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Daniel Torres-Salinas

Publications and source records attributed to Daniel Torres-Salinas.

At least 37 records · Page 2Linked to original sources
arXiv2018

Disentangling Gold Open Access

This chapter focuses on the analysis of current publication trends in gold Open Access (OA). The purpose of the chapter is to develop a full understanding on country patterns, OA journals characteristics and citation differences between gold OA and non-gold OA publications. For this, we will first review current literature regarding Open Access and its relation with its so-called citation advantage. Starting with a chronological perspective we will describe its development, how different countries are promoting OA publishing, and its effects on the journal publishing industry. We will deepen the analysis by investigating the research output produced by different units of analysis. First, we will focus on the production of countries with a special emphasis on citation and disciplinary differences. A point of interest will be identification of national idiosyncrasies and the relation between OA publication and research of local interest. This will lead to our second unit of analysis, OA journals indexed in Web of Science. Here we will deepen on journals characteristics and publisher types to clearly identify factors which may affect citation differences between OA and traditional journals which may not necessarily be derived from the OA factor. Gold OA publishing is being encouraged in many countries as opposed to Green OA. This chapter aims at fully understanding how it affects researchers' publication patterns and whether it ensures an alleged citation advantage as opposed to non-gold OA publications.

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arXiv2018

Methodological considerations on the use of the normalized impact in the Severo Ochoa and María de Maetzu programmes

In 2011, the programme for Severo Ochoa Centers of Excellence and María de Maeztu Units of Excellence was launched for the first time. Since this programme has become one of the axes of the Spanish scientific policy. 186 million euros have been distributed and 26 centers and 16 units have been accredited. One of the most relevant criteria for submission is the need for guarantor researchers to have a Normalized Impact of 1.5. In this work, we critically analyze the origin of this bibliometric indicator rooted in the 1980s, the different variants that have been proposed and the limitations its use in this programme have. Finally, we offer a series of practical recommendations for a more accurate use of normalized impact indicators for evaluative purposes.

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arXiv2017

Filling the citation gap: Measuring the multidimensional impact of the academic book at institutional level with PlumX

More than five years after their emergence, altmetrics are still seen as a promise to complement traditional citation-based indicators. However, no study has focused on their potential usefulness to capture the impact of scholarly books. While recent literature shows that citation indicators cannot fully capture the impact of books, other studies have suggested alternative indicators such as usage, publishers' prestige or library holdings. In this paper, we calculate 18 indicators which range from altmetrics to library holdings, views, downloads or citations to the production of monographs of a Spanish university using the bibliometric suite PlumX from EBSCO. The objective of the study is to adopt a multidimensional perspective on the analysis of books and understand the level of complementarity between these different indicators. Also, we compare the overview offered by this range of indicators when applied to monographs with the traditional bibliometric perspective focused on journal articles and citation impact. We observe a low presence of altmetric indicators for monographs, even lower than for journal articles and a predominance of library holdings, confirming this indicator as the most promising one towards the analysis of the impact of books.

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arXiv2016

Can we use altmetrics at the institutional level? A case study analysing the coverage by research areas of four Spanish universities

Social media based indicators or altmetrics have been under scrutiny for the last seven years. Their promise as alternative metrics for measuring scholarly impact is still far from becoming a reality. Up to now, most studies have focused on the understanding of the nature and relation of altmetric indicators with citation data. Few papers have analysed research profiles based on altmetric data. Most of these have related to researcher profiles and the expansion of these tools among researchers. This paper aims at exploring the coverage of the Altmetric.com database and its potential use in order to show universities' research profiles in relationship with other databases. We analyse a sample of four different Spanish universities.First, we observe a low coverage of altmetric indicators with only 36 percent of all documents retrieved from the Web of Science having an 'altmetric' score. Second, we observe that for the four universities analysed, the area of Science shows higher 'altmetric' scores that the rest of the research areas. Finally, considering the low coverage of altmetric data at the institutional level, it could be interesting for research policy makers to consider the development of guidelines and best practices guides to ensure that researchers disseminate adequately their research findings through social media.

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arXiv2016

Using network centrality measures to improve national journal classification lists

In countries like Denmark and Spain classified journal lists are now being produced and used in the calculation of nationwide performance indicators. As a result, Danish and Spanish scholars are advised to contribute to journals of high 'authority' (as in the former) or those within a high class (as in the latter). This can create a few problems. The aim of this paper is to analyse the potential use of network centrality measures to identify possible mismatches of journal categories. It analysis the Danish National Authority List and the Spanish CIRC Classification. Based on a sample of Library and Information Science publications, it analyses centrality measures that can assess on the importance of journals to given fields, correcting mismatches in these classifications. We conclude by emphasising the use of these measures to better calibrate journal classifications as we observe a general bias in these lists towards older journals. Centrality measures can allow to identify periphery-to-core journals' transitions.

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arXiv2015

Analyzing data citation practices using the Data Citation Index

We present an analysis of data citation practices based on the Data Citation Index from Thomson Reuters. This database launched in 2012 aims to link data sets and data studies with citations received from the other citation indexes. The DCI harvests citations to research data from papers indexed in the Web of Science. It relies on the information provided by the data repository as data citation practices are inconsistent or inexistent in many cases. The findings of this study show that data citation practices are far from common in most research fields. Some differences have been reported on the way researchers cite data: while in the areas of Science and Engineering and Technology data sets were the most cited, in Social Sciences and Arts and Humanities data studies play a greater role. A total of 88.1 percent of the records have received no citation, but some repositories show very low uncitedness rates. Although data citation practices are rare in most fields, they have expanded in disciplines such as crystallography and genomics. We conclude by emphasizing the role that the DCI could play in encouraging the consistent, standardized citation of research data; a role that would enhance their value as a means of following the research process from data collection to publication.

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arXiv2015

The BiPublishers ranking: Main results and methodological problems when constructing rankings of academic publishers

We present the results of the Bibliometric Indicators for Publishers project (also known as BiPublishers). This project represents the first attempt to systematically develop bibliometric publisher rankings. The data for this project was derived from the Book Citation Index, and the study time period was 2009-2013. We have developed 42 rankings: 4 for by fields and 38 by disciplines. We display six indicators by publisher divided into three types: output, impact and publisher's profile. The aim is to capture different characteristics of the research performance of publishers. 254 publishers were processed and classified according to publisher type: commercial publishers and university presses. We present the main publishers by fields. Then, we discuss the main challenges presented when developing this type of tools. The BiPublishers ranking is an on-going project which aims to develop and explore new data sources and indicators to better capture and define the research impact of publishers.

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arXiv2015

Hyperlinks embedded in Twitter as a proxy for total external inlinks to international university websites

This article analyzes Twitter as a potential alternative source of external links for use in webometric analysis because of its capacity to embed hyperlinks in different tweets. Given the limitations on searching Twitter's public API, we decided to use the Topsy search engine as a source for compiling tweets. To this end, we took a global sample of 200 universities and compiled all the tweets with hyperlinks to any of these institutions. Further link data was obtained from alternative sources (MajesticSEO and OpenSiteExplorer) in order to compare the results. Thereafter, various statistical tests were performed to determine the correlation between the indicators and the ability to predict external links from the collected tweets. The results indicate a high volume of tweets, although they are skewed by the presence and performance of specific universities and countries. The data provided by Topsy correlated significantly with all link indicators, particularly with OpenSiteExplorer (r=0.769). Finally, prediction models do not provide optimum results because of high error rates, which fall slightly in nonlinear models applied to specific environments. We conclude that the use of Twitter (via Topsy) as a source of hyperlinks to universities produces promising results due to its high correlation with link indicators, though limited by policies and culture regarding use and presence in social networks.

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arXiv2014

Bibliometric Indicators for Publishers: Data processing, indicators and interpretation

Here we describe the Bibliometric Indicators for Publishers Project, an initiative undertaken by EC3Metrics SL for the analysis and development of indicators based on books and book chapters. Its goal is to study and analyze the publication and citation patterns of books and book chapters considering academic publishers as the unit of analysis. It aims at developing new methodologies and indicators that can better capture and define the research impact of publishers. It is an on-going project in which data sources and indicators are tested. We consider academic publishers as an analogy of journals, focusing on them as the unit of analysis. In this working paper we present the http://bipublishers.es website where all findings derived from the project are displayed. We describe the data retrieval and normalization process and we show the main results. A total 482,470 records have been retrieved and processed, identifying 342 publishers from which 254 have been analyzed. Then six indicators have been calculated for each publisher for four fields and 38 disciplines and displayed.

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arXiv2014

New data, new possibilities: Exploring the insides of Altmetric.com

This paper analyzes Altmetric.com, one of the most important altmetric data providers currently used. We have analyzed a set of publications with DOI number indexed in the Web of Science during the period 2011-2013 and collected their data with the Altmetric API. 19% of the original set of papers was retrieved from Altmetric.com including some altmetric data. We identified 16 different social media sources from which Altmetric.com retrieves data. However five of them cover 95.5% of the total set. Twitter (87.1%) and Mendeley (64.8%) have the highest coverage. We conclude that Altmetric.com is a transparent, rich and accurate tool for altmetric data. Nevertheless, there are still potential limitations on its exhaustiveness as well as on the selection of social media sources that need further research.

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arXiv2014

An insight into the importance of national university rankings in an international context: The case of the I-UGR Rankings of Spanish universities

The great importance international rankings have achieved in the research policy arena warns against many threats consequence of the flaws and shortcomings these tools present. One of them has to do with the inability to accurately represent national university systems as their original purpose is only to rank world-class universities. Another one has to do with the lack of representativeness of universities' disciplinary profiles as they usually provide a unique table. Although some rankings offer a great coverage and others offer league tables by fields, no international ranking does both. In order to surpass such limitation from a research policy viewpoint, this paper analyzes the possibility of using national rankings in order to complement international rankings. For this, we analyze the Spanish university system as a study case presenting the I-UGR Rankings for Spanish universities by fields and subfields. Then, we compare their results with those obtained by the Shanghai Ranking, the QS Ranking, the Leiden Ranking and the NTU Ranking, as they all have basic common grounds which allow such comparison. We conclude that it is advisable to use national rankings in order to complement international rankings, however we observe that this must be done with certain caution as they differ on the methodology employed as well as on the construction of the fields.

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arXiv2014

An introduction to the coverage of the Data Citation Index (Thomson-Reuters): disciplines, document types and repositories

In the past years, the movement of data sharing has been enjoying great popularity. Within this context, Thomson Reuters launched at the end of 2012 a new product inside the Web of Knowledge family: the Data Citation Index. The aim of this tool is to enable discovery and access, from a single place, to data from a variety of data repositories from different subject areas and from around the world. In this short note we present some preliminary results from the analysis of the Data Citation Index. Specifically, we address the following issues: discipline coverage, data types present in the database, and repositories that were included at the time of the study

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arXiv2014

Analyzing the citation characteristics of books: edited books, book series and types of publishers in the Book Citation Index

This paper presents a first approach to analyzing the factors that determine the citation characteristics of books. For this we use the Thomson Reuters' Book Citation Index, a novel multidisciplinary database launched in 2010 which offers bibliometric data of books. We analyze three possible factors which are considered to affect the citation impact of books: the presence of editors, the inclusion in series and the type of publisher. Also, we focus on highly cited books to see if these factors may affect them as well. We considered as highly cited books, those in the top 5% of the most highly cited ones of the database. We define these three aspects and we present the results for four major scientific areas in order to identify field-based differences (Science, Engineering & Technology, Social Sciences and Arts & Humanities). Finally we conclude observing that differences were noted for edited books and types of publishers. Although books included in series showed higher impact in two areas.

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arXiv2013

Coverage, field specialization and impact of scientific publishers indexed in the 'Book Citation Index'

Purpose: The aim of this study is to analyze the disciplinary coverage of the Thomson Reuters' Book Citation Index database focusing on publisher presence, impact and specialization. Design/Methodology/approach: We conduct a descriptive study in which we examine coverage by discipline, publisher distribution by field and country of publication, and publisher impact. For this the Thomson Reuters' Subject Categories were aggregated into 15 disciplines. Findings: 30% of the total share of this database belongs to the fields of Humanities and Social Sciences. Most of the disciplines are covered by very few publishers mainly from the UK and USA (75.05% of the books), in fact 33 publishers concentrate 90% of the whole share. Regarding publisher impact, 80.5% of the books and chapters remained uncited. Two serious errors were found in this database. Firstly, the Book Citation Index does not retrieve all citations for books and chapters. Secondly, book citations do not include citations to their chapters. Research limitations/implications: The Book Citation Index is still underdeveloped and has serious limitations which call into caution when using it for bibliometric purposes. Practical implications: The results obtained from this study warn against the use of this database for bibliometric purposes, but opens a new window of opportunities for covering long neglected areas such as Humanities and Social Sciences. The target audience of this study is librarians, bibliometricians, researchers, scientific publishers, prospective authors and evaluation agencies. Originality/Value: There are currently no studies analyzing in depth the coverage of this novel database which covers monographs.

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arXiv2013

Letter to the editor: Against the Resilience of Rejected Manuscripts

In this letter we propose the development of guidelines by the main editors associations as well as protocols within online journal management systems for keeping track of rejected manuscripts that are resubmitted as well as for the interchange of referees reports between journals.

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arXiv2013

The Google Scholar Experiment: how to index false papers and manipulate bibliometric indicators

Google Scholar has been well received by the research community. Its promises of free, universal and easy access to scientific literature as well as the perception that it covers better than other traditional multidisciplinary databases the areas of the Social Sciences and the Humanities have contributed to the quick expansion of Google Scholar Citations and Google Scholar Metrics: two new bibliometric products that offer citation data at the individual level and at journal level. In this paper we show the results of a experiment undertaken to analyze Google Scholar's capacity to detect citation counting manipulation. For this, six documents were uploaded to an institutional web domain authored by a false researcher and referencing all the publications of the members of the EC3 research group at the University of Granada. The detection of Google Scholar of these papers outburst the citations included in the Google Scholar Citations profiles of the authors. We discuss the effects of such outburst and how it could affect the future development of such products not only at individual level but also at journal level, especially if Google Scholar persists with its lack of transparency.

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