Search (117 results, page 1 of 6)

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Abstract

Citation indictors are increasingly used in some subject areas to support peer review in the evaluation of researchers and departments. Nevertheless, traditional journal-based citation indexes may be inadequate for the citation impact assessment of book-based disciplines. This article examines whether online citations from Google Books and Google Scholar can provide alternative sources of citation evidence. To investigate this, we compared the citation counts to 1,000 books submitted to the 2008 U.K. Research Assessment Exercise (RAE) from Google Books and Google Scholar with Scopus citations across seven book-based disciplines (archaeology; law; politics and international studies; philosophy; sociology; history; and communication, cultural, and media studies). Google Books and Google Scholar citations to books were 1.4 and 3.2 times more common than were Scopus citations, and their medians were more than twice and three times as high as were Scopus median citations, respectively. This large number of citations is evidence that in book-oriented disciplines in the social sciences, arts, and humanities, online book citations may be sufficiently numerous to support peer review for research evaluation, at least in the United Kingdom.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.11, S.2147-2164

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Abstract

We use a new data gathering method, "Web/URL citation," Web/URL and Google Scholar to compare traditional and Web-based citation patterns across multiple disciplines (biology, chemistry, physics, computing, sociology, economics, psychology, and education) based upon a sample of 1,650 articles from 108 open access (OA) journals published in 2001. A Web/URL citation of an online journal article is a Web mention of its title, URL, or both. For each discipline, except psychology, we found significant correlations between Thomson Scientific (formerly Thomson ISI, here: ISI) citations and both Google Scholar and Google Web/URL citations. Google Scholar citations correlated more highly with ISI citations than did Google Web/URL citations, indicating that the Web/URL method measures a broader type of citation phenomenon. Google Scholar citations were more numerous than ISI citations in computer science and the four social science disciplines, suggesting that Google Scholar is more comprehensive for social sciences and perhaps also when conference articles are valued and published online. We also found large disciplinary differences in the percentage overlap between ISI and Google Scholar citation sources. Finally, although we found many significant trends, there were also numerous exceptions, suggesting that replacing traditional citation sources with the Web or Google Scholar for research impact calculations would be problematic.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.7, S.1055-1065

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Abstract

Collaboration is a major research policy objective, but does it deliver higher quality research? This study uses citation analysis to examine the Web of Science (WoS) Information Science & Library Science subject category (IS&LS) to ascertain whether, in general, more highly cited articles are more highly collaborative than other articles. It consists of two investigations. The first investigation is a longitudinal comparison of the degree and proportion of collaboration in five strata of citation; it found that collaboration in the highest four citation strata (all in the most highly cited 22%) increased in unison over time, whereas collaboration in the lowest citation strata (un-cited articles) remained low and stable. Given that over 40% of the articles were un-cited, it seems important to take into account the differences found between un-cited articles and relatively highly cited articles when investigating collaboration in IS&LS. The second investigation compares collaboration for 35 influential information scientists; it found that their more highly cited articles on average were not more highly collaborative than their less highly cited articles. In summary, although collaborative research is conducive to high citation in general, collaboration has apparently not tended to be essential to the success of current and former elite information scientists.

Date

22. 3.2009 12:43:51

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.434-442

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Abstract

The microblogging site Twitter generates a constant stream of communication, some of which concerns events of general interest. An analysis of Twitter may, therefore, give insights into why particular events resonate with the population. This article reports a study of a month of English Twitter posts, assessing whether popular events are typically associated with increases in sentiment strength, as seems intuitively likely. Using the top 30 events, determined by a measure of relative increase in (general) term usage, the results give strong evidence that popular events are normally associated with increases in negative sentiment strength and some evidence that peaks of interest in events have stronger positive sentiment than the time before the peak. It seems that many positive events, such as the Oscars, are capable of generating increased negative sentiment in reaction to them. Nevertheless, the surprisingly small average change in sentiment associated with popular events (typically 1% and only 6% for Tiger Woods' confessions) is consistent with events affording posters opportunities to satisfy pre-existing personal goals more often than eliciting instinctive reactions.

Date

22. 1.2011 14:27:06

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.406-418

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Abstract

This article introduces a new source of evidence of the value of medical-related research: citations from clinical guidelines. These give evidence that research findings have been used to inform the day-to-day practice of medical staff. To identify whether citations from guidelines can give different information from that of traditional citation counts, this article assesses the extent to which references in clinical guidelines tend to be highly cited in the academic literature and highly read in Mendeley. Using evidence from the United Kingdom, references associated with the UK's National Institute of Health and Clinical Excellence (NICE) guidelines tended to be substantially more cited than comparable articles, unless they had been published in the most recent 3 years. Citation counts also seemed to be stronger indicators than Mendeley readership altmetrics. Hence, although presence in guidelines may be particularly useful to highlight the contributions of recently published articles, for older articles citation counts may already be sufficient to recognize their contributions to health in society.

Date

19. 3.2016 12:22:00

Source

Journal of the Association for Information Science and Technology. 67(2016) no.4, S.960-966

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Abstract

Counts of tweets and Mendeley user libraries have been proposed as altmetric alternatives to citation counts for the impact assessment of articles. Although both have been investigated to discover whether they correlate with article citations, it is not known whether users tend to tweet or save (in Mendeley) the same kinds of articles that they cite. In response, this article compares pairs of articles that are tweeted, saved to a Mendeley library, or cited by the same user, but possibly a different user for each source. The study analyzes 1,131,318 articles published in 2012, with minimum tweeted (10), saved to Mendeley (100), and cited (10) thresholds. The results show surprisingly minor overall overlaps between the three phenomena. The importance of journals for Twitter and the presence of many bots at different levels of activity suggest that this site has little value for impact altmetrics. The moderate differences between patterns of saving and citation suggest that Mendeley can be used for some types of impact assessments, but sensitivity is needed for underlying differences.

Date

28. 7.2018 10:00:22

Source

Journal of the Association for Information Science and Technology. 69(2018) no.8, S.959-973

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Abstract

Although the analysis of citations in the scholarly literature is now an established and relatively well understood part of information science, not enough is known about citations that can be found on the Web. In particular, are there new Web types, and if so, are these trivial or potentially useful for studying or evaluating research communication? We sought evidence based upon a sample of 1,577 Web citations of the URLs or titles of research articles in 64 open-access journals from biology, physics, chemistry, and computing. Only 25% represented intellectual impact, from references of Web documents (23%) and other informal scholarly sources (2%). Many of the Web/URL citations were created for general or subject-specific navigation (45%) or for self-publicity (22%). Additional analyses revealed significant disciplinary differences in the types of Google unique Web/URL citations as well as some characteristics of scientific open-access publishing on the Web. We conclude that the Web provides access to a new and different type of citation information, one that may therefore enable us to measure different aspects of research, and the research process in particular; but to obtain good information, the different types should be separated.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1631-1644

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Abstract

Scientists and managers using citation-based indicators to help evaluate research cannot evaluate recent articles because of the time needed for citations to accrue. Reading occurs before citing, however, and so it makes sense to count readers rather than citations for recent publications. To assess this, Mendeley readers and citations were obtained for articles from 2004 to late 2014 in five broad categories (agriculture, business, decision science, pharmacy, and the social sciences) and 50 subcategories. In these areas, citation counts tended to increase with every extra year since publication, and readership counts tended to increase faster initially but then stabilize after about 5 years. The correlation between citations and readers was also higher for longer time periods, stabilizing after about 5 years. Although there were substantial differences between broad fields and smaller differences between subfields, the results confirm the value of Mendeley reader counts as early scientific impact indicators.

Date

16.11.2016 11:07:22

Source

Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3036-3050

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Abstract

Webometric network analyses have been used to map the connectivity of groups of websites to identify clusters, important sites or overall structure. Such analyses have mainly been based upon hyperlink counts, the number of hyperlinks between a pair of websites, although some have used title mentions or URL citations instead. The ability to automatically gather hyperlink counts from Yahoo! ceased in April 2011 and the ability to manually gather such counts was due to cease by early 2012, creating a need for alternatives. This article assesses URL citations and title mentions as possible replacements for hyperlinks in both binary and weighted direct link and co-inlink network diagrams. It also assesses three different types of data for the network connections: hit count estimates, counts of matching URLs, and filtered counts of matching URLs. Results from analyses of U.S. library and information science departments and U.K. universities give evidence that metrics based upon URLs or titles can be appropriate replacements for metrics based upon hyperlinks for both binary and weighted networks, although filtered counts of matching URLs are necessary to give the best results for co-title mention and co-URL citation network diagrams.

Date

6. 4.2012 18:16:22

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.4, S.805-816

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Abstract

Purpose The four major Subject Repositories (SRs), arXiv, Research Papers in Economics (RePEc), Social Science Research Network (SSRN) and PubMed Central (PMC), are all important within their disciplines but no previous study has systematically compared how often they are cited in academic publications. In response, the purpose of this paper is to report an analysis of citations to SRs from Scopus publications, 2000-2013. Design/methodology/approach Scopus searches were used to count the number of documents citing the four SRs in each year. A random sample of 384 documents citing the four SRs was then visited to investigate the nature of the citations. Findings Each SR was most cited within its own subject area but attracted substantial citations from other subject areas, suggesting that they are open to interdisciplinary uses. The proportion of documents citing each SR is continuing to increase rapidly, and the SRs all seem to attract substantial numbers of citations from more than one discipline. Research limitations/implications Scopus does not cover all publications, and most citations to documents found in the four SRs presumably cite the published version, when one exists, rather than the repository version. Practical implications SRs are continuing to grow and do not seem to be threatened by institutional repositories and so research managers should encourage their continued use within their core disciplines, including for research that aims at an audience in other disciplines. Originality/value This is the first simultaneous analysis of Scopus citations to the four most popular SRs.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 67(2015) no.6, S.614-635

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Abstract

Purpose Mendeley reader counts have been proposed as early indicators for the impact of academic publications. The purpose of this paper is to assess whether there are enough Mendeley readers for research evaluation purposes during the month when an article is first published. Design/methodology/approach Average Mendeley reader counts were compared to the average Scopus citation counts for 104,520 articles from ten disciplines during the second half of 2016. Findings Articles attracted, on average, between 0.1 and 0.8 Mendeley readers per article in the month in which they first appeared in Scopus. This is about ten times more than the average Scopus citation count. Research limitations/implications Other disciplines may use Mendeley more or less than the ten investigated here. The results are dependent on Scopus's indexing practices, and Mendeley reader counts can be manipulated and have national and seniority biases. Practical implications Mendeley reader counts during the month of publication are more powerful than Scopus citations for comparing the average impacts of groups of documents but are not high enough to differentiate between the impacts of typical individual articles. Originality/value This is the first multi-disciplinary and systematic analysis of Mendeley reader counts from the publication month of an article.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 69(2017) no.2, S.174-183

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Abstract

A huge number of informal messages are posted every day in social network sites, blogs, and discussion forums. Emotions seem to be frequently important in these texts for expressing friendship, showing social support or as part of online arguments. Algorithms to identify sentiment and sentiment strength are needed to help understand the role of emotion in this informal communication and also to identify inappropriate or anomalous affective utterances, potentially associated with threatening behavior to the self or others. Nevertheless, existing sentiment detection algorithms tend to be commercially oriented, designed to identify opinions about products rather than user behaviors. This article partly fills this gap with a new algorithm, SentiStrength, to extract sentiment strength from informal English text, using new methods to exploit the de facto grammars and spelling styles of cyberspace. Applied to MySpace comments and with a lookup table of term sentiment strengths optimized by machine learning, SentiStrength is able to predict positive emotion with 60.6% accuracy and negative emotion with 72.8% accuracy, both based upon strength scales of 1-5. The former, but not the latter, is better than baseline and a wide range of general machine learning approaches.

Date

22. 1.2011 14:29:23

Footnote

Vgl. auch das Erratum in: Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.419

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.12, S.2544-2558

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Abstract

Purpose Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value This is the first qualitative analysis of general COVID-19-related retweeting.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 72(2020) no.6, S.945-962

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Abstract

Collaboration is encouraged because it is believed to improve academic research, supported by indirect evidence in the form of more coauthored articles being more cited. Nevertheless, this might not reflect quality but increased self-citations or the "audience effect": citations from increased awareness through multiple author networks. We address this with the first science wide investigation into whether author numbers associate with journal article quality, using expert peer quality judgments for 122,331 articles from the 2014-20 UK national assessment. Spearman correlations between author numbers and quality scores show moderately strong positive associations (0.2-0.4) in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities, and a possible negative association for decision sciences. This gives the first systematic evidence that greater numbers of authors associates with higher quality journal articles in the majority of academia outside the arts and humanities, at least for the UK. Positive associations between team size and citation counts in areas with little association between team size and quality also show that audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields.

Date

22. 6.2023 18:11:50

Source

Journal of the Association for Information Science and Technology. 74(2023) no.7, S.791-810

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Date

4.12.2006 12:12:22

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Abstract

Results from recent advances in link metrics have demonstrated that the hyperlink structure of national university systems can be strongly related to the research productivity of the individual institutions. This paper uses a page categorization to show that restricting the metrics to subsets more closely related to the research of the host university can produce even stronger associations. A partial overlap was also found between the effects of applying advanced document models and separating page types, but the best results were achieved through a combination of the two.

Source

Journal of the American Society for Information Science and technology. 54(2003) no.7, S.594-602

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Abstract

Although citation counts are often used to evaluate the research impact of academic publications, they are problematic for books that aim for educational or cultural impact. To fill this gap, this article assesses whether a number of simple metrics derived from Amazon.com reviews of academic books could provide evidence of their impact. Based on a set of 2,739 academic monographs from 2008 and a set of 1,305 best-selling books in 15 Amazon.com academic subject categories, the existence of significant but low or moderate correlations between citations and numbers of reviews, combined with other evidence, suggests that online book reviews tend to reflect the wider popularity of a book rather than its academic impact, although there are substantial disciplinary differences. Metrics based on online reviews are therefore recommended for the evaluation of books that aim at a wide audience inside or outside academia when it is important to capture the broader impacts of educational or cultural activities and when they cannot be manipulated in advance of the evaluation.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.3, S.566-581

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Abstract

A common task in both Webmetrics and Web information retrieval is to identify a set of Web pages or sites that are similar in content. In this paper we assess the extent to which links, colinks and couplings can be used to identify similar Web sites. As an experiment, a random sample of 500 pairs of domains from the UK academic Web were taken and human assessments of site similarity, based upon content type, were compared against ratings for the three concepts. The results show that using a combination of all three gives the highest probability of identifying similar sites, but surprisingly this was only a marginal improvement over using links alone. Another unexpected result was that high values for either colink counts or couplings were associated with only a small increased likelihood of similarity. The principal advantage of using couplings and colinks was found to be greater coverage in terms of a much larger number of pairs of sites being connected by these measures, instead of increased probability of similarity. In information retrieval terminology, this is improved recall rather than improved precision.

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Abstract

This study investigates a range of metrics available when a nanoscience and nanotechnology article is published to see which metrics correlate more with the number of citations to the article. It also introduces the degree of internationality of journals and references as new metrics for this purpose. The journal impact factor; the impact of references; the internationality of authors, journals, and references; and the number of authors, institutions, and references were all calculated for papers published in nanoscience and nanotechnology journals in the Web of Science from 2007 to 2009. Using a zero-inflated negative binomial regression model on the data set, the impact factor of the publishing journal and the citation impact of the cited references were found to be the most effective determinants of citation counts in all four time periods. In the entire 2007 to 2009 period, apart from journal internationality and author numbers and internationality, all other predictor variables had significant effects on citation counts.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.1055-1064

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Abstract

A layered approach for identifying communities in the Web is presented and explored by applying the flake exact community identification algorithm to the UK academic Web. Although community or topic identification is a common task in information retrieval, a new perspective is developed by: the application of alternative document models, shifting the focus from individual pages to aggregated collections based upon Web directories, domains and entire sites; the removal of internal site links; and the adaptation of a new fast algorithm to allow fully-automated community identification using all possible single starting points. The overall topology of the graphs in the three least-aggregated layers was first investigated and found to include a large number of isolated points but, surprisingly, with most of the remainder being in one huge connected component, exact proportions varying by layer. The community identification process then found that the number of communities far exceeded the number of topological components, indicating that community identification is a potentially useful technique, even with random starting points. Both the number and size of communities identified was dependent on the parameter of the algorithm, with very different results being obtained in each case. In conclusion, the UK academic Web is embedded with layers of non-trivial communities and, if it is not unique in this, then there is the promise of improved results for information retrieval algorithms that can exploit this additional structure, and the application of the technique directly to partially automate Web metrics tasks such as that of finding all pages related to a given subject hosted by a single country's universities.

Source

Journal of documentation. 59(2003) no.4, S.410-429