Search (16 results, page 1 of 1)

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.; 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.; 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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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.
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

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) 0.01

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Date: 22. 6.2023 18:11:50

Thelwall, M.: Can Google's PageRank be used to find the most important academic Web pages? (2003) 0.01
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Abstract

Google's PageRank is an influential algorithm that uses a model of Web use that is dominated by its link structure in order to rank pages by their estimated value to the Web community. This paper reports on the outcome of applying the algorithm to the Web sites of three national university systems in order to test whether it is capable of identifying the most important Web pages. The results are also compared with simple inlink counts. It was discovered that the highest inlinked pages do not always have the highest PageRank, indicating that the two metrics are genuinely different, even for the top pages. More significantly, however, internal links dominated external links for the high ranks in either method and superficial reasons accounted for high scores in both cases. It is concluded that PageRank is not useful for identifying the top pages in a site and that it must be combined with a powerful text matching techniques in order to get the quality of information retrieval results provided by Google.
Thelwall, M.: Assessing web search engines : a webometric approach (2011) 0.01
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Abstract

Information Retrieval (IR) research typically evaluates search systems in terms of the standard precision, recall and F-measures to weight the relative importance of precision and recall (e.g. van Rijsbergen, 1979). All of these assess the extent to which the system returns good matches for a query. In contrast, webometric measures are designed specifically for web search engines and are designed to monitor changes in results over time and various aspects of the internal logic of the way in which search engine select the results to be returned. This chapter introduces a range of webometric measurements and illustrates them with case studies of Google, Bing and Yahoo! This is a very fertile area for simple and complex new investigations into search engine results.

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