A semi-automated approach to policy-relevant evidence synthesis: Combining natural language processing, causal mapping, and graph analytics for public policy

Rory Hooper, Nihit Goyal, Kornelis Blok, Lisa Scholten

Open source

DOI
10.21203/rs.3.rs-3285731/v1
Published
2023-08-23
Container
Not recorded
Publisher
Springer Science and Business Media LLC
Open access
unknown

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BibTeX

@article{allodium:10.21203/rs.3.rs-3285731/v1,
  title = {A semi-automated approach to policy-relevant evidence synthesis: Combining natural language processing, causal mapping, and graph analytics for public policy},
  author = {Rory Hooper and Nihit Goyal and Kornelis Blok and Lisa Scholten},
  year = {2023},
  doi = {10.21203/rs.3.rs-3285731/v1},
  url = {https://doi.org/10.21203/rs.3.rs-3285731/v1}
}

RIS

TY  - JOUR
TI  - A semi-automated approach to policy-relevant evidence synthesis: Combining natural language processing, causal mapping, and graph analytics for public policy
AU  - Rory Hooper
AU  - Nihit Goyal
AU  - Kornelis Blok
AU  - Lisa Scholten
PY  - 2023
DO  - 10.21203/rs.3.rs-3285731/v1
UR  - https://doi.org/10.21203/rs.3.rs-3285731/v1
ER  - 

APA

Hooper, R., Goyal, N., Blok, K., & Scholten, L. (2023). A semi-automated approach to policy-relevant evidence synthesis: Combining natural language processing, causal mapping, and graph analytics for public policy. https://doi.org/10.21203/rs.3.rs-3285731/v1

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