-
Thelwall, M.; Sud, P.: Mendeley readership counts : an investigation of temporal and disciplinary differences (2016)
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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
-
Thelwall, M.; Buckley, K.; Paltoglou, G.; Cai, D.; Kappas, A.: Sentiment strength detection in short informal text (2010)
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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
-
Harries, G.; Wilkinson, D.; Price, L.; Fairclough, R.; Thelwall, M.: Hyperlinks as a data source for science mapping : making sense of it all (2005)
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- Source
- Journal of information science. 30(2005) no.5, S.436-
-
Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006)
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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)
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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)
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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
-
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.; 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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- 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)
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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)
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- Date
- 22. 6.2023 18:11:50
-
Thelwall, M.: Webometrics (2009)
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- Date
- 5. 8.2010 17:33:43
-
Thelwall, M.: Assessing web search engines : a webometric approach (2011)
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- Date
- 5. 2.2012 19:36:40
-
Didegah, F.; Thelwall, M.: Determinants of research citation impact in nanoscience and nanotechnology (2013)
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- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.1055-1064
-
Shema, H.; Bar-Ilan, J.; Thelwall, M.: Do blog citations correlate with a higher number of future citations? : Research blogs as a potential source for alternative metrics (2014)
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- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.1018-1027
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Thelwall, M.; Kousha, K.: ResearchGate: Disseminating, communicating, and measuring scholarship? (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.5, S.876-889
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Thelwall, M.: Book genre and author gender : romance > paranormal-romance to autobiography > memoir (2017)
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- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1212-1223
