Archives des mots-clés : Altmetrics

Research data explored: an extended analysis of citations and altmetrics

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In this study, we explore the citedness of research data, its distribution over time and its relation to the availability of a digital object identifier (DOI) in the Thomson Reuters database Data Citation Index (DCI).

We investigate if cited research data “impacts” the (social) web, reflected by altmetrics scores, and if there is any relationship between the number of citations and the sum of altmetrics scores from various social media platforms.

Three tools are used to collect altmetrics scores, namely PlumX, ImpactStory, and Altmetric.com, and the corresponding results are compared. We found that out of the three altmetrics tools, PlumX has the best coverage. Our experiments revealed that research data remain mostly uncited (about 85 %), although there has been an increase in citing data sets published since 2008.

The percentage of the number of cited research data with a DOI in DCI has decreased in the last years. Only nine repositories are responsible for research data with DOIs and two or more citations. The number of cited research data with altmetrics “foot-prints” is even lower (4–9 %) but shows a higher coverage of research data from the last decade. In our study, we also found no correlation between the number of citations and the total number of altmetrics scores.

Yet, certain data types (i.e. survey, aggregate data, and sequence data) are more often cited and also receive higher altmetrics scores. Additionally, we performed citation and altmetric analyses of all research data published between 2011 and 2013 in four different disciplines covered by the DCI.

In general, these results correspond very well with the ones obtained for research data cited at least twice and also show low numbers in citations and in altmetrics. Finally, we observed that there are disciplinary differences in the availability and extent of altmetrics scores.

URL : http://link.springer.com/article/10.1007/s11192-016-1887-4

Meaningful Metrics: A 21st Century Librarian’s Guide to Bibliometrics, Altmetrics, and Research Impact

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What does it mean to have meaningful metrics in today’s complex higher education landscape? With a foreword by Heather Piwowar and Jason Priem, this highly engaging and activity-laden book serves to introduce readers to the fast-paced world of research metrics from the unique perspective of academic librarians and LIS practitioners.

Starting with the essential histories of bibliometrics and altmetrics, and continuing with in-depth descriptions of the core tools and emerging issues at stake in the future of both fields, Meaningful Metrics is a convenient all-in-one resource that is designed to be used by a range of readers, from those with little to no background on the subject to those looking to become movers and shakers in the current scholarly metrics movement. Authors Borchardt and Roemer, offer tips, tricks, and real-world examples illustrate how librarians can support the successful adoption of research metrics, whether in their institutions or across academia as a whole.

URL : http://www.ala.org/acrl/sites/ala.org.acrl/files/content/publications/booksanddigitalresources/digital/9780838987568_metrics_OA.pdf

Tweets Do Measure Non – Citational Intellectual Impact

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Purpose

The aim of the paper is to identify the motive behind the social media indicators in focus to tweets and attempts to identify what is measured or indicated by tweets, based on these motives.

Design/methodology/approach

Documents with non zero tweets were manually collected from a source of 5 journals – Nature Biotechnology, Nature Nanotechnology, Nature Physics, Nature Chemistry and Nature Communications for the period January 2014 – October 2014 so as to depict the contemporary trend, as tweets tends to have L shaped curve in time-wise distribution.

Findings

Investigations suggest that the motives behind the tweets are research reach, research acceptance and research usage. Further analysis revealed that the motive behind self – tweets are research visibility, which is one of the attributes of social media and therefore self tweets may not be a complex problem as expected seeing that documents are self tweeted not more than once in most cases.

Furthermore, identifying and classifying tweets based on users – Publishers, Frequent tweeters who apparently tweet all documents of an issue and Authors will increase the effectiveness of altmetrics in research evaluation. It was also found that association between subjects can be identified by the analysis of tweets pattern among subjects.

Originality/value

Study proposes an overall hierarchical structure of impact based on the change/advancement instigated. The study confirms that tweets do measure non – academic intellectual impact that is not captured by traditional metrics.

URL : http://www.itlit.net/v2n2art2.pdf

Altmetrics as traces of the computerization of the research process

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I propose a broad, multi-dimensional conception of altmetrics, namely as traces of the computerization of the research process. Computerization should be conceived in its broadest sense, including all recent developments in ICT and software, taking place in society as a whole. I distinguish four aspects of the research process: the collection of research data and development of research methods; scientific information processing; communication and organization; and, last but not least, research assessment.

I will argue that in each aspect, computerization plays a key role, and metrics are being developed to describe this process. I propose to label the total collection of such metrics as Altmetrics. I seek to provide a theoretical foundation of altmetrics, based on notions developed by Michael Nielsen in his monograph Reinventing Discovery: The New Era of Networked Science. Altmetrics can be conceived as tools for the practical realization of the ethos of science and scholarship in a computerized or digital age.

URL : http://arxiv.org/abs/1510.05131

The quandary between communication and certification

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Purpose

The purpose of this paper is to understand individual academics’ perception, attitudes and participation in Open Access Publishing and open scholarship and revisit some principles and designs of openness in academic publishing from the perspective of creative end-users, which helps to increase the sustainability and efficiency of open models.

Design/methodology/approach

 This paper draws on a case study of China and empirical data collected through semi-structured interviews with a wide range of academics and stakeholders.

Findings

 A separation between the communication and certification functions of publishing is identified: open initiatives are valued for efficient and interactive communication while traditional publishing still dominates the legitimacy of research publications, which leads to the quandary of individual academics operating within the transitional landscape of scholarly communication.

Practical implications

Practical recommendations for sustainable and efficient openness are derived from discussions on the difficulties associated open/social certification and the shifting maxims that govern academics from “publish or perish” to “be visible or vanish”.

Originality/value

“Openness” is defined in broad sense integrating Open Access and open scholarship to comprehensively reflect individual academics’ views in the transitional landscape of academic publishing. The research findings suggest that new open approaches are needed to address the evolving tension and conflicts between communication and certification.

URL : http://dx.doi.org/10.1108/OIR-04-2015-0129

Interpreting “altmetrics”: viewing acts on social media through the lens of citation and social theories

Statut

“More than 30 years after Cronin’s seminal paper on “the need for a theory of citing” (Cronin, 1981), the metrics community is once again in need of a new theory, this time one for so-called “altmetrics”. Altmetrics, short for alternative (to citation) metrics — and as such a misnomer — refers to a new group of metrics based (largely) on social media events relating to scholarly communication. As current definitions of altmetrics are shaped and limited by active platforms, technical possibilities, and business models of aggregators such as Altmetric.com, ImpactStory, PLOS, and Plum Analytics, and as such constantly changing, this work refrains from defining an umbrella term for these very heterogeneous new metrics. Instead a framework is presented that describes acts leading to (online) events on which the metrics are based. These activities occur in the context of social media, such as discussing on Twitter or saving to Mendeley, as well as downloading and citing. The framework groups various types of acts into three categories — accessing, appraising, and applying — and provides examples of actions that lead to visibility and traceability online. To improve the understanding of the acts, which result in online events from which metrics are collected, select citation and social theories are used to interpret the phenomena being measured. Citation theories are used because the new metrics based on these events are supposed to replace or complement citations as indicators of impact. Social theories, on the other hand, are discussed because there is an inherent social aspect to the measurements.”

URL : http://arxiv.org/abs/1502.05701

Characterizing Social Media Metrics of Scholarly Papers: The Effect of Document Properties and Collaboration Patterns

Statut

“A number of new metrics based on social media platforms—grouped under the term “altmetrics”—have recently been introduced as potential indicators of research impact. Despite their current popularity, there is a lack of information regarding the determinants of these metrics. Using publication and citation data from 1.3 million papers published in 2012 and covered in Thomson Reuters’ Web of Science as well as social media counts from Altmetric.com, this paper analyses the main patterns of five social media metrics as a function of document characteristics (i.e., discipline, document type, title length, number of pages and references) and collaborative practices and compares them to patterns known for citations. Results show that the presence of papers on social media is low, with 21.5% of papers receiving at least one tweet, 4.7% being shared on Facebook, 1.9% mentioned on blogs, 0.8% found on Google+ and 0.7% discussed in mainstream media. By contrast, 66.8% of papers have received at least one citation. Our findings show that both citations and social media metrics increase with the extent of collaboration and the length of the references list. On the other hand, while editorials and news items are seldom cited, it is these types of document that are the most popular on Twitter. Similarly, while longer papers typically attract more citations, an opposite trend is seen on social media platforms. Finally, contrary to what is observed for citations, it is papers in the Social Sciences and humanities that are the most often found on social media platforms. On the whole, these findings suggest that factors driving social media and citations are different. Therefore, social media metrics cannot actually be seen as alternatives to citations; at most, they may function as complements to other type of indicators.”

URL : Characterizing Social Media Metrics of Scholarly Papers

DOI : 10.1371/journal.pone.0120495