Search (30 results, page 1 of 2)

  • × author_ss:"Thelwall, M."
  1. Thelwall, M.; Buckley, K.; Paltoglou, G.; Cai, D.; Kappas, A.: Sentiment strength detection in short informal text (2010) 0.00 
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    Date
    22. 1.2011 14:29:23
  2. Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.00 
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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
  3. Thelwall, M.; Wilkinson, D.: Finding similar academic Web sites with links, bibliometric couplings and colinks (2004) 0.00 
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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.
  4. Thelwall, M.: Assessing web search engines : a webometric approach (2011) 0.00 
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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.
    Source
    Innovations in information retrieval: perspectives for theory and practice. Eds.: A. Foster, u. P. Rafferty
  5. Thelwall, M.: ¬A layered approach for investigating the topological structure of communities in the Web (2003) 0.00 
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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.
  6. Thelwall, M.; Sud, P.: ¬A comparison of methods for collecting web citation data for academic organizations (2011) 0.00 
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    Abstract
    The primary webometric method for estimating the online impact of an organization is to count links to its website. Link counts have been available from commercial search engines for over a decade but this was set to end by early 2012 and so a replacement is needed. This article compares link counts to two alternative methods: URL citations and organization title mentions. New variations of these methods are also introduced. The three methods are compared against each other using Yahoo!. Two of the three methods (URL citations and organization title mentions) are also compared against each other using Bing. Evidence from a case study of 131 UK universities and 49 US Library and Information Science (LIS) departments suggests that Bing's Hit Count Estimates (HCEs) for popular title searches are not useful for webometric research but that Yahoo!'s HCEs for all three types of search and Bing's URL citation HCEs seem to be consistent. For exact URL counts the results of all three methods in Yahoo! and both methods in Bing are also consistent. Four types of accuracy factors are also introduced and defined: search engine coverage, search engine retrieval variation, search engine retrieval anomalies, and query polysemy.
  7. Thelwall, M.: Can Google's PageRank be used to find the most important academic Web pages? (2003) 0.00 
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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.
  8. Thelwall, M.; Vaughan, L.: New versions of PageRank employing alternative Web document models (2004) 0.00 
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    Abstract
    Introduces several new versions of PageRank (the link based Web page ranking algorithm), based on an information science perspective on the concept of the Web document. Although the Web page is the typical indivisible unit of information in search engine results and most Web information retrieval algorithms, other research has suggested that aggregating pages based on directories and domains gives promising alternatives, particularly when Web links are the object of study. The new algorithms introduced based on these alternatives were used to rank four sets of Web pages. The ranking results were compared with human subjects' rankings. The results of the tests were somewhat inconclusive: the new approach worked well for the set that includes pages from different Web sites; however, it does not work well in ranking pages that are from the same site. It seems that the new algorithms may be effective for some tasks but not for others, especially when only low numbers of links are involved or the pages to be ranked are from the same site or directory.
  9. Thelwall, M.: Web indicators for research evaluation : a practical guide (2016) 0.00 
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    Series
    Synthesis lectures on information concepts, retrieval, and services; 52
  10. Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.00 
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    Date
    4.12.2006 12:12:22
  11. Levitt, J.M.; Thelwall, M.: Citation levels and collaboration within library and information science (2009) 0.00 
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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
  12. Thelwall, M.: Directing students to new information types : a new role for Google in literature searches? (2005) 0.00 
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    Date
    3. 6.2007 16:37:29
  13. Vaughan, L.; Thelwall, M.: Search engine coverage bias : evidence and possible causes (2004) 0.00 
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    Date
    14. 8.2004 10:30:29
  14. Thelwall, M.; Kousha, K.: ResearchGate: Disseminating, communicating, and measuring scholarship? (2015) 0.00 
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    Date
    26. 4.2015 19:29:49
  15. Maflahi, N.; Thelwall, M.: When are readership counts as useful as citation counts? : Scopus versus Mendeley for LIS journals (2016) 0.00 
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    Date
    27.12.2015 11:29:37
  16. Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011) 0.00 
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    Date
    22. 1.2011 14:27:06
  17. Thelwall, M.; Maflahi, N.: Guideline references and academic citations as evidence of the clinical value of health research (2016) 0.00 
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    Date
    19. 3.2016 12:22:00
  18. Thelwall, M.; Sud, P.: Mendeley readership counts : an investigation of temporal and disciplinary differences (2016) 0.00 
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    Date
    16.11.2016 11:07:22
  19. Didegah, F.; Thelwall, M.: Co-saved, co-tweeted, and co-cited networks (2018) 0.00 
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    Date
    28. 7.2018 10:00:22
  20. Vaughan, L.; Thelwall, M.: Scholarly use of the Web : what are the key inducers of links to journal Web sites? (2003) 0.00 
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    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.1, S.29-38

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