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Aslib Journal of Information Management, vol. 67 no. 3
Type: Research Article
ISSN: 2050-3806

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Article
Publication date: 13 July 2015

Cassidy R. Sugimoto and Scott Weingart

– The purpose of this paper is to identify criteria for and definitions of disciplinarity, and how they differ between different types of literature.

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1058

Abstract

Purpose

The purpose of this paper is to identify criteria for and definitions of disciplinarity, and how they differ between different types of literature.

Design/methodology/approach

This synthesis is achieved through a purposive review of three types of literature: explicit conceptualizations of disciplinarity; narrative histories of disciplines; and operationalizations of disciplinarity.

Findings

Each angle of discussing disciplinarity presents distinct criteria. However, there are a few common axes upon which conceptualizations, disciplinary narratives, and measurements revolve: communication, social features, topical coherence, and institutions.

Originality/value

There is considerable ambiguity in the concept of a discipline. This is of particular concern in a heightened assessment culture, where decisions about funding and resource allocation are often discipline-dependent (or focussed exclusively on interdisciplinary endeavors). This work explores the varied nature of disciplinarity and, through synthesis of the literature, presents a framework of criteria that can be used to guide science policy makers, scientometricians, administrators, and others interested in defining, constructing, and evaluating disciplines.

Details

Journal of Documentation, vol. 71 no. 4
Type: Research Article
ISSN: 0022-0418

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Article
Publication date: 18 May 2015

Timothy D Bowman

The purpose of this paper is to show that there were differences in the use of Twitter by professors at AAU schools. Affordance use differed between the personal and…

Abstract

Purpose

The purpose of this paper is to show that there were differences in the use of Twitter by professors at AAU schools. Affordance use differed between the personal and professional tweets of professors as categorized by turkers. Framing behaviors were described that could impact the interpretation of tweets by audience members.

Design/methodology/approach

A three phase research design was used that included surveys of professors, categorization of tweets by workers in Amazon’s Mechanical Turk, and categorization of tweets by active professors on Twitter.

Findings

There were significant differences found between professors that reported having a Twitter account, significant differences found between types of Twitter accounts (personal, professional, or both), and significant differences in the affordances used in personal and professional tweets. Framing behaviors were described that may assist altmetric researchers in distinguishing between personal and professional tweets.

Research limitations/implications

The study is limited by the sample population, survey instrument, low survey response rate, and low Cohen’s κ.

Practical implications

An overview of various affordances found in Twitter is provided and a novel use of Amazon’s Mechanical Turk for the categorization of tweets is described that can be applied to future altmetric studies.

Originality/value

This work utilizes a socio-technical framework integrating social and psychological theories to interpret results from the tweeting behavior of professors and the interpretation of tweets by workers in Amazon’s Mechanical Turk.

Details

Aslib Journal of Information Management, vol. 67 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

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Book part
Publication date: 19 August 2019

Elaine M. Lasda

Abstract

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The New Metrics: Practical Assessment of Research Impact
Type: Book
ISBN: 978-1-78973-269-6

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Article
Publication date: 18 May 2015

Rodrigo Costas, Zohreh Zahedi and Paul Wouters

The purpose of this paper is to analyze the disciplinary orientation of scientific publications that were mentioned on different social media platforms, focussing on their…

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1882

Abstract

Purpose

The purpose of this paper is to analyze the disciplinary orientation of scientific publications that were mentioned on different social media platforms, focussing on their differences and similarities with citation counts.

Design/methodology/approach

Social media metrics and readership counts, associated with 500,216 publications and their citation data from the Web of Science database, were collected from Altmetric.com and Mendeley. Results are presented through descriptive statistical analyses together with science maps generated with VOSviewer.

Findings

The results confirm Mendeley as the most prevalent social media source with similar characteristics to citations in their distribution across fields and their density in average values per publication. The humanities, natural sciences, and engineering disciplines have a much lower presence of social media metrics. Twitter has a stronger focus on general medicine and social sciences. Other sources (blog, Facebook, Google+, and news media mentions) are more prominent in regards to multidisciplinary journals.

Originality/value

This paper reinforces the relevance of Mendeley as a social media source for analytical purposes from a disciplinary perspective, being particularly relevant for the social sciences (together with Twitter). Key implications for the use of social media metrics on the evaluation of research performance (e.g. the concentration of some social media metrics, such as blogs, news items, etc., around multidisciplinary journals) are identified.

Details

Aslib Journal of Information Management, vol. 67 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

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Article
Publication date: 18 May 2015

Lutz Bornmann

– The purpose of this case study is to investigate the usefulness of altmetrics for measuring the broader impact of research.

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1162

Abstract

Purpose

The purpose of this case study is to investigate the usefulness of altmetrics for measuring the broader impact of research.

Design/methodology/approach

This case study is based on a sample of 1,082 the Public Library of Science (PLOS) journal articles recommended in F1000. The data set includes altmetrics which were provided by PLOS. The F1000 data set contains tags on papers which were assigned by experts to characterise them.

Findings

The most relevant tag for altmetric research is “good for teaching”, as it is assigned to papers which could be of interest to a wider circle of readers than the peers in a specialised area. One could expect papers with this tag to be mentioned more often on Facebook and Twitter than those without this tag. The results from regression models were able to confirm these expectations: papers with this tag show significantly higher Facebook and Twitter counts than papers without this tag. This clear association could not be seen with Mendeley or Figshare counts (that is with counts from platforms which are chiefly of interest in a scientific context).

Originality/value

The results of the current study indicate that Facebook and Twitter, but not Figshare or Mendeley, might provide an indication of which papers are of interest to a broader circle of readers (and not only for the peers in a specialist area), and could therefore be useful for the measurement of the societal impact of research.

Details

Aslib Journal of Information Management, vol. 67 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

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Article
Publication date: 18 May 2015

Juan Pablo Alperin

The purpose of this study is to contribute to the understanding of how the potential of altmetrics varies around the world by measuring the percentage of articles with…

Abstract

Purpose

The purpose of this study is to contribute to the understanding of how the potential of altmetrics varies around the world by measuring the percentage of articles with non-zero metrics (coverage) for articles published from a developing region (Latin America).

Design/methodology/approach

This study uses article metadata from a prominent Latin American journal portal, SciELO, and combines it with altmetrics data from Altmetric.com and with data collected by author-written scripts. The study is primarily descriptive, focusing on coverage levels disaggregated by year, country, subject area, and language.

Findings

Coverage levels for most of the social media sources studied was zero or negligible. Only three metrics had coverage levels above 2 per cent – Mendeley, Twitter, and Facebook. Of these, Twitter showed the most significant differences with previous studies. Mendeley coverage levels reach those found by previous studies, but it takes up to two years longer for articles to be saved in the reference manager. For the most recent year, coverage was less than half than what was found in previous studies. The coverage levels of Facebook appear similar (around 3 per cent) to that of previous studies.

Research limitations/implications

The Altmetric.com data used for some of the analyses were collected for a six month period. For other analyses, Altmetric.com data were only available for a single country (Brazil).

Originality/value

The results of this study have implications for the altmetrics research community and for any stakeholders interested in using altmetrics for evaluation. It suggests the need of careful sample selection when wishing to make generalizable claims about altmetrics.

Details

Aslib Journal of Information Management, vol. 67 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

To view the access options for this content please click here

Abstract

Details

Journal of Documentation, vol. 71 no. 2
Type: Research Article
ISSN: 0022-0418

Keywords

To view the access options for this content please click here
Article
Publication date: 18 May 2015

Victoria Uren and Aba-Sah Dadzie

The purpose of this paper is to assess high-dimensional visualisation, combined with pattern matching, as an approach to observing dynamic changes in the ways people tweet…

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1518

Abstract

Purpose

The purpose of this paper is to assess high-dimensional visualisation, combined with pattern matching, as an approach to observing dynamic changes in the ways people tweet about science topics.

Design/methodology/approach

The high-dimensional visualisation approach was applied to three science topics to test its effectiveness for longitudinal analysis of message framing on Twitter over two disjoint periods in time. The paper uses coding frames to drive categorisation and visual analytics of tweets discussing the science topics.

Findings

The findings point to the potential of this mixed methods approach, as it allows sufficiently high sensitivity to recognise and support the analysis of non-trending as well as trending topics on Twitter.

Research limitations/implications

Three topics are studied, these illustrate a range of frames, but results may not be representative of all science topics.

Social implications

Funding bodies increasingly encourage scientists to participate in public engagement. As social media provides an avenue actively utilised for public communication, understanding the nature of the dialog on this medium is important for the scientific community and the public at large.

Originality/value

This study differs from standard approaches to the analysis of micropost data, which tend to focus on large-scale data sets. It provides evidence that this approach enables practical and effective analysis of the content of midsize to large collections of microposts.

Details

Aslib Journal of Information Management, vol. 67 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

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Article
Publication date: 18 May 2015

Alesia A Zuccala, Frederik T. Verleysen, Roberto Cornacchia and Tim C.E. Engels

– The purpose of this paper is to assess the value of Goodreads reader ratings for measuring the wider impact of scholarly books published in the field of History.

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1981

Abstract

Purpose

The purpose of this paper is to assess the value of Goodreads reader ratings for measuring the wider impact of scholarly books published in the field of History.

Design/methodology/approach

Book titles were extracted from the reference lists of articles that appeared in 604 history journals indexed in Scopus (2007-2011). The titles were cleaned and matched with WorldCat.org (for publisher information) as well as Goodreads (for reader ratings) using an API. A set of 8,538 books was first filtered based on Dewey Decimal Classification class 900 “History and Geography”, then a subset of 997 books with the highest citations and reader ratings (i.e. top 25 per cent) was analysed separately based on additional characteristics.

Findings

A weak correlation (0.212) was found between citation counts and reader rating counts for the full data set (n=8,538). An additional correlation for the subset of 997 books indicated a similar weak correlation (0.190). Further correlations between citations, reader ratings, written reviews, and library holdings indicate that a reader rating on Goodreads was more likely to be given to a book held in an international library, including both public and academic libraries.

Originality/value

Research on altmetrics has focused almost exclusively on scientific journal articles appearing on social media services (e.g. Twitter, Facebook). In this paper we show the potential of Goodreads reader ratings to identify the impact of books beyond academia. As a unique altmetric data source, Goodreads can allow scholarly authors from the social sciences and humanities to measure the wider impact of their books.

Details

Aslib Journal of Information Management, vol. 67 no. 3
Type: Research Article
ISSN: 2050-3806

Keywords

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