arbiter
JournalsAccount

Restoring the forecasting power of Google Trends with statistical preprocessing

Candice Djorno et al.

International Journal of Forecasting2026https://doi.org/10.1016/j.ijforecast.2026.03.001article
AJG 3ABDC A
Weight
0.37

Abstract

No abstract available.

1 citation

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1016/j.ijforecast.2026.03.001

Or copy a formatted citation

@article{candice2026,
  title        = {{Restoring the forecasting power of Google Trends with statistical preprocessing}},
  author       = {Candice Djorno et al.},
  journal      = {International Journal of Forecasting},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.ijforecast.2026.03.001},
}

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

Flag this paper

Restoring the forecasting power of Google Trends with statistical preprocessing

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

Evidence weight

0.37

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

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
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.