Search (67 results, page 4 of 4)

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Abstract

Data collected by social media platforms have been introduced as new sources for indicators to help measure the impact of scholarly research in ways that are complementary to traditional citation analysis. Data generated from social media activities can be used to reflect broad types of impact. This article aims to provide systematic evidence about how often Twitter is used to disseminate information about journal articles in the biomedical sciences. The analysis is based on 1.4 million documents covered by both PubMed and Web of Science and published between 2010 and 2012. The number of tweets containing links to these documents was analyzed and compared to citations to evaluate the degree to which certain journals, disciplines, and specialties were represented on Twitter and how far tweets correlate with citation impact. With less than 10% of PubMed articles mentioned on Twitter, its uptake is low in general but differs between journals and specialties. Correlations between tweets and citations are low, implying that impact metrics based on tweets are different from those based on citations. A framework using the coverage of articles and the correlation between Twitter mentions and citations is proposed to facilitate the evaluation of novel social-media-based metrics.

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Abstract

Since its creation in 1991, arXiv has become central to the diffusion of research in a number of fields. Combining data from the entirety of arXiv and the Web of Science (WoS), this article investigates (a) the proportion of papers across all disciplines that are on arXiv and the proportion of arXiv papers that are in the WoS, (b) the elapsed time between arXiv submission and journal publication, and (c) the aging characteristics and scientific impact of arXiv e-prints and their published version. It shows that the proportion of WoS papers found on arXiv varies across the specialties of physics and mathematics, and that only a few specialties make extensive use of the repository. Elapsed time between arXiv submission and journal publication has shortened but remains longer in mathematics than in physics. In physics, mathematics, as well as in astronomy and astrophysics, arXiv versions are cited more promptly and decay faster than WoS papers. The arXiv versions of papers-both published and unpublished-have lower citation rates than published papers, although there is almost no difference in the impact of the arXiv versions of published and unpublished papers.

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Abstract

International collaboration tends to result in more highly cited research and, partly as a result of this, many research funding schemes are specifically international in scope. Nevertheless, it is not clear whether this citation advantage is the result of higher quality research or due to other factors, such as a larger audience for the publications. To test whether the apparent advantage of internationally collaborative research may be due to additional interest in articles from the countries of the authors, this article assesses the extent to which the national affiliations of the authors of articles affect the national affiliations of their Mendeley readers. Based on English-language Web of Science articles in 10 fields from science, medicine, social science, and the humanities, the results of statistical models comparing author and reader affiliations suggest that, in most fields, Mendeley users are disproportionately readers of articles authored from within their own country. In addition, there are several cases in which Mendeley users from certain countries tend to ignore articles from specific other countries, although it is not clear whether this reflects national biases or different national specialisms within a field. In conclusion, research funders should not incentivize international collaboration on the basis that it is, in general, higher quality because its higher impact may be primarily due to its larger audience. Moreover, authors should guard against national biases in their reading to select only the best and most relevant publications to inform their research.

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Abstract

Goodreads is an Amazon-owned book-based social web site for members to share books, read, review books, rate books, and connect with other readers. Goodreads has tens of millions of book reviews, recommendations, and ratings that may help librarians and readers to select relevant books. This article describes a first investigation of the properties of Goodreads users, using a random sample of 50,000 members. The results suggest that about three quarters of members with a public profile are female, and that there is little difference between male and female users in patterns of behavior, except for females registering more books and rating them less positively. Goodreads librarians and super-users engage extensively with most features of the site. The absence of strong correlations between book-based and social usage statistics (e.g., numbers of friends, followers, books, reviews, and ratings) suggests that members choose their own individual balance of social and book activities and rarely ignore one at the expense of the other. Goodreads is therefore neither primarily a book-based website nor primarily a social network site but is a genuine hybrid, social navigation site.

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Abstract

Altmetrics are web-based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from Altmetric.com and Mendeley associate with individual article quality scores. It exploits expert norm-referenced peer review scores from the UK Research Excellence Framework 2021 for 67,030+ journal articles in all fields 2014-2017/2018, split into 34 broadly field-based Units of Assessment (UoAs). Altmetrics correlated more strongly with research quality than previously found, although less strongly than raw and field normalized Scopus citation counts. Surprisingly, field normalizing citation counts can reduce their strength as a quality indicator for articles in a single field. For most UoAs, Mendeley reader counts are the best altmetric (e.g., three Spearman correlations with quality scores above 0.5), tweet counts are also a moderate strength indicator in eight UoAs (Spearman correlations with quality scores above 0.3), ahead of news (eight correlations above 0.3, but generally weaker), blogs (five correlations above 0.3), and Facebook (three correlations above 0.3) citations, at least in the United Kingdom. In general, altmetrics are the strongest indicators of research quality in the health and physical sciences and weakest in the arts and humanities.

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Abstract

This study aims to identify the way researchers collaborate with other researchers in the course of the scientific research life cycle and provide information to the designers of e-Science and e-Research implementations. On the basis of in-depth interviews with and on-site observations of 24 scientists and a follow-up focus group interview in the field of bioscience/nanoscience and technology in Korea, we examined scientific collaboration using the framework of the scientific research life cycle. We attempt to explain the major motiBiochemistry is a highly funded research area that is typified by large research teams and is important for many areas of the life sciences. This article investigates the citation impact and Mendeley readership impact of biochemistry research from 2011 in the Web of Science according to the type of collaboration involved. Negative binomial regression models are used that incorporate, for the first time, the inclusion of specific countries within a team. The results show that, holding other factors constant, larger teams robustly associate with higher impact research, but including additional departments has no effect and adding extra institutions tends to reduce the impact of research. Although international collaboration is apparently not advantageous in general, collaboration with the United States, and perhaps also with some other countries, seems to increase impact. In contrast, collaborations with some other nations seems to decrease impact, although both findings could be due to factors such as differing national proportions of excellent researchers. As a methodological implication, simpler statistical models would find international collaboration to be generally beneficial and so it is important to take into account specific countries when examining collaboration.t only in the beginning phase of the cycle. For communication and information-sharing practices, scientists continue to favor traditional means of communication for security reasons. Barriers to collaboration throughout the phases included different priorities, competitive tensions, and a hierarchical culture among collaborators, whereas credit sharing was a barrier in the research product phase.