scientometrics

To compute author-level bibliometric metrics like the h-index, the skill processes OpenAlex publication data to calculate h-index, total citations, i10-index, top venues, and active years for a specified ORCID. It returns a summary of these computed metrics for author evaluation.

Yes, you can build co-authorship networks and export them for VOSviewer. The skill uses NetworkX to build network graphs and generates VOSviewer-compatible node and edge files, enabling interactive visualization of the strongest clusters.

Bibliographic coupling and co-citation analysis map research structure by quantifying citation relationships between publications. The skill computes these bibliometric relationships from OpenAlex data to identify research connections and emerging fronts across specified year ranges.

Yes, you need Python libraries like pandas and networkx to run scientometric analysis. The skill requires HTTP access to the OpenAlex API and utilizes pandas, networkx, numpy, and scipy to process publication data and compute science-network structures.

The best way to visualize topic landscapes and research clusters from publication data is by computing co-citation and bibliographic coupling metrics. This skill calculates these structures and exports VOSviewer-compatible files for interactive exploration of research relationships.

Yes, you can use OpenAlex API data to evaluate researchers without manually wrangling publication datasets. The skill automates bibliometric analysis to quantify scientific impact, directly fetching and processing publication data to measure researchers and fields.