Altmetrics

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The original logotype from the Altmetrics Manifesto. Altmetrics.svg
The original logotype from the Altmetrics Manifesto.

In scholarly and scientific publishing, altmetrics are non-traditional bibliometrics [2] proposed as an alternative [3] or complement [4] to more traditional citation impact metrics, such as impact factor and h-index. [5] The term altmetrics was proposed in 2010, [1] as a generalization of article level metrics, [6] and has its roots in the #altmetrics hashtag. Although altmetrics are often thought of as metrics about articles, they can be applied to people, journals, books, data sets, presentations, videos, source code repositories, web pages, etc.

Contents

Altmetrics use public APIs across platforms to gather data with open scripts and algorithms. Altmetrics did not originally cover citation counts, [7] but calculate scholar impact based on diverse online research output, such as social media, online news media, online reference managers and so on. [8] [9] It demonstrates both the impact and the detailed composition of the impact. [1] Altmetrics could be applied to research filter, [1] promotion and tenure dossiers, grant applications [10] [11] and for ranking newly-published articles in academic search engines. [12]

Adoption

The development of web 2.0 has changed the research publication seeking and sharing within or outside the academy, but also provides new innovative constructs to measure the broad scientific impact of scholar work. Although the traditional metrics are useful, they might be insufficient to measure immediate and uncited impacts, especially outside the peer-review realm. [1]

Projects such as ImpactStory, [13] [14] and various companies, including Altmetric, [13] [15] Plum Analytics [13] [16] [17] [18] and Overton [19] are calculating altmetrics. Several publishers have started providing such information to readers, including BioMed Central, Public Library of Science (PLOS), [20] [21] Frontiers, [22] Nature Publishing Group, [23] and Elsevier. [24] [25] The NIHR Journals Library also includes altmetric data alongside its publications. [26]

In 2008, the Journal of Medical Internet Research started to systematically collect tweets about its articles. [27] Starting in March 2009, the Public Library of Science also introduced article-level metrics for all articles. [20] [21] [28] Funders have started showing interest in alternative metrics, [29] including the UK Medical Research Council. [30] Altmetrics have been used in applications for promotion review by researchers. [31] Furthermore, several universities, including the University of Pittsburgh are experimenting with altmetrics at an institute level. [31]

However, it is also observed that an article needs little attention to jump to the upper quartile of ranked papers, [32] suggesting that not enough sources of altmetrics are currently available to give a balanced picture of impact for the majority of papers.

Important in determining the relative impact of a paper, a service that calculates altmetrics statistics needs a considerably sized knowledge base. The following table shows the number of artefacts, including papers, covered by services (as of 2016):

WebsiteNumber of artefacts
Plum Analytics~ 52.6 Million [33]
Altmetric.com~ 35 Million [34]
ImpactStory~ 1 Million [35]
Overton~ 6 Million [36]

Categories

Altmetrics are a very broad group of metrics, capturing various parts of impact a paper or work can have. A classification of altmetrics was proposed by ImpactStory in September 2012, [37] and a very similar classification is used by the Public Library of Science: [38]

Viewed

One of the first alternative metrics to be used was the number of views of a paper. Traditionally, an author would wish to publish in a journal with a high subscription rate, so many people would have access to the research. With the introduction of web technologies it became possible to actually count how often a single paper was looked at. Typically, publishers count the number of HTML views and PDF views. As early as 2004, the BMJ published the number of views for its articles, which was found to be somewhat correlated to citations. [40]

Discussed

The discussion of a paper can be seen as a metric that captures the potential impact of a paper. Typical sources of data to calculate this metric include Facebook, Google+, Twitter, Science Blogs, and Wikipedia pages. Some researchers regard the mentions on social media as citations. For example, citations on a social media platform could be divided into two categories: internal and external. For instance, the former includes retweets, the latter refers to tweets containing links to outside documents. [41] The correlation between the mentions and likes and citation by primary scientific literature has been studied, and a slight correlation at best was found, e.g. for articles in PubMed. [4]

In 2008 the Journal of Medical Internet Research began publishing views and tweets. These "tweetations" proved to be a good indicator of highly cited articles, leading the author to propose a "Twimpact factor", which is the number of Tweets it receives in the first seven days of publication, as well as a Twindex, which is the rank percentile of an article's Twimpact factor. [27] However, if implementing use of the Twimpact factor, research shows scores to be highly subject specific, and as a result, comparisons of Twimpact factors should be made between papers of the same subject area. [27] While past research in the literature has demonstrated a correlation between tweetations and citations, it is not a causative relationship. At this point in time, it is unclear whether higher citations occur as a result of greater media attention via Twitter and other platforms, or is simply reflective of the quality of the article itself. [27]

Recent research conducted at the individual level, rather than the article level, supports the use of Twitter and social media platforms as a mechanism for increasing impact value. [42] Results indicate that researchers whose work is mentioned on Twitter have significantly higher h-indices than those of researchers whose work was not mentioned on Twitter. The study highlights the role of using discussion based platforms, such as Twitter, in order to increase the value of traditional impact metrics.

Besides Twitter and other streams, blogging has shown to be a powerful platform to discuss literature. Various platforms exist that keep track of which papers are being blogged about. Altmetric.com uses this information for calculating metrics, while other tools just report where discussion is happening, such as ResearchBlogging and Chemical blogspace.

Platforms may even provide a formal way of ranking papers or recommending papers otherwise, such as Faculty of 1000. [43]

Saved

It is also informative to quantify the number of times a page has been saved, or bookmarked. It is thought that individuals typically choose to bookmark pages that have a high relevance to their own work, and as a result, bookmarks may be an additional indicator of impact for a specific study. Providers of such information include science specific social bookmarking services such as CiteULike and Mendeley.

Cited

The cited category is a narrowed definition, different from the discussion. Besides the traditional metrics based on citations in scientific literature, such as those obtained from Google Scholar, CrossRef, PubMed Central, and Scopus, altmetrics also adopt citations in secondary knowledge sources. For example, ImpactStory counts the number of times a paper has been referenced by Wikipedia. [44] Plum Analytics also provides metrics for various academic publications, [45] seeking to track research productivity. PLOS is also a tool that may be used to utilize information on engagement. [45]

Numerous studies have shown that scientific articles disseminated through social media channels (i.e. Twitter, Reddit, Facebook, YouTube, etc) have substantially higher biblometric scores (downlodas, reads and citations) than articles not advertised through social media. In the fields of plastic surgery, [46] hand surgery [47] and more, higher Altmetric scores are associated with better short-term bibliometrics.

Interpretation

While there is less consensus on the validity and consistency of altmetrics, [48] the interpretation of altmetrics in particular is discussed. Proponents of altmetrics make clear that many of the metrics show attention or engagement, rather than the quality of impacts on the progress of science. [38] Even citation-based metrics do not indicate if a high score implies a positive impact on science; that is, papers are also cited in papers that disagree with the cited paper, an issue for example addressed by the Citation Typing Ontology project. [49]

Altmetrics could be more appropriately interpreted by providing detailed context and qualitative data. For example, in order to evaluate the scientific contribution of a scholar work to policy making by altmetrics, qualitative data, such as who's citing online [12] and to what extent the online citation is relevant to the policymaking, should be provided as evidence. [50]

Regarding the relatively low correlation between traditional metrics and altmetrics, altmetrics might measure complementary perspectives of the scholar impact. It is reasonable to combine and compare the two types of metrics in interpreting the societal and scientific impacts. Researchers built a 2*2 framework based on the interactions between altmetrics and traditional citations. [4] Further explanations should be provided for the two groups with high altmetrics/low citations and low altmetrics/high citations. [27] [4] Thus, altmetrics provide convenient approaches for researchers and institutions to monitor the impact of their work and avoid inappropriate interpretations.

Controversy

The usefulness of metrics for estimating scientific impact is controversial. [51] [52] [53] [54] Research has found that online buzz could amplify the effect of other forms of outreach on researchers' scientific impact. For the nano-scientists that are mentioned on Twitter, their interactions with reporters and non-scientists positively and significantly predicted higher h-index, whereas the non-mentioned group failed. [42] Altmetrics expands the measurement of scholar impact for containing a rapid uptake, a broader range of audiences and diverse research outputs. In addition, the community shows a clear need: funders demand measurables on the impact of their spending, such as public engagement.

However, there are limitations that affect the usefulness due to technique problems and systematic bias of construct, such as data quality, heterogeneity and particular dependencies. [52] In terms of technique problems, the data might be incomplete, because it is difficult to collect those online research outputs without direct links to their mentions (i.e. videos) and identify different versions of one research work. Additionally, whether the API leads to any missing data is unsolved. [4]

As for systematic bias, like other metrics, altmetrics are prone to self-citation, gaming, and other mechanisms to boost one's apparent impact such as performing citation spam in Wikipedia. Altmetrics can be gamed: for example, likes and mentions can be bought. [55] Altmetrics can be more difficult to standardize than citations. One example is the number of tweets linking to a paper where the number can vary widely depending on how the tweets are collected. [56] Besides, online popularity may not equal to scientific values. Some popular online citations might be far from the value of generating further research discoveries, while some theoretical-driven or minority-targeted research of great science-related importance might be marginalized online. [27] For example, the top tweeted articles in biomedicine in 2011 were relevant to curious or funny content, potential health applications, and catastrophe. [4] Altmetric state that they have systems in place to detect, identify and correct gaming. [57] Finally, recent research has shown Altmetrics reproduce gendered biases found in disciplinary publication and citation practices: for example, journal articles authored exclusively by female scholars score 27% lower on average than exclusively male-authored outputs. At once, this same research shows 0 attention scores are more likely for male-authored articles. [58]

Altmetrics for more recent articles may be higher because of the increasing uptake of the social web and because articles may be mentioned mainly when they are published. [59] As a result, it might not be fair to compare the altmetrics scores of articles unless they have been published at a similar time. Researchers has developed a sign test to avoid the usage uptake bias by comparing the metrics of an article with the two articles published immediately before and after it. [59]

It should be kept in mind that the metrics are only one of the outcomes of tracking how research is disseminated and used. Altmetrics should be carefully interpreted to overcome the bias. Even more informative than knowing how often a paper is cited, is which papers are citing it. That information allows researchers to see how their work is impacting the field (or not). Providers of metrics also typically provide access to the information from which the metrics were calculated. For example, Web of Science shows which are the citing papers, ImpactStory shows which Wikipedia pages are referencing the paper, and CitedIn shows which databases extracted data from the paper. [60]

Another concern of altmetrics, or any metrics, is how universities or institutions are using metrics to rank their employees make promotion or funding decisions, [61] and the aim should be limited to measure engagement. [62]

The overall online research output is very little and varied among different disciplines. [27] [4] The phenomenon might be consistent with the social media use among scientists. Surveys has shown that nearly half of their respondents held ambivalent attitudes of social media's influence on academic impact and never announced their research work on social media. [63] With the changing shift in open science and social media use, the consistent altmetrics across disciplines and institutions will more likely be adopted.

Ongoing research

The specific use cases and characteristics is an active research field in bibliometrics, providing much needed data to measure the impact of altmetrics itself. Public Library of Science has an Altmetrics Collection [64] and both the Information Standards Quarterly and the Aslib Journal of Information Management recently published special issues on altmetrics. [65] [66] A series of articles that extensively reviews altmetrics was published in late 2015. [67] [68] [69]

There is other research examining the validity of one altmetrics [4] [27] or make comparisons across different platforms. [59] Researchers examine the correlation between altmetrics and traditional citations as the validity test. They assume that the positive and significant correlation reveals the accuracy of altmetrics to measure scientific impact as citations. [59] The low correlation (less than 0.30 [4] ) leads to the conclusion that altmetrics serves a complementary role in scholar impact measurement such as the study by Lamba (2020) [70] who examined 2343 articles having both altmetric attention scores and citations published by 22 core health care policy faculty members at Harvard Medical School and a significant strong positive correlation (r>0.4) was observed between the aggregated ranked altmetric attention scores and ranked citation/increased citation values for all the faculty members in the study. However, it remains unsolved that what altmetrics are most valuable and what degree of correlation between two metrics generates a stronger impact on the measurement. Additionally, the validity test itself faces some technical problems as well. For example, replication of the data collection is impossible because of the instant changing algorithms of data providers. [71]

See also

Related Research Articles

<span class="mw-page-title-main">Citation</span> Reference to a source

A citation is a reference to a source. More precisely, a citation is an abbreviated alphanumeric expression embedded in the body of an intellectual work that denotes an entry in the bibliographic references section of the work for the purpose of acknowledging the relevance of the works of others to the topic of discussion at the spot where the citation appears.

<span class="mw-page-title-main">Scientific citation</span>

Scientific citation is providing detailed reference in a scientific publication, typically a paper or book, to previous published communications which have a bearing on the subject of the new publication. The purpose of citations in original work is to allow readers of the paper to refer to cited work to assist them in judging the new work, source background information vital for future development, and acknowledge the contributions of earlier workers. Citations in, say, a review paper bring together many sources, often recent, in one place.

The impact factor (IF) or journal impact factor (JIF) of an academic journal is a scientometric index calculated by Clarivate that reflects the yearly mean number of citations of articles published in the last two years in a given journal, as indexed by Clarivate's Web of Science.

<span class="mw-page-title-main">Bibliometrics</span> Statistical analysis of written publications

Bibliometrics is the use of statistical methods to analyse books, articles and other publications, especially in scientific contents. Bibliometric methods are frequently used in the field of library and information science. Bibliometrics is closely associated with scientometrics, the analysis of scientific metrics and indicators, to the point that both fields largely overlap.

Scientometrics is the field of study which concerns itself with measuring and analysing scholarly literature. Scientometrics is a sub-field of informetrics. Major research issues include the measurement of the impact of research papers and academic journals, the understanding of scientific citations, and the use of such measurements in policy and management contexts. In practice there is a significant overlap between scientometrics and other scientific fields such as information systems, information science, science of science policy, sociology of science, and metascience. Critics have argued that over-reliance on scientometrics has created a system of perverse incentives, producing a publish or perish environment that leads to low-quality research.

<span class="mw-page-title-main">Google Scholar</span> Academic search service by Google

Google Scholar is a freely accessible web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines. Released in beta in November 2004, the Google Scholar index includes peer-reviewed online academic journals and books, conference papers, theses and dissertations, preprints, abstracts, technical reports, and other scholarly literature, including court opinions and patents.

Citation impact or citation rate is a measure of how many times an academic journal article or book or author is cited by other articles, books or authors. Citation counts are interpreted as measures of the impact or influence of academic work and have given rise to the field of bibliometrics or scientometrics, specializing in the study of patterns of academic impact through citation analysis. The importance of journals can be measured by the average citation rate, the ratio of number of citations to number articles published within a given time period and in a given index, such as the journal impact factor or the citescore. It is used by academic institutions in decisions about academic tenure, promotion and hiring, and hence also used by authors in deciding which journal to publish in. Citation-like measures are also used in other fields that do ranking, such as Google's PageRank algorithm, software metrics, college and university rankings, and business performance indicators.

The h-index is an author-level metric that measures both the productivity and citation impact of the publications, initially used for an individual scientist or scholar. The h-index correlates with success indicators such as winning the Nobel Prize, being accepted for research fellowships and holding positions at top universities. The index is based on the set of the scientist's most cited papers and the number of citations that they have received in other publications. The index has more recently been applied to the productivity and impact of a scholarly journal as well as a group of scientists, such as a department or university or country. The index was suggested in 2005 by Jorge E. Hirsch, a physicist at UC San Diego, as a tool for determining theoretical physicists' relative quality and is sometimes called the Hirsch index or Hirsch number.

<i>PLOS One</i> Peer-reviewed open-access scientific journal

PLOS One is a peer-reviewed open access mega journal published by the Public Library of Science (PLOS) since 2006. The journal covers primary research from any discipline within science and medicine. The Public Library of Science began in 2000 with an online petition initiative by Nobel Prize winner Harold Varmus, formerly director of the National Institutes of Health and at that time director of Memorial Sloan–Kettering Cancer Center; Patrick O. Brown, a biochemist at Stanford University; and Michael Eisen, a computational biologist at the University of California, Berkeley, and the Lawrence Berkeley National Laboratory.

Journal Citation Reports (JCR) is an annual publication by Clarivate. It has been integrated with the Web of Science and is accessed from the Web of Science Core Collection. It provides information about academic journals in the natural and social sciences, including impact factors. The JCR was originally published as a part of the Science Citation Index. Currently, the JCR, as a distinct service, is based on citations compiled from the Science Citation Index Expanded and the Social Sciences Citation Index. As of the 2023 edition, journals from the Arts and Humanities Citation Index and the Emerging Sources Citation Index will also be included.

Journal ranking is widely used in academic circles in the evaluation of an academic journal's impact and quality. Journal rankings are intended to reflect the place of a journal within its field, the relative difficulty of being published in that journal, and the prestige associated with it. They have been introduced as official research evaluation tools in several countries.

The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. As a measure of importance, the Eigenfactor score scales with the total impact of a journal. All else equal, journals generating higher impact to the field have larger Eigenfactor scores.

ResearchGate is a European commercial social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. According to a 2014 study by Nature and a 2016 article in Times Higher Education, it is the largest academic social network in terms of active users, although other services have more registered users, and a 2015–2016 survey suggests that almost as many academics have Google Scholar profiles.

Figshare is an online open access repository where researchers can preserve and share their research outputs, including figures, datasets, images, and videos. It is free to upload content and free to access, in adherence to the principle of open data. Figshare is one of a number of portfolio businesses supported by Digital Science, a subsidiary of Springer Nature.

Article-level metrics are citation metrics which measure the usage and impact of individual scholarly articles.

The Kardashian Index (K-Index), named after media personality Kim Kardashian, is a satirical measure of the discrepancy between a scientist's social media profile and publication record. Proposed by Neil Hall in 2014, the measure compares the number of followers a research scientist has on Twitter to the number of citations they have for their peer-reviewed work.

<span class="mw-page-title-main">Altmetric</span>

Altmetric, or altmetric.com, is a data science company that tracks where published research is mentioned online, and provides tools and services to institutions, publishers, researchers, funders and other organisations to monitor this activity, commonly referred to as altmetrics. Altmetric was recognized by European Commissioner Máire Geoghegan-Quinn in 2014 as a company challenging the traditional reputation systems.

Author-level metrics are citation metrics that measure the bibliometric impact of individual authors, researchers, academics, and scholars. Many metrics have been developed that take into account varying numbers of factors.

Metascience is the use of scientific methodology to study science itself. Metascience seeks to increase the quality of scientific research while reducing inefficiency. It is also known as "research on research" and "the science of science", as it uses research methods to study how research is done and find where improvements can be made. Metascience concerns itself with all fields of research and has been described as "a bird's eye view of science". In the words of John Ioannidis, "Science is the best thing that has happened to human beings ... but we can do it better."

The Leiden Manifesto for research metrics (LM) is a list of "ten principles to guide research evaluation", published as a comment in Volume 520, Issue 7548 of Nature, on 22 April 2015. It was formulated by public policy professor Diana Hicks, scientometrics professor Paul Wouters, and their colleagues at the 19th International Conference on Science and Technology Indicators, held between 3–5 September 2014 in Leiden, The Netherlands.

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