Search (19 results, page 1 of 1)

Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Why are coauthored academic articles more cited : higher quality or larger audience? (2023) 0.03

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Date: 22. 6.2023 18:11:50
Source: Journal of the Association for Information Science and Technology. 74(2023) no.7, S.791-810

Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.01

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Date: 4.12.2006 12:12:22

Levitt, J.M.; Thelwall, M.: Citation levels and collaboration within library and information science (2009) 0.01
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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

Thelwall, M.; Harries, G.: ¬The connection between the research of a university and counts of links to its Web pages : an investigation based upon a classification of the relationships of pages to the research of the host university (2003) 0.01

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

Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011) 0.01

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Date: 22. 1.2011 14:27:06

Thelwall, M.; Maflahi, N.: Guideline references and academic citations as evidence of the clinical value of health research (2016) 0.01

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Date: 19. 3.2016 12:22:00

Thelwall, M.; Sud, P.: Mendeley readership counts : an investigation of temporal and disciplinary differences (2016) 0.01

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Date: 16.11.2016 11:07:22

Didegah, F.; Thelwall, M.: Co-saved, co-tweeted, and co-cited networks (2018) 0.01

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Date: 28. 7.2018 10:00:22

Thelwall, M.; Prabowo, R.: Identifying and characterizing public science-related fears from RSS feeds (2007) 0.01

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Date: 7. 3.2007 18:32:02

Thelwall, M.; Klitkou, A.; Verbeek, A.; Stuart, D.; Vincent, C.: Policy-relevant Webometrics for individual scientific fields (2010) 0.01

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Source: Journal of the American Society for Information Science and Technology. 61(2010) no.7, S.1464-1475

Maflahi, N.; Thelwall, M.: When are readership counts as useful as citation counts? : Scopus versus Mendeley for LIS journals (2016) 0.01
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Abstract

In theory, articles can attract readers on the social reference sharing site Mendeley before they can attract citations, so Mendeley altmetrics could provide early indications of article impact. This article investigates the influence of time on the number of Mendeley readers of an article through a theoretical discussion and an investigation into the relationship between counts of readers of, and citations to, 4 general library and information science (LIS) journals. For this discipline, it takes about 7 years for articles to attract as many Scopus citations as Mendeley readers, and after this the Spearman correlation between readers and citers is stable at about 0.6 for all years. This suggests that Mendeley readership counts may be useful impact indicators for both newer and older articles. The lack of dates for individual Mendeley article readers and an unknown bias toward more recent articles mean that readership data should be normalized individually by year, however, before making any comparisons between articles published in different years.
Kousha, K.; Thelwall, M.: How is science cited on the Web? : a classification of google unique Web citations (2007) 0.01
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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.

Thelwall, M.; Buckley, K.; Paltoglou, G.; Cai, D.; Kappas, A.: Sentiment strength detection in short informal text (2010) 0.01

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Date: 22. 1.2011 14:29:23

Thelwall, M.; Sud, P.; Wilkinson, D.: Link and co-inlink network diagrams with URL citations or title mentions (2012) 0.01

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Date: 6. 4.2012 18:16:22

Li, X.; Thelwall, M.; Kousha, K.: ¬The role of arXiv, RePEc, SSRN and PMC in formal scholarly communication (2015) 0.01

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Date: 20. 1.2015 18:30:22

Thelwall, M.: Are Mendeley reader counts high enough for research evaluations when articles are published? (2017) 0.01

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Date: 20. 1.2015 18:30:22

Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.01

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Date: 20. 1.2015 18:30:22

Kousha, K.; Thelwall, M.: Google Scholar citations and Google Web/URL citations : a multi-discipline exploratory analysis (2007) 0.01

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

Kousha, K.; Thelwall, M.: Patent citation analysis with Google (2017) 0.01
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Abstract

Citations from patents to scientific publications provide useful evidence about the commercial impact of academic research, but automatically searchable databases are needed to exploit this connection for large-scale patent citation evaluations. Google covers multiple different international patent office databases but does not index patent citations or allow automatic searches. In response, this article introduces a semiautomatic indirect method via Bing to extract and filter patent citations from Google to academic papers with an overall precision of 98%. The method was evaluated with 322,192 science and engineering Scopus articles from every second year for the period 1996-2012. Although manual Google Patent searches give more results, especially for articles with many patent citations, the difference is not large enough to be a major problem. Within Biomedical Engineering, Biotechnology, and Pharmacology & Pharmaceutics, 7% to 10% of Scopus articles had at least one patent citation but other fields had far fewer, so patent citation analysis is only relevant for a minority of publications. Low but positive correlations between Google Patent citations and Scopus citations across all fields suggest that traditional citation counts cannot substitute for patent citations when evaluating research.

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