Applying the Publication Power Approach to Artificial Intelligence Journals

Abstract

This study evaluates the utility of a publication power approach (PPA) for assessing the quality of journals in the field of artificial intelligence. PPA is compared with the Thomson‐Reuters Institute for Scientific Information (TR) 5‐year and 2‐year impact factors and with expert opinion. The ranking produced by the method under study is only partially correlated with citation‐based measures (TR), but exhibits close agreement with expert survey rankings. A simple average of TR and power rankings results in a new ranking that is highly correlated with the expert survey rankings. This evidence suggests that power ranking can contribute to evaluating artificial intelligence journals.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 8 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.