-
Vaughan, L.; Thelwall, M.: ¬A modelling approach to uncover hyperlink patterns : the case of Canadian universities (2005)
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- Abstract
- Hyperlink patterns between Canadian university Web sites were analyzed by a mathematical modeling approach. A multiple regression model was developed which shows that faculty quality and the language of the university are important predictors for links to a university Web site. Higher faculty quality means more links. French universities received lower numbers of links to their Web sites than comparable English universities. Analysis of interlinking between pairs of universities also showed that English universities are advantaged. Universities are more likely to link to each other when the geographical distance between them is less than 3000 km, possibly reflecting the east vs. west divide that exists in Canadian society.
-
Payne, N.; Thelwall, M.: Mathematical models for academic webs : linear relationship or non-linear power law? (2005)
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- Abstract
- Previous studies of academic web interlinking have tended to hypothesise that the relationship between the research of a university and links to or from its web site should follow a linear trend, yet the typical distribution of web data, in general, seems to be a non-linear power law. This paper assesses whether a linear trend or a power law is the most appropriate method with which to model the relationship between research and web site size or outlinks. Following linear regression, analysis of the confidence intervals for the logarithmic graphs, and analysis of the outliers, the results suggest that a linear trend is more appropriate than a non-linear power law.
-
Thelwall, M.; Wouters, P.; Fry, J.: Information-centered research for large-scale analyses of new information sources (2008)
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- Abstract
- New mass publishing genres, such as blogs and personal home pages provide a rich source of social data that is yet to be fully exploited by the social sciences and humanities. Information-centered research (ICR) not only provides a genuinely new and useful information science research model for this type of data, but can also contribute to the emerging e-research infrastructure. Nevertheless, ICR should not be conducted on a purely abstract level, but should relate to potentially relevant problems.
-
Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006)
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- Date
- 4.12.2006 12:12:22
-
Thelwall, M.: Can Google's PageRank be used to find the most important academic Web pages? (2003)
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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.
-
Didegah, F.; Thelwall, M.: Determinants of research citation impact in nanoscience and nanotechnology (2013)
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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.
-
Levitt, J.M.; Thelwall, M.: Citation levels and collaboration within library and information science (2009)
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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.: Conceptualizing documentation on the Web : an evaluation of different heuristic-based models for counting links between university Web sites (2002)
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- Abstract
- All known previous Web link studies have used the Web page as the primary indivisible source document for counting purposes. Arguments are presented to explain why this is not necessarily optimal and why other alternatives have the potential to produce better results. This is despite the fact that individual Web files are often the only choice if search engines are used for raw data and are the easiest basic Web unit to identify. The central issue is of defining the Web "document": that which should comprise the single indissoluble unit of coherent material. Three alternative heuristics are defined for the educational arena based upon the directory, the domain and the whole university site. These are then compared by implementing them an a set of 108 UK university institutional Web sites under the assumption that a more effective heuristic will tend to produce results that correlate more highly with institutional research productivity. It was discovered that the domain and directory models were able to successfully reduce the impact of anomalous linking behavior between pairs of Web sites, with the latter being the method of choice. Reasons are then given as to why a document model an its own cannot eliminate all anomalies in Web linking behavior. Finally, the results from all models give a clear confirmation of the very strong association between the research productivity of a UK university and the number of incoming links from its peers' Web sites.
-
Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011)
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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)
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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)
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- Date
- 16.11.2016 11:07:22
-
Didegah, F.; Thelwall, M.: Co-saved, co-tweeted, and co-cited networks (2018)
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- Date
- 28. 7.2018 10:00:22
-
Kousha, K.; Thelwall, M.: How is science cited on the Web? : a classification of google unique Web citations (2007)
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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)
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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)
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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)
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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)
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- 20. 1.2015 18:30:22
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Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020)
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- 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)
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- Date
- 22. 6.2023 18:11:50
