Analysis of Effects to Journal Impact Factors Based on Citation Networks Generated via Social Computing

Abstract

Via the idea of social computing, a simple experimental model is developed as a reference for exploring the variation of journal impact factors, particularly between different disciplines. Our model intends to simulate the publication and citation behaviors of the articles in journals belonging to a similar discipline, in a distributed manner. Based on the citation networks generated, the mechanism of influence from several fundamental factors to the trend of impact factor is better revealed. These factors include the average review cycle, the average number of references, and yearly distribution of references. The analysis also reveals a satisfactory capability of the model for approximation between actual data and simulation results.

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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 — 15 citations exist upstream.

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