Evidence-based editing: factors influencing the number of citations in a national journal

Purpose: Citations received by papers published within a journal serve to increase its bibliometric impact. The objective of this paper was to assess the influence of publication language, article type, number of authors, and year of publication on the citations received by papers published in Gaceta Sanitaria, a Spanish-language journal of public health. Methods: The information sources were the journal website and the Web of Knowledge, of the Institute of Scientific Information. The period analyzed was from 2007 to 2010. We included original articles, brief original articles, and reviews published within that period. We extracted manually information regarding the variables analyzed and we also differentiated among total citations and self-citations. We constructed logistic regression models to analyze the probability of a Gaceta Sanitaria paper to be cited or not, taking into account the aforementioned independent variables. We also analyzed the probability of receiving citations from non-Spanish authors. Results: Two hundred forty papers fulfilled the inclusion criteria. The included papers received a total of 287 citations, which became 202 when excluding self-citations. The only variable influencing the probability of being cited was the publication year. After excluding never cited papers, time since publication and review papers had the highest probabilities of being cited. Papers in English and review articles had a higher probability of citation from non-Spanish authors. Conclusions: Publication language has no influence on the citations received by a national, non-English journal. Reviews in English have the highest probability of citation from abroad. Editors should decide how to manage this information when deciding policies to raise the bibliometric impact factor of their journals.

False anglicisms in the Spanish language of fashion and beauty

Many works have already dealt with anglicisms in Spanish, especially in science and information technologies. However, despite the high and growing number of English terms incorporated daily by the language of fashion, it has received comparative less attention in lexicographic and terminological studies than that of other areas, such as science or business. For several reasons, which include prestige or peer pressure, Spanish has not only adopted English words with new meanings and usage, but also contains other forms based on English patterns which users seem to consider more accurate or expressive. This paper concentrates on false anglicisms as indicators of some of the special relationships and influences between languages arising from the pervasive presence of English. We shall look at the Spanish language of fashion, which, in addition to genuine anglicisms, has for some time been using English words with different meanings, or even created items of its own (or imported them from other languages) with the appearance of English words. These false anglicisms, which have proven extremely popular in receiving languages (not only in Spanish) have frequently been disseminated by youth magazines and the new digital media, both in general spheres and in fashion-specific contexts.

PoS-tagging the Web in Portuguese. National varieties, text typologies and spelling systems

The great amount of text produced every day in the Web turned it as one of the main sources for obtaining linguistic corpora, that are further analyzed with Natural Language Processing techniques. On a global scale, languages such as Portuguese - official in 9 countries - appear on the Web in several varieties, with lexical, morphological and syntactic (among others) differences. Besides, a unified spelling system for Portuguese has been recently approved, and its implementation process has already started in some countries. However, it will last several years, so different varieties and spelling systems coexist. Since PoS-taggers for Portuguese are specifically built for a particular variety, this work analyzes different training corpora and lexica combinations aimed at building a model with high-precision annotation in several varieties and spelling systems of this language. Moreover, this paper presents different dictionaries of the new orthography (Spelling Agreement) as well as a new freely available testing corpus, containing different varieties and textual typologies.