Citation score normalized by cited references (CSNCR): The introduction of a new citation impact indicator

Bornmann, Lutz; Haunschild, Robin

doi:10.1016/j.joi.2016.07.002

Cited by 30 publications

(25 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Citation score normalized by cited references (CSNCR) Bornmann and Haunschild (2016) introduced the field-normalized indicator "citation score normalized by cited references" (CSNCR) which is closely related to the MNCS. The indicator is rooted in early suggestions by Garfield (1979) that "the most accurate measure of citation potential is the average number of references per paper published in a given field".…”

Section: 3mentioning

confidence: 99%

“…The CSNCR is defined as follows: the citations of a focal paper are divided by the mean number of cited references in a subject category. The theoretical analysis of the CSNCR by Bornmann and Haunschild (2016) demonstrated that the indicator has the properties of consistency and homogeneous normalization. The authors' empirical comparison of the CSNCR with other field-normalized indicators revealed that it is as suitable as other fieldnormalized indicators to normalize citations.…”

Section: 3mentioning

confidence: 99%

See 1 more Smart Citation

How well does I3 perform for impact measurement compared to other bibliometric indicators? The convergent validity of several (field-normalized) indicators

2019

Self Cite

View full text Add to dashboard Cite

Recently, the integrated impact indicator (I3) indicator was introduced where citations are weighted in accordance with the percentile rank class of each publication in a set of publications. I3 can also be used as a field-normalized indicator. Field-normalization is common practice in bibliometrics, especially when institutions and countries are compared.Publication and citation practices are so different among fields that citation impact is normalized for cross-field comparisons. In this study, we test the ability of the indicator to discriminate between quality levels of papers as defined by Faculty members at F1000Prime.F1000Prime is a post-publication peer review system for assessing papers in the biomedical area. Thus, we test the convergent validity of I3 (in this study, we test I3/Nthe sizeindependent variant of I3 where I3 is divided by the number of papers) using assessments by peers as baseline and compare its validity with several other (field-normalized) indicators: the mean-normalized citation score (MNCS), relative-citation ratio (RCR), citation score normalized by cited references (CSNCR), characteristic scores and scales (CSS), sourcenormalized citation score (SNCS), citation percentile, and proportion of papers which belong to the x% most frequently cited papers (PPtop x%). The results show that the PPtop 1% indicator discriminates best among different quality levels. I3 performs similar as (slightly better than) most of the other field-normalized indicators. Thus, the results point out that the indicator could be a valuable alternative to other indicators in bibliometrics.

show abstract

Section: 3mentioning

confidence: 99%

Section: 3mentioning

confidence: 99%

How well does I3 perform for impact measurement compared to other bibliometric indicators? The convergent validity of several (field-normalized) indicators

2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…The focus on a well-defined target obviates the normalization of citation impact which is necessary in the times cited analysis: professional bibliometrics without normalization is difficult to imagine because impact using times cited data is mostly measured across different fields. The focus on one field (or topic) in the CRA implies field normalization and avoids advanced methods of field normalization, which are described by Waltman (2016) or Bornmann and Haunschild (2016).…”

Section: Spectroscopy (Rpys)mentioning

confidence: 99%

Identifying single influential publications in a research field: new analysis opportunities of the CRExplorer

Thor¹,

Bornmann

Marx

et al. 2018

Scientometrics

Self Cite

View full text Add to dashboard Cite

Reference Publication Year Spectroscopy (RPYS) has been developed for identifying the cited references (CRs) with the greatest influence in a given paper set (mostly sets of papers on certain topics or fields). The program CRExplorer (see www.crexplorer.net) was specifically developed by Bornmann (2016a, 2016b) for applying RPYS to publication sets downloaded from Scopus or Web of Science. In this study, we present some advanced methods which have been newly developed for CRExplorer. These methods are able to identify and characterize the CRs which have been influential across a longer period (many citing years). The new methods are demonstrated in this study using all the papers published in Scientometrics between 1978 and 2016. The indicators N_TOP50, N_TOP25, and N_TOP10 can be used to identify those CRs which belong to the 50%, 25%, or 10% most frequently cited publications (CRs) over many citing publication years. In the Scientometrics dataset, for example, Lotka's (1926) paper on the distribution of scientific productivity belongs to the top 10% publications (CRs) in 36 citing years. Furthermore, the new version of CRExplorer analyzes the impact sequence of CRs across citing years. CRs can have below average (-), average (0), or above average (+) impact in citing years (whereby average is meant in the sense of expected values). The sequence (e.g. 00++---0--00) is used by the program to identify papers with typical impact distributions. For example, CRs can have early, but not late impact ("hot papers", e.g. +++---) or vice versa ("sleeping beauties", e.g. ---0000---++).

show abstract

“…Another difficulty of citation analysis is the skewed distribution of publications attending to the number of citations (Seglen, 1992;Albarrán et al, 2011a), which makes it difficult to extract relevant information for research assessment from the analysis of simple citation counting. Several approaches have been proposed to extract this information considering citation distribution (Glanzel and Schubert, 1988;Adams et al, 2007;Bornmann et al, 2008;Bornmann et al, 2013c;Li et al, 2013;Bornmann and Mutz, 2014;Glanzel et al, 2014;Albarrán et al, 2015;Bornmann and Haunschild, 2016a;Schneider and Costas, 2017), including some that specifically attend to both the number of highly and lowly cited papers (Albarrán et al, 2011c;2011b;2011d). All these methods have been developed under strict mathematical and statistical considerations but all have the aforementioned problem of difficult validation.…”

Section: Introductionmentioning

confidence: 99%

Research assessment by percentile-based double rank analysis

Brito

Rodríguez‐Navarro

2018

Journal of Informetrics

View full text Add to dashboard Cite

In the double rank analysis of research publications, the local rank position of a country or institution publication is expressed as a function of the world rank position. Excluding some highly or lowly cited publications, the double rank plot fits well with a power law, which can be explained because citations for local and world publications follow lognormal distributions. We report here that the distribution of the number of country or institution publications in world percentiles is a double rank distribution that can be fitted to a power law. Only the data points in high percentiles deviate from it when the local and world µ parameters of the lognormal distributions are very different.The likelihood of publishing very highly cited papers can be calculated from the power law that can be fitted either to the upper tail of the citation distribution or to the percentile-based double rank distribution. The great advantage of the latter method is that it has universal application, because it is based on all publications and not just on highly cited publications. Furthermore, this method extends the application of the wellestablished percentile approach to very low percentiles where breakthroughs are reported but paper counts cannot be performed.

show abstract

Citation score normalized by cited references (CSNCR): The introduction of a new citation impact indicator

Cited by 30 publications

References 57 publications

How well does I3 perform for impact measurement compared to other bibliometric indicators? The convergent validity of several (field-normalized) indicators

How well does I3 perform for impact measurement compared to other bibliometric indicators? The convergent validity of several (field-normalized) indicators

Identifying single influential publications in a research field: new analysis opportunities of the CRExplorer

Research assessment by percentile-based double rank analysis

Contact Info

Product

Resources

About