arbiter
JournalsPricingAccount

Natural language processing in impact assessment: a review of applications and concerns

Shiu Fung Hung et al.

Impact Assessment and Project Appraisal2026https://doi.org/10.1080/14615517.2026.2620186article
ABDC C
Weight
0.50

What the paper says

The rolling out of Artificial Intelligence (AI) applications is extensively discussed among the impact assessment (IA) community. It is in this context that our letter focuses on natural language processing (NLP) applications. We introduce six categories of NLP applications and examine common concerns over their accuracy, quality, and transparency. We emphasize that it is the users’ responsibility to ensure quality and transparency when applying AI. We also suggest that it is time to elevate the discussion on the preparation for further AI use in IA.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.1080/14615517.2026.2620186

Or copy a formatted citation

@article{shiu2026,
  title        = {{Natural language processing in impact assessment: a review of applications and concerns}},
  author       = {Shiu Fung Hung et al.},
  journal      = {Impact Assessment and Project Appraisal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/14615517.2026.2620186},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Natural language processing in impact assessment: a review of applications and concerns

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.