Differences In Citation Practices Research Articles

Citation practices in tourism research: Toward a gender conscientious engagement

This study explores gender gaps and differences in citation practices of scholars in the top-cited articles in tourism research. The results suggest that male researchers dominate the authorship of those articles and are more likely to engage in self-citation than females. The study also finds a disparity in citation counts between male- and female-authored articles. Controlling for other factors, author gender is an important determinant of citation counts. The study advocates for a more gender conscious citation practices and provides potential gender-based interventions to reduce the citation gap. The research raises awareness about the dangers of the perfunctory use of citations and paves the way for further debates on the politics and embedded inequalities of citations in tourism research.

Types and Functions of Citations in Native vs. Non-native Written Medical Research Articles

Citation is an essential prevalent feature of all academic writings in various fields of knowledge. It is employed by authors and researchers across disciplines for diverse reasons. This study was aimed at comparing types and functions of citations in medical research articles in discussion sections between Iranian medical faculty members and their native counterparts. Method: To this end, discussion sections of 48 native and non-native written Research Articles (RAs) from credible ISI-indexed journals with good impact factor (about 0.5-1.5) from each group were analyzed in terms of citation types and functions. Results: The results revealed that non-integral citations were found to be the most frequent citation type both among RAs written by non-native and native researchers. Also, Vancouver referencing style in non-native articles was used more while in native articles APA referencing style was the dominant style. Concerning citation functions, referencing was the most common one in native articles. However, referencing and comparisons were the most two frequent functions among non-native articles. As the results revealed, there were striking differences in citation practices of native and non-native researchers in medical sciences. Conclusion: This study calls for reevaluation of citation practices among Iranian authors and systematic treatment of types and functions of citations in ESM and EAP writing courses

Field-normalized citation impact indicators using algorithmically constructed classification systems of science

Abstract We study the problem of normalizing citation impact indicators for differences in citation practices across scientific fields. Normalization of citation impact indicators is usually done based on a field classification system. In practice, the Web of Science journal subject categories are often used for this purpose. However, many of these subject categories have a quite broad scope and are not sufficiently homogeneous in terms of citation practices. As an alternative, we propose to work with algorithmically constructed classification systems. We construct these classification systems by performing a large-scale clustering of publications based on their citation relations. In our analysis, 12 classification systems are constructed, each at a different granularity level. The number of fields in these systems ranges from 390 to 73,205 in granularity levels 1–12. This contrasts with the 236 subject categories in the WoS classification system. Based on an investigation of some key characteristics of the 12 classification systems, we argue that working with a few thousand fields may be an optimal choice. We then study the effect of the choice of a classification system on the citation impact of the 500 universities included in the 2013 edition of the CWTS Leiden Ranking. We consider both the MNCS and the PP top 10% indicator. Globally, for all the universities taken together citation impact indicators generally turn out to be relatively insensitive to the choice of a classification system. Nevertheless, for individual universities, we sometimes observe substantial differences between indicators normalized based on the journal subject categories and indicators normalized based on an appropriately chosen algorithmically constructed classification system.

The effect on citation inequality of differences in citation practices at the web of science subject category level

This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz‐Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ∼14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all‐sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.

Quantitative evaluation of alternative field normalization procedures

Wide differences in publication and citation practices make impossible the direct comparison of raw citation counts across scientific disciplines. Recent research has studied new and traditional normalization procedures aimed at suppressing as much as possible these disproportions in citation numbers among scientific domains. Using the recently introduced IDCP (Inequality due to Differences in Citation Practices) method, this paper rigorously tests the performance of six cited-side normalization procedures based on the Thomson Reuters classification system consisting of 172 sub-fields. We use six yearly datasets from 1980 to 2004, with widely varying citation windows from the publication year to May 2011. The main findings are the following three. Firstly, as observed in previous research, within each year the shapes of sub-field citation distributions are strikingly similar. This paves the way for several normalization procedures to perform reasonably well in reducing the effect on citation inequality of differences in citation practices. Secondly, independently of the year of publication and the length of the citation window, the effect of such differences represents about 13% of total citation inequality. Thirdly, a recently introduced two-parameter normalization scheme outperforms the other normalization procedures over the entire period, reducing citation disproportions to a level very close to the minimum achievable given the data and the classification system. However, the traditional procedure of using sub-field mean citations as normalization factors yields also good results.

Citation Analysis May Severely Underestimate the Impact of Clinical Research as Compared to Basic Research

BackgroundCitation analysis has become an important tool for research performance assessment in the medical sciences. However, different areas of medical research may have considerably different citation practices, even within the same medical field. Because of this, it is unclear to what extent citation-based bibliometric indicators allow for valid comparisons between research units active in different areas of medical research.MethodologyA visualization methodology is introduced that reveals differences in citation practices between medical research areas. The methodology extracts terms from the titles and abstracts of a large collection of publications and uses these terms to visualize the structure of a medical field and to indicate how research areas within this field differ from each other in their average citation impact.ResultsVisualizations are provided for 32 medical fields, defined based on journal subject categories in the Web of Science database. The analysis focuses on three fields: Cardiac & cardiovascular systems, Clinical neurology, and Surgery. In each of these fields, there turn out to be large differences in citation practices between research areas. Low-impact research areas tend to focus on clinical intervention research, while high-impact research areas are often more oriented on basic and diagnostic research.ConclusionsPopular bibliometric indicators, such as the h-index and the impact factor, do not correct for differences in citation practices between medical fields. These indicators therefore cannot be used to make accurate between-field comparisons. More sophisticated bibliometric indicators do correct for field differences but still fail to take into account within-field heterogeneity in citation practices. As a consequence, the citation impact of clinical intervention research may be substantially underestimated in comparison with basic and diagnostic research.

The Measurement of the Effect on Citation Inequality of Differences in Citation Practices across Scientific Fields

This paper has two aims: (i) to introduce a novel method for measuring which part of overall citation inequality can be attributed to differences in citation practices across scientific fields, and (ii) to implement an empirical strategy for making meaningful comparisons between the number of citations received by articles in 22 broad fields. The number of citations received by any article is seen as a function of the article’s scientific influence, and the field to which it belongs. A key assumption is that articles in the same quantile of any field citation distribution have the same degree of citation impact in their respective field. Using a dataset of 4.4 million articles published in 1998–2003 with a five-year citation window, we estimate that differences in citation practices between the 22 fields account for 14% of overall citation inequality. Our empirical strategy is based on the strong similarities found in the behavior of citation distributions. We obtain three main results. Firstly, we estimate a set of average-based indicators, called exchange rates, to express the citations received by any article in a large interval in terms of the citations received in a reference situation. Secondly, using our exchange rates as normalization factors of the raw citation data reduces the effect of differences in citation practices to, approximately, 2% of overall citation inequality in the normalized citation distributions. Thirdly, we provide an empirical explanation of why the usual normalization procedure based on the fields’ mean citation rates is found to be equally successful.

Some modifications to the SNIP journal impact indicator

The SNIP (source normalized impact per paper) indicator is an indicator of the citation impact of scientific journals. The indicator, introduced by Henk Moed in 2010, is included in Elsevier's Scopus database. The SNIP indicator uses a source normalized approach to correct for differences in citation practices between scientific fields. The strength of this approach is that it does not require a field classification system in which the boundaries of fields are explicitly defined.In this paper, a number of modifications that were recently made to the SNIP indicator are explained, and the advantages of the resulting revised SNIP indicator are pointed out. It is argued that the original SNIP indicator has some counterintuitive properties, and it is shown mathematically that the revised SNIP indicator does not have these properties. Empirically, the differences between the original SNIP indicator and the revised one turn out to be relatively small, although some systematic differences can be observed. Relations with other source normalized indicators proposed in the literature are discussed as well.

Sub-field normalization in the multiplicative case: Average-based citation indicators

This paper investigates the citation impact of three large geographical areas – the U.S., the European Union (EU), and the rest of the world (RW) – at different aggregation levels. The difficulty is that 42% of the 3.6 million articles in our Thomson Scientific dataset are assigned to several sub-fields among a set of 219 Web of Science categories. We follow a multiplicative approach in which every article is wholly counted as many times as it appears at each aggregation level. We compute the crown indicator and the Mean Normalized Citation Score (MNCS) using for the first time sub-field normalization procedures for the multiplicative case. We also compute a third indicator that does not correct for differences in citation practices across sub-fields. It is found that: (1) No geographical area is systematically favored (or penalized) by any of the two normalized indicators. (2) According to the MNCS, only in six out of 80 disciplines – but in none of 20 fields – is the EU ahead of the U.S. In contrast, the normalized U.S./EU gap is greater than 20% in 44 disciplines, 13 fields, and for all sciences as a whole. The dominance of the EU over the RW is even greater. (3) The U.S. appears to devote relatively more – and the RW less – publication effort to sub-fields with a high mean citation rate, which explains why the U.S./EU and EU/RW gaps for all sciences as a whole increase by 4.5 and 5.6 percentage points in the un-normalized case. The results with a fractional approach are very similar indeed.

Sub-field normalization in the multiplicative case: High- and low-impact citation indicators

CEPR Project SCIFI-GLOW*Corresponding author. Email: jrc@eco.uc3m.esThis article uses high- and low-impact citation indicators for the evaluation of the citation per-formance of research units at different aggregate levels using a dataset of about 3.6 millionarticles published in 1998–2002 in the natural and the social sciences with a 5-year citationwindow. The difficulty is that a large proportion of individual articles are assigned to multiplesubfields. To control for wide differences in citation practices at the subfield level, we apply anovel normalization procedure in the multiplicative approach in which each paper is whollycounted as many times as necessary in the several categories to which it is assigned at eachaggregation level. The methodology is applied to a partition of the world into three geographicalareas: the USA, the European Union (EU), and the Rest of the World. The main findings are thefollowing two. (1) Although normalization does not systematically bias the results against anyarea, it reduces the US/EU high-impact gap in the all-sciences case by a non-negligible 14.4%.(2) The dominance of the USA over the EU in the basic and applied research published in theperiodical literature is almost universal at all aggregation levels. From the high-impact perspective,for example, the USA is ahead of the EU in 77 out of 80 disciplines, and all of 20 fields. For allsciences as a whole, the US high-impact indicator is 61% greater than that of the EU.Keywords: citation analysis; high- and low-impact indicators; subfield normalization; multiplica-tive approach; US/EU scientific gap.

Alone or together: examples from history research

Individualistic nature of research in the humanities is a common fact, as well as the notion that boundaries in humanities are poorly defined. Using citation analysis we have to take into account differences in citation practices not only between humanities and sciences but also within narrower fields of humanities. In the current study we observe differences between publication behaviour of historians and archaeologists, examine some aspects of citation practices in those fields, and show their effect on visibility.

Academic attribution: citation and the construction of disciplinary knowledge

In this paper I explore the ways in which academic citation practices contribute to the construction of disciplinary knowledge. Based on the analysis of a computer corpus of 80 research articles and interviews with experienced writers, the study investigates the contextual variability of citations in eight disciplines and suggests how textual conventions point to distinctions in the ways knowledge is typically negotiated and confirmed within different academic communities. Clear disciplinary differences are identified in both the extent to which writers refer to the work of others and in how they depict the reported information. Writers in the humanities and social sciences employed substantially more citations than scientists and engineers, and were more likely to use integral structures, to employ discourse reporting verbs, and to represent cited authors as adopting a stance to their material. It is argued that these differences in citation practices are related to the fact that the academics actively participate in knowledge construction as members of professional groups and that their discoursal decisions are influenced by, and deeply embedded in, the epistemological and social conventions of their disciplines.

What is a Citation Worth?

A robust finding in all studies is that citations are a positive and significant determinant of earnings over almost all of the observed range of citation levels. The marginal value of a citation (when the level of citations is zero) varies between $50 and $1,300. Some differences in marginal values may be due to differences in citation practices among disciplines while others may be due to differences among the studies in the control variables included in the salary regressions. Finally, no gain in explanatory power results from the inclusion in the salary regression of the costly nonfirst-author citation measure.