Altmetrics, Social Media Indicators and Webometrics (Kousha metrics)
[websites] Kousha, K., Thelwall, M. & Abdoli, M. (2021). Which types of online evidence show the non-academic benefits of research? Websites cited in UK impact case studies. Quantitative Science Studies. [Summarises the types of websites used to evidence the non-academic impacts of UK research.]
[Twitter] Mohammadi, E., Thelwall, M., Kwasny, M., & Holmes, K. (2018). Academic information on Twitter: A user survey. PLOS ONE, 13(5): e0197265. https://doi.org/10.1371/journal.pone.0197265. [A survey of people that tweet about academic research. A surprisingly high proportion are not academics.]
[Twitter, Mendeley] Didegah, F. & Thelwall, M. (2018). Co-saved, co-tweeted and co-cited networks. Journal of the Association for Information Science and Technology, 69(8), 959-973. http://dx.doi.org/10.1002/asi.24028.[There is very little overlap between co-saved, co-tweeted and co-cited networks.]
[All] Thelwall, M. & Nevill, T. (2018). Could scientists use Altmetric.com scores to predict longer term citation counts? [free access] [w] [data] Journal of Informetrics, 12(1), 237–248. [Academic.com scores can be used to help predict future citation counts, especially if the Mendeley reader component is included. Considering both Altmetric.com scores and journal impact factors gives the best predictions. Altmetric.com scores also seem to partly reflect non-scholarly impact dimensions in some fields.]
[Mendeley] Thelwall, M. (2017). Are Mendeley reader counts useful impact indicators in all fields?Scientometrics, 113(3), 1721–1731. doi:10.1007/s11192-017-2557-x [Correlations between Mendeley reader counts and Scopus citation counts are strong in almost all of 325 narrow Scopus fields checked, so Mendeley reader counts are an almost universally strong citation impact indicator.]
[ResearchGate] Orduna-Malea, E., Martín-Martín, A., Thelwall, M., & Delgado López-Cózar, E. (2017). Do ResearchGate Scores create ghost academic reputations? Scientometrics. 112(1), 443-460. doi:10.1007/s11192-017-2396-9. See LSE Impact Blog post.
[Patent citations] Orduna-Malea, E., Thelwall, M. & Kousha, K. (2017). Web citations in patents: Evidence of technological impact? Journal of the Association for Information Science and Technology, 68(8), 1967-1974. doi:10.1002/asi.23821 [URL citations in online patents are common enough to be used to help rank major US universities for an aspect of technological impact.]
[Figshare] Thelwall, M. & Kousha, K. (2016). Figshare: A universal repository for academic resource sharing?Online Information Review, 40(3), 333-346. doi:10.1108/OIR-06-2015-0190 [The repository FigShare host resources from some subject areas more than others but the uptake of its resources does not depend on their subject area.]
[ResearchGate] Thelwall, M., & Kousha, K. (2017). ResearchGate articles: Age, discipline, audience size and impact. Journal of the Association for Information Science and Technology, 68(2), 468-479. doi:10.1002asi.23675 [Article views in ResearchGate have a significant positive correlation with Scopus citations but seem to reflect a wider audience than scholarly citations.]
[altmetrics and webometrics] Thelwall, M., Kousha, K., Dinsmore, A. & Dolby, K. (2016). Alternative metric indicators for funding scheme evaluations. Aslib Journal of Information Management, 68(1), 2-18. doi:10.1108/AJIM-09-2015-0146 [Some alternative indicators can aid funding agencies’ evaluations of their funding schemes, if used carefully.]
[Mendeley] Fairclough, R. & Thelwall, M. (2015). National research impact indicators from Mendeley readers. Journal of Informetrics, 9(4), 845–859. doi:10.1016/j.joi.2015.08.003. [Mendeley reader counts can be used instead of citations for national research impact indicators and seem to identify trends about a year earlier.]
[All] Thelwall, M. & Delgado, M. (2015). Arts and humanities research evaluation: No metrics please, just data. Journal of Documentation, 71(4), 817-833. DOI:10.1108/JD-02-2015-0028 [Arts and humanities researchers should be encouraged to think creatively about the kinds of data that they may be able to generate in support of the value of their research and should not rely upon standardised metrics.]
[Mendeley] Thelwall, M. & Sud, P. (2016). Mendeley readership counts: An investigation of temporal and disciplinary differences. Journal of the Association for Information Science and Technology, 57(6), 3036-3050. doi:10.1002/asi.23559 [Mendeley reader counts increase more quickly than do citation counts across many different areas of research and stabilise after about five years. Coupled with high correlations between Mendeley readers and citations, this confirms the value of Mendeley reader counts as early evidence of impact for research.]
[Mendeley] Thelwall, M. & Wilson, P. (2016). Mendeley readership altmetrics for medical articles: An analysis of 45 fields, Journal of the Association for Information Science and Technology, 67(8), 1962-1972. doi:10.1002/asi.23501 [Using the new Mendeley API with its more comprehensive information, shows that Mendeley bookmarks correlate highly (0.7) with citations to medical articles from 2009 in almost all fields and that readership counts follow a lognormal or a hooked power law distribution rather than a power law.]
[Mendeley] Mohammadi, E., Thelwall, M. & Kousha, K. (2016). Can Mendeley bookmarks reflect readership? A survey of user motivations. Journal of the Association for Information Science and Technology, 67(5), 1198-1209. doi:10.1002/asi.23477 [Based on a survey of Mendeley users, articles are bookmarked in Mendeley mainly because they have been read or intend to be read. Hence Mendeley bookmarks can be used as indicators of readership for articles, at least for Mendeley users.]
[Amazon book reviews, Google Books] Kousha, K. & Thelwall, M. (2016). Can Amazon.com reviews help to assess the wider impacts of books? Journal of the Association for Information Science and Technology, 67(3), 566-581. doi:10.1002/asi.23404.[Introduces Amazon book reviews (number and sentiment) as metrics for academic book impact. Shows that book reviews tend to reflect the wider popularity of books rather than their purely academic impact.]
[Google Scholar, Microsoft Academic Search, Mendeley, Academia, LinkedIn, SlideShare] Mas-Bleda, A., Thelwall, M., Kousha, K. & Aguillo, I.F. (2014). Do highly cited researchers successfully use the Social Web? Scientometrics, 101(1), 337-356. [Shows that few European highly cited researchers use social web sites.]
[Mendeley] Mohammadi, E., Thelwall, M., Haustein, S., & Larivière, V. (2015). Who reads research articles? An altmetrics analysis of Mendeley user categories. Journal of the Association for Information Science and Technology, 66(9), 1832-1846. doi:10.1002/asi.23286. [PhD students, postgraduates and postdocs are the main readers of articles in Mendeley, although there are disciplinary differences.]
[ResearchGate] Thelwall, M. & Kousha, K. (2015). ResearchGate: Disseminating, communicating and measuring scholarship? Journal of the American Society for Information Science and Technology 66(5). 876–889. doi:10.1002/asi.23236 [Statistics reported by ResearchGate about its users broadly reflect traditional academic hierarchies, at least at the country level, but some countries make much more use of ResearchGate than do others.].
[Blogs] Shema, H., Bar-Ilan, J., & Thelwall, M. (2015). How is research blogged? A content analysis approach. Journal of the Association for Information Science and Technology, 66(6), 1136–1149. doi:10.1002/asi.23239 [Shows that health research bloggers tend to cover others's work, seem to aim at a general audience, and often include critical comments.]
[Twitter, Blogs, Facebook, Google+, forums, mainstream media, LinkedIn, Reddit, Pinterest, research highlights, Q&A] Thelwall, M., Haustein, S., Larivière, V. & Sugimoto, C. (2013). Do altmetrics work? Twitter and ten other candidates. PLOS ONE, 8(5): e64841. doi:10.1371/journal.pone.0064841
Kousha, K. & Thelwall, M. (2015). An automatic method for extracting citations from Google Books. Journal of the American Society for Information Science and Technology, 66(2), 309–320. [Citations can be automatically extracted from Google Books and this is useful for social sciences and humanities research evaluation.]
Gender in academic research (bibliometric studies)
Thelwall, M. Abdullah, A, & Fairclough, R. (in press). Researching women and men 1996-2020: Is androcentrism still dominant? Quantitative Science Studies. [The proportion of research about women has steadily increased in recent decades, with more research now about women than about men.]
Thelwall, M. (2020). Mid-career field switches reduce gender disparities in academic publishing.Scientometrics, 123(3), 1365-1383. [When academics switch the field that they publish in during their career, the net effect reduces gender disparities: Relative to men, women are more likely to switch to fields with a higher proportion of men. This also contains a small and related tribute to Prof Judit Bar-Ilan.]
Thelwall, M. & Mas-Bleda, A. (2020). How common are explicit research questions in journal articles?Quantitative Science Studies, 1(2), 730–748. [Research questions are almost never explicitly mentioned (under 2%) by articles in engineering, physical, life and medical sciences, and occurred in less than 20% of articles in all broad fields.]
Kousha, K., & Thelwall, M. (2022). Covid-19 refereeing duration and impact in major medical journals. Quantitative Science Studies.[Refereeing for Covid-related journal articles was quicker, but apparently without compromising quality.]
Thelwall, M. & Fairclough, R. (2020). All downhill from the PhD? The typical impact trajectory of US academic careers.Quantitative Science Studies, 1(3), 1334-1348. [Experienced researchers do not seem to improve their citation impact: For researchers starting and finishing their publication careers in the USA, the average citation impact of their publications decreases towards the end of their careers, on average.]
Vera-Baceta, M., Thelwall, M. & Kousha, K. (in press). Web of Science and Scopus language coverage, Scientometrics. [Scopus and the Web of Science have different coverage of non-English languages, with each having strengths in some languages.]
Thelwall, M., (2018). Does Microsoft Academic find early citations? Scientometrics, 114(1), 325–334. doi:10.1007/s11192-017-2558-9 [Microsoft Academic does not have a substantial early citation advantage over Scopus for Nature, Science and seven library and information science journals.]
Thelwall, M. (in press). Three practical field normalised alternative indicator formulae for research evaluation. Journal of Informetrics. 10.1016/j.joi.2016.12.002 [A robust indicator is introduced for citation counts that allows narrower confidence intervals to be calculated for more powerful analyses. Two new proportion cited indicators are introduced to allow more powerful web indicators when a low proportion of outputs have a non-zero indicator score.]
Thelwall, M. (2017). Trends in African scientific output and impact 1996-2015. African Journal of Library, Archives and Information Science, 27(2), 131-143.[African countries are increasing their share of the world’s output but mostly decreasing their relative citation impact - probably due to increasing national research.]
Thelwall, M. (2016). Citation count distributions for large monodisciplinary journals. Journal of Informetrics, 10(3), 863-874. doi:10.1016/j.joi.2016.07.006 [The discretised lognormal fits citation distributions for individual large journals better than the hooked power law, reversing the situation for entire subject categories. Ultra-high precision (128+bit) parameter fitting software for the hooked power law is also introduced.] code and data for this paper.
Kousha, K. & Thelwall, M. (2017). Patent citation analysis with Google. Journal of the Association for Information Science and Technology, 68(1), 48-61. doi:10.1002/asi.23608 [Citations from patents to academic papers can be extracted semi-automatically from the Google Patents index and the results give evidence of commercial relevance for a varying minority of articles in applied disciplines.]
Thelwall, M. & Wilson, P. (2014). Distributions for cited articles from individual subjects and years. Journal of Informetrics, 8(4), 824-839. [Shows that for a set of articles from a single subject and year, the hooked power law and the lognormal distributions fit better than the power law (for articles with at least one citation), even for the distribution tail, and so should always be used in preference to the power law.]
Levitt, J., & Thelwall, M. (2013). Alphabetization and the skewing of first authorship towards last names early in the alphabet. Journal of Informetrics 7(3), 575– 582.
Didegah, F., Thelwall, M. & Gazni, A. (2012). An international comparison of journal publishing and citing behaviours, Journal of Informetrics 6(4), 516-531.
Levitt, J., Thelwall, M. & Oppenheim, C. (2011). Variations between subjects in the extent to which the social sciences have become more interdisciplinary. Journal of the American Society for Information Science and Technology, 62(6), 1118–1129
Thelwall, M. (2018). Gender bias in sentiment analysis. Online Information Review, 42(1), 45-57. [publisher version]. doi:10.1108/OIR-05-2017-0139 [Lexical sentiment analysis over-represents the opinions of females because they express sentiment more clearly.]
Paltoglou, G. & Thelwall, M. (2017). Sensing social media: A range of approaches for sentiment analysis. In: Holyst, J. (Ed.) Cyberemotions: Collective emotions in cyberspace. Berlin, Germany: Springer (pp. 97-117). doi: 10.1007/978-3-319-43639-5_6 [Sentiment analysis methods for social media texts - review.]
Gobron, S., Ahn, J., Paltoglou, G., Thelwall, M. & Thalmann, D. (2010). From sentence to emotion: A real-time three-dimensional graphics metaphor of emotions extracted from text. The Visual Computer: International Journal of Computer Graphics, 26(6-8), 505-519.
Thelwall, M., Kousha, K. & Thelwall, S. (2021). Covid-19 vaccine hesitancy on English-language Twitter. El Profesional de la Información. 30(2), e300212. https://doi.org/10.3145/epi.2021.mar.12 [Vaccine hesitation was mainly expressed by people with right-wing tweeting themes, although it was also expressed by some non-political tweeters, reaching other topics on Twitter.]
Thelwall, M. & Thelwall, S. (2020). Covid-19 tweeting in English: Gender differences. El Profesional de la Información, 29(3), e290301. [Key findings: a) Women seem to be taking a disproportionate share of the responsibility for directly keeping the population safe, and therefore it is particularly important that to convey safety messages to females. b) Failure to impose a sporting bans whilst encouraging social distancing may send mixed messages to males.]
Thelwall, S. & Thelwall, M. (2020). Anthropomorphizing atopy: Tweeting about eczema. Journal of the Dermatology Nurses' Association, 12(2), 74-77. [People tweeting about their eczema use humour to announce attacks and giving it agency.]
Makita, M., Mas-Bleda, A., Stuart, E., & Thelwall, M. (2019). Ageing, old age and older adults: a social media analysis of dominant topics and discourses. Ageing & Society, DOI: 10.1017/S0144686X19001016 [Twitter reproduces the ageist language of tradiational media.]
Stuart, E., Thelwall, M., & Stuart, D. (2019). Which image types do universities tweet? First Monday, 24(3). [Universities typically tweet showcasing and humanising images, apparently broadcasting to potential future students.]
Thelwall, M., Buckley, K., & Paltoglou, G. (2011). Sentiment in Twitter events. Journal of the American Society for Information Science and Technology, 62(2), 406-418. [Peaks of interest in external events are reflected in slight increases in negative sentiment strength for the topic.]
YouTube [see also the social web section]
Thelwall, M. & Foster, D. (2021). Male or female gender-polarised YouTube videos are less viewed. Journal of the Association for Information Science and Technology, 72(12), 1545-1557. https://doi.org/10.1002/asi.24529 [YouTube videos primarily attracting a single gender (male or female) tend to be less popular than videos attracting both males and females. This means that targetting content at a single gender is not overall the best strategy, although it might be for some content.]
Thelwall, M. (2018). Can museums find male or female audiences online with YouTube?Aslib Journal of Information Management, 70(5), 481-497. [There are huge gender differences in the audiences of museum YouTube channels, including for museums of the same broad type. Museums can target audiences by gender through YouTube.]
Thelwall, M. & Mas-Bleda, A. (2018). YouTube science channel video presenters and comments: Female friendly or vestiges of sexism? Aslib Journal of Information Management, 70(1), 28-46. doi:10.1108/AJIM-09-2017-0204 [Popular science channel comments tend to be dominated by males and tend not to be negative towards, females although there is a minority of sexist commenting. Presenter gender does not seem to influence audience gender.] [Note that The method used to detect gender gives a small bias in favour of males. After removing this bias, the Tyler DeWitt channel has 3% more female than male commenters, but all the other channels have a majority of male commenters. See also gender detection accuracy calculations]
Thelwall, M., Kousha, K., Weller, K., & Puschmann, C. (2012). Assessing the impact of online academic videos. In: G. Widen Wulff & K. Holmberg, (Eds), Social Information Research, Bradford: Emerald Group Publishing Limited. (pp. 195-213).
Thelwall, M. (2019). Reader and author gender and genre in Goodreads. Journal of Librarianship & Information Science, 5(2), 403-430. [In most Goodreads genres, reviewers give higher ratings to books authored by their own gender. Readers and authors also seem to value gendered aspects of books, even in non-gendered genres.]
Thelwall, M. (2017). Book genre and author gender: romance>paranormal-romance to autobiography>memoir. Journal of the Association for Information Science and Technology, 68(5), 1212-1223. 10.1002/asi.23768. [There are gender differences in authorship in almost all genres and gender differences the level of interest in, and ratings of, books in a minority of genres. There is not a clear relationship between the success of an author's gender and the prevalence of that gender within a genre.]
Thelwall, M. & Kousha, K. (2017). Goodreads: A social network site for book readers. Journal of the Association for Information Science and Technology, 68(4), 972-983. doi:10.1002/asi.23733 [Goodreads users are predominantly female. Members choose their own combinations of book-related and social networking activities within the site.]
Thelwall, M., Goriunova, O. Vis, F., Faulkner, S., Burns, A., Aulich, J. Mas-Bleda, A., Stuart, E. & D’Orazio, F. (2016). Chatting through pictures? A classification of images tweeted in one week in the UK and USA. Journal of the Association for Information Science and Technology, 67(11), 2575-2586. [People tend to share photographs more than other types of images on Twitter, often apparently in real time, and often of people, including selfies. Layered or hybrid images are also common, such as screenshots, collages, and captioned pictures, even for routine sharing.]
Thelwall, M. & Kappas, A. (2014). The role of sentiment in the social web. In: von Scheve, C. & Salmela, M. (eds.) Collective Emotions. Oxford: Oxford University Press (pp. 375-388).
Thelwall, M. (2011). Privacy and gender in the Social Web. In: Sabine Trepte, Leonard Reinecke (Eds), Privacy online: Perspectives on Privacy and Self-Disclosure in the Social Web, New York: Springer (pp. 255-269).
Chapter summary: Gender is important for understanding attitudes to privacy in the social web because of the many gender-related privacy differences. In general, women are more concerned about privacy than men but nevertheless publish more personal information in blogs and social network sites. The root causes of the differences seem to lie in socialised gendered communication strategies and privacy-related issues that disproportionately concern women. This chapter reviews evidence for gendered online communication and privacy concerns, focusing mainly on blogs, social network sites and YouTube, and includes a special section on LGBT issues. [See also book web site]
Thelwall, M., Wilkinson, D. & Uppal, S.(2010). Data mining emotion in social network communication: Gender differences in MySpace, Journal of the American Society for Information Science and Technology, 61(1), 190-199.[Two thirds of comments in US MySpace expressed positive sentiment but a minority (20%) contained negative sentiment; females are likely to give and receive more positive comments than are males.]
Thelwall, M. (2008). Fk yea I swear: Cursing and gender in a corpus of MySpace pages, Corpora, 3(1), 83-107. Preprint (with extended literature review and background information compared to the published version, and a revised first two paragraphs of the conclusion [8 Jan, 2008]) available at: http://www.scit.wlv.ac.uk/~cm1993/papers/MySpaceSwearing_online.doc
Koteyko, N. Thelwall, M. & Nerlich, B. (2010). From carbon markets to carbon morality: creative compounds as framing devices in online discourses on climate change mitigation, Science Communication, 32(1), 25-54.
Prabowo, R., Thelwall, M., Hellsten I., & Scharnhorst A., (2008). Evolving debate in online communication: A graph analytical approach, Internet Research.18(5), 520-540.
Park, H. W., & Thelwall, M. (2008). Developing network indicators for ideological landscapes from the political blogosphere in South Korea, Journal of Computer-Mediated Communication, 13(4), 856-879.
Thelwall, M. & Hasler, L. (2007). Blog search engines. Online Information Review, 31(4), 467-479.
Sud, P. & Thelwall, M. (2014). Linked title mentions: A new automated link search candidate. Scientometrics, 101(3), 1831-1849. [Introduces a new automatic link search method that is in Webometric Analyst and can give more accurate results that URL citations or title mentions in certain circumstances.]
Thelwall, M. (2003). Web use and peer interconnectivity metrics for academic web sites, Journal of Information Science, 29(1), 11-20.
Thelwall, M. (2002). Conceptualizing documentation on the Web: an evaluation of different heuristic-based models for counting links between university web sites, Journal of the American Society for Information Science and Technology, 53(12), 995-1005.
[Cited in Microsoft patent: US 7739281 B2]
Wilkinson, D., Harries, G., Thelwall, M. & Price, E. (2003). Motivations for academic web site interlinking: Evidence for the web as a novel source of information on informal scholarly communication, Journal of Information Science, 29(1), 29(1), 59-66.
Thelwall, M. (2002). The top 100 linked pages on UK university web sites: high inlink counts are not usually directly associated with quality scholarly content, Journal of Information Science, 28(6), 485-493.
Zuccala, A., Thelwall, M., Oppenheim, C., & Dhiensa, R. (2008, to appear). Web Intelligence Analyses of Digital Libraries: A Case Study of the National electronic Library for Health (NeLH). Journal of Documentation.
Journal Link Analysis
Kim, H., Park, H.W., & Thelwall, M. (2006). Comparing academic hyperlink structures with journal publishing in Korea: A social network analysis, Science Communication, 27(4), 540-564
Kousha, K. & Thelwall, M. (2014). Disseminating Research with Web CV Hyperlinks. Journal of the Association for Information Science and Technology, 65(8), 1615–1626. [Shows that few EU researchers are fully exploiting their CVs to publicise their research.]
Mas Bleda, A., Thelwall, M., Kousha, K., & Aguillo, I. (2014). Successful researchers publicizing research online: An outlink analysis of European highly cited scientists’ personal Websites, Journal of Documentation, 70(1), 148-172
Li, X., Thelwall, M., Musgrove, P. & Wilkinson, D. (2005). National and international university departmental web site interlinking: Part 1, validation of departmental link analysis. Scientometrics, 64(2), 151-185.
Li, X., Thelwall, M., Musgrove, P. & Wilkinson, D. (2005). National and international university departmental web site interlinking: Part 2, link patterns. Scientometrics, 64(2), 187-208.
Park, H. & Thelwall, M. (2006). Web science communication in the age of globalization: Links among universities’ websites in Asia and Europe. New Media & Society, 8(4), 631-652
Tang, R. & Thelwall, M. (2008). A hyperlink analysis of US public and academic libraries’ Web sites, Library Quarterly, 78(4), 419-435.
Vaughan, L. & Thelwall, M. (2005). A modeling approach to uncover hyperlink patterns: The case of Canadian universities. Information Processing & Management, 41(2), 347-359.
Tang, R. & Thelwall, M. (2004). Patterns of national and international web inlinks to US academic departments: An analysis of disciplinary variations. Scientometrics, 60(3), 475-485.
Thelwall, M. & Tang, R. (2003). Disciplinary and linguistic considerations for academic Web linking: An exploratory hyperlink mediated study with Mainland China and Taiwan, Scientometrics, 58(1), 153-179.
Thelwall, M., & Aguillo, I. (2003). La salud de las Web universitarias españolas, Revista Española de Documentación Científica, 26(3), 291-305.
Thelwall, M. & Price, E. (2003). Disciplinary differences in academic web presence – A statistical study of the UK. Libri, 53(4), 242-253.
Tang, R. & Thelwall, M. (2003). Disciplinary differences in US academic departmental web site interlinking, Library & Information Science Research, 25(4), 437-458.
Li, X., Thelwall, M., Musgrove, P. & Wilkinson, D. (2003). The relationship between the links/Web Impact Factors of computer science departments in UK and their RAE (Research Assessment Exercise) ranking in 2001, Scientometrics, 57(2), 239-255.
Chu, H., He, S. & Thelwall, M. (2002). Library and information science schools in Canada and USA: A Webometric perspective. Journal of Education for Library and Information Science, 43(2), 110-125.
Thelwall, M. (2001). Results from a Web Impact Factor crawler, Journal of Documentation, 57(2), 177-191.
Soualmia, L.F., Darmoni, S.J. Le Duff, F., Douyère, M., & Thelwall, M. (2002). Web Impact Factor: a bibliometric criterion applied to medical informatics societies’ Web sites, Medical Informatics in Europe MIE2002 congress (to be held in Budapest, Hungary, August 25-29).
Douyère, M., Soualmia, L.F., Le Duff, F., Thelwall, M. & Darmoni, S.J. (2002). Web Impact Factor : un outil bibliométrique appliqué aux sites Web des facultés de médecine et des CHU français, Neuvièmes Journées Francophones d'Informatique Médicale. 6-7 mai 2002, Québec-Canada.
Kousha, K. & Thelwall, M. (2005). Motivations for linking to open access LIS library and information science articles: Exploring characteristics of sources of Web citation. ISSI 2005.
Thelwall, M. (2011). Investigating human communication and language from traces left on the web. In: Malcolm Williams, W Paul Vogt, (Eds), The SAGE Handbook of Innovation in Social Research Methods, London: Sage. (pp. 167-181). [This includes some small link diagrams for Alan Turing]
Thelwall, M. (2004). Hyperlink analysis, Encyclopedia of Virtual communities and Technologies, Idea Group Inc.
Park, H. & Thelwall, M. (2005). The network approach to web hyperlink research and its utility for science communication, In: Hine, C. (Ed.), Virtual Methods: Issues in Social Research on the Internet (chapter 13), London: Berg (pp. 171-181).
Wilkinson, D., Thelwall, M. & Li, X. (2003). Exploiting hyperlinks to study academic Web use. Social Science Computer Review, 21(3), 340-351.
Park, H. & Thelwall, M. (2003). Hyperlink analyses of the world wide web: A review. Journal of Computer-Mediated Communication. 8(4).
Thelwall, M. (2005). Scientific Web Intelligence: Finding relationships in university webs. Communications of the ACM, 48(7), 93-96.
Thelwall, M. (2004). Vocabulary Spectral Analysis as an exploratory tool for Scientific Web Intelligence. 8th International Conference on Information Visualisation (14-16 July 2004, London) In: Information Visualization (IV04), Los Alamitos, CA: IEEE, pp. 501-506.
Thelwall, M. (2005). Scientific Web Intelligence. In: Wang, J. (Ed.) Encyclopedia of Data warehousing and mining, Idea Group Inc.
Web Issue Analysis
Thelwall, M., Thelwall, S. & Fairclough, R. (2006). Automated web issue analysis: A nurse prescribing case study. Information Processing & Management (Informetrics special issue), 42(6), 1471-1483.
Wilkinson, D., & Thelwall, M. (2013). Search markets and search results: The case of Bing. Library and Information Science Research, 35(4), 318-325.10.1016/j.lisr.2013.04.006[(a) Webometric research can exploit search markets to get more search results, and (b) Bing results can vary substantially depending upon the location of the searcher.]
Thelwall, M. (2008). Extracting accurate and complete results from search engines: Case study Windows Live. Journal of the American Society for Information Science and Technology, 59(1), 38-50.
[The hit count estimates from search engines seem to estimate either (a) the total number of matches or (b) the number of matches after eliminating spam, same domain duplicates and near duplicates. This explains their variations in accuracy. This paper also introduces query splitting, an automatic variation of Judit Bar-Ilan's method to get extra matches for a query beyond those normally given by a search engine.]
Thelwall, M. (2000). Web Impact Factors and search engine coverage, Journal of Documentation, 56(2), 185-189.
Thelwall, M. (2001). A survey of search engine capabilities useful in data mining, Proceedings of the ASIST Annual Meeting Volume 38 (ASIST 2001) 24-30.
Thelwall, M. Binns, R. Harries, G. Page-Kennedy, T. Price E., & Wilkinson, D. (2001). Custom interfaces for advanced queries in search engines, ASLIB Proceedings, 53(10), 413-422. [Cited in Microsoft patent: US 7346613 B2]
Thelwall, M. (2005). Directing students to new information types: A new role for Google in literature searches?, Internet Reference Services Quarterly , 10(3/4), 159-166.
Cugelman, B., Thelwall, M., & Dawes, P. (2009). The dimensions of website credibility and their relation to active trust and behavioural impact, Communications of the Association for Information Systems, 24, 455-472.
Thelwall, M. (1999). Open Access Randomly Generated Tests: Assessment to Drive Learning, In Brown, S., Race, P. and Bull, J., Computer Assisted Assessment in Higher Education, London: Kogan Page. ISBN 0 7494 3035 4.
Thelwall, M. (1999), The Promotion of Understanding by the use of Open Access Computerised Assessment in Introductory Mathematics and Statistics Courses, Alt-C 99, University of Bristol, September 1999.
Thelwall, M. (1999), Randomly generated motivation from Maths and Stats Tests, Maths and Stats, 10(1), 13-16. (Magazine article)
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