||It has been suggested that this article be merged with Citation analysis to Citation impact analysis. (Discuss) Proposed since December 2013.|
||It has been suggested that Impact factor#Other measures of impact be merged into this article. (Discuss) Proposed since December 2013.|
Citation impact can be measured in various ways.
An obvious measure is citation count, which quantifies both the usage and impact of the cited work. This is called citation analysis or bibliometrics. Among the measures that have emerged from citation analysis are the citation counts for:
- an individual article (how often it was cited);
- an author (total citations, or average citation count per article);
- a journal (average citation count for the articles in the journal).
Many measures have been proposed, beyond simple citation counts, to better quantify an individual scholar's citation impact. The best-known measures include the h-index and the g-index. Each measure has advantages and disadvantages, spanning from bias to discipline-dependence and limitations of the citation data source.
An important recent development in research on citation impact is the discovery of universality, or citation impact patterns that hold across different disciplines in the sciences, social sciences, and humanities. For example it has been shown that the number of citations received by a publication, once properly rescaled by its average across articles published in the same discipline and in the same year, follows a universal log-normal distribution that is the same in every discipline. This finding has suggested a universal citation impact measure that extends the h-index by properly rescaling citation counts and resorting publications, however the computation of such a universal measure requires the collection of extensive citation data and statistics for every discipline and year. Social crowdsourcing tools such as Scholarometer have been proposed to address this need.
While citation counts are often correlated with other measures of scholarly and scientific performance, causal statements linking a citation advantage with open access status have been contradicted by some experimental and observational studies.
Research suggests the impact of an article can be, partly, explained by superficial factors and not only by the scientific merits of an article. For instance in Medicine among other factors the number of authors, the number of references, the article length, and the presence of a colon in the title influence the impact. Whilst in Sociology the number of references, the article length, and title length are among the factors.
Automated citation indexing has changed the nature of citation analysis research, allowing millions of citations to be analyzed for large scale patterns and knowledge discovery. The first example of automated citation indexing was CiteSeer, later to be followed by Google Scholar. More recently, advanced models for a dynamic analysis of citation aging have been proposed. The latter model is even used as a predictive tool for determining the citations that might be obtained at any time of the lifetime of a corpus of publications.
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