Correlational analysis of topic specificity and citations count of publication venues

Abstract

Purpose Citation analysis is an important measure for the assessment of quality and impact of academic entities (authors, papers and publication venues) used for ranking of research articles, authors and publication venues. It is a common observation that high-level publication venues, with few exceptions (Nature, Science and PLOS ONE), are usually topic specific. The purpose of this paper is to investigate the claim correlation analysis between topic specificity and citation count of different types of publication venues (journals, conferences and workshops). Design/methodology/approach The topic specificity was calculated using the information theoretic measure of entropy (which tells us about the disorder of the system). The authors computed the entropy of the titles of the papers published in each venue type to investigate their topic specificity. Findings It was observed that venues usually with higher citations (high-level publication venues) have low entropy and venues with lesser citations (not-high-level publication venues) have high entropy. Low entropy means less disorder and more specific to topic and vice versa. The input data considered here were DBLP-V7 data set for the last 10 years. Experimental analysis shows that topic specificity and citation count of publication venues are negatively correlated to each other. Originality/value This paper is the first attempt to discover correlation between topic sensitivity and citation counts of publication venues. It also used topic specificity as a feature to rank academic entities.

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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 — 21 citations exist upstream.

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