intelligence: Challenges and Changes [J]. Document,Informaiton & Knowledge, 2020, 0(6): 109-116.
[15]	. Correlation Analysis on Peer Review and Impact Factor of Journal Evaluation in Humanities and Social Science [J]. Document,Informaiton & Knowledge, 2020, 0(3): 128-136.

The Landscape of Social Science in the Era of Large Language Models

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments