Paste any public Google Scholar profile. CiteVector pulls the live metrics, reconstructs how they changed over time from Wayback Machine snapshots, projects where they are heading, and attaches Altmetric and Dimensions badges to the top papers.
…&view_op=list_works&sortby=citedby&pagesize=100 to include up to 100 publications. The file is parsed in your browser and never uploaded.Total citations, h-index, i10-index, per-year citation counts and the full publication list, fetched from the profile when you ask.
Every archived copy of the profile in the Wayback Machine is parsed, so you can see citations and h-index as they were on each archived date. CiteVector adds its own observation each time a profile is loaded.
Per-paper citation forecasts (Wang–Song–Barabási aging model with a self-exciting correction) roll up into projected totals, h-index and i10-index.
Top papers are matched to DOIs through OpenAlex, then shown with live Altmetric and Dimensions badges.
Each point is a dated observation of the profile: Wayback archived copies, CiteVector observations recorded by this site, and the live value fetched just now. Hover a point for the exact figures and a link to the archived page.
| # | Title | Venue | Year | Citations | Cit/yr | +1 yr | +3 yr | +5 yr |
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Live data. The profile page and its publication list (sorted by citations, 100 per page) are fetched by the CiteVector server and cached for six hours. Each load also records one observation per day in CiteVector's own history, so the trajectory keeps growing even for profiles the Wayback Machine rarely captures.
Wayback trajectory. The Wayback Machine's CDX index is queried for every archived URL of the profile (any hl= language, with or without view_op=list_works). One snapshot per calendar month is kept, the raw archived HTML is fetched with the id_ flag (no toolbar rewriting), and the metrics table is parsed with the same parser used for live pages. Snapshots whose metrics table cannot be read are listed but not plotted.
Projections. Each paper gets the Wang, Song & Barabási (Science 2013) aging model c(t) = m·(eλ·Φ(t;μ,σ) − 1) with m = 30, where Φ is a log-normal CDF (μ = 0.9, σ = 1.0 in log-years) and λ is inverted from the observed count and paper age. Future increments are scaled by a bounded self-exciting factor in the spirit of Xiao et al. (IJCAI 2016), so papers running ahead of the model are boosted and stale ones damped. Publication dates are taken as mid-year because the profile only exposes the year. Totals, h-index and i10-index are recomputed from the projected per-paper counts at each year-end. Treat these as rough, order-of-magnitude forecasts.
Badges. Top papers are matched to DOIs by title search on OpenAlex (best match with bigram similarity above 0.6). Altmetric and Dimensions badges are embedded by DOI; a paper with no DOI match shows no badge.