Ruodan Zhang
Biographic Data
| ID | 4372637 |
|---|---|
| NAME | Ruodan Zhang |
| GIVEN NAMES | Ruodan |
| FAMILY NAME | Zhang |
| SIGNATURE | ZHANG R |
| AFFILIATIONS | Indiana University |
| ORCID | 0000-0002-0702-246X |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 1 |
Identifying Nonprofits by Scaling Mission and Activity with Word Embedding
This study develops a new text-as-data method for organization identification, based on word embedding. We introduce and apply the method to identify identity-based nonprofit organizations, using the U.S. nonprofits’ mission and activity information reported in the IRS Form 990s in 2010–2016. Our results show that such method is simple but versatile. It complements the existing dictionary-based approaches and supervised machine learning methods f…
Impact evaluations in South Korea and China
While evidence-based policy-making is increasingly in demand, as new policies are required to bring effective results to targeted groups in South Korea and China, few studies have investigated the progress of quantitative impact evaluation that focuses on causality. This paper studies the trends of quantitative impact evaluation of public policy in South Korea and China by surveying major public administration and public policy journals in these …
Identifying Nonprofits by Scaling Mission and Activity with Word Embedding
This study develops a new text-as-data method for organization identification, based on word embedding. We introduce and apply the method to identify identity-based nonprofit organizations, using the U.S. nonprofits’ mission and activity information reported in the IRS Form 990s in 2010–2016. Our results show that such method is simple but versatile. It complements the existing dictionary-based approaches and supervised machine learning methods f…
Impact evaluations in South Korea and China
While evidence-based policy-making is increasingly in demand, as new policies are required to bring effective results to targeted groups in South Korea and China, few studies have investigated the progress of quantitative impact evaluation that focuses on causality. This paper studies the trends of quantitative impact evaluation of public policy in South Korea and China by surveying major public administration and public policy journals in these …
Identifying Nonprofits by Scaling Mission and Activity with Word Embedding
This study develops a new text-as-data method for organization identification, based on word embedding. We introduce and apply the method to identify identity-based nonprofit organizations, using the U.S. nonprofits’ mission and activity information reported in the IRS Form 990s in 2010–2016. Our results show that such method is simple but versatile. It complements the existing dictionary-based approaches and supervised machine learning methods f…
Political science (2 works) · Advanced Causal Inference Techniques (1 works) · Artificial Intelligence (1 works) · Causality (physics (1 works) · China (1 works) · Computer Science (1 works) · Curse of dimensionality (1 works) · Data science (1 works) · Development economics (1 works) · Dimensionality reduction (1 works)