Jiaao Chen
Biographic Data
| ID | 4004659 |
|---|---|
| NAME | Jiaao Chen |
| GIVEN NAMES | Jiaao |
| FAMILY NAME | Chen |
| SIGNATURE | CHEN J |
| AFFILIATIONS | Central South University of Forestry and Technology |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 49 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Attractiveness of urban open spaces in the information Era
Insights into the risk of Covid-19 infection in urban neighborhood and its environmental influence factors
Mapping urban green equity and analysing its impacted mechanisms
Quantifying and mapping landscape value using online texts
Can Large Language Models Transform Computational Social Science
Large language models (LLMs) are capable of successfully performing many language processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify and explain social phenomena like persuasiveness and political ideology, then LLMs could augment the computational social science (CSS) pipeline in important ways. This work provides a road map for using LLMs as CSS tools. Towards this end, we contribute a set of prompti…
Can Large Language Models Transform Computational Social Science
Large language models (LLMs) are capable of successfully performing many language processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify and explain social phenomena like persuasiveness and political ideology, then LLMs could augment the computational social science (CSS) pipeline in important ways. This work provides a road map for using LLMs as CSS tools. Towards this end, we contribute a set of prompti…
Quantifying and mapping landscape value using online texts
Can Large Language Models Transform Computational Social Science
Large language models (LLMs) are capable of successfully performing many language processing tasks zero-shot (without training data). If zero-shot LLMs can also reliably classify and explain social phenomena like persuasiveness and political ideology, then LLMs could augment the computational social science (CSS) pipeline in important ways. This work provides a road map for using LLMs as CSS tools. Towards this end, we contribute a set of prompti…
Insights into the risk of Covid-19 infection in urban neighborhood and its environmental influence factors
Mapping urban green equity and analysing its impacted mechanisms
Attractiveness of urban open spaces in the information Era
Geography (3 works) · Land Use and Ecosystem Services (3 works) · Environmental planning (2 works) · Perception (2 works) · Urban Green Space and Health (2 works) · Urban planning (2 works) · 2019-20 coronavirus outbreak (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Attractiveness (1 works)