Altmetrics, Social Media Indicators and Webometrics (Kousha metrics)

1. [All] Thelwall, M., Kousha, K., Abdoli, M., Stuart, E., Makita, M., Wilson, P. & Levitt, J. (2023). Do altmetric scores reflect article quality? Evidence from the UK Research Excellence Framework 2021. Journal of the Association for Information Science and Technology, 74(5), 582-593. https://doi.org/10.1002/asi.24751 [Compares altmetric scores with expert judgements of the quality of journal articles in all fields of science, mostly finding positive correlations.]
2. [Twitter] Htoo, T.H.H, Na, J.-C. & Thelwall, M. (2022). Why are medical research articles tweeted? The news value perspective Scientometrics. [Instead of news coverage attracting tweets or journalists noticing highly tweeted articles and writing about them, the results are consistent with newsworthy characteristics of articles attracting both tweets and news mentions.]
3. [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, 2(3), 864-881. [Summarises the types of websites used to evidence the non-academic impacts of UK research.]
4. [WorldCat] Torres-Salinas, D., Arroyo-Machado, W. & Thelwall, M. (2021). Exploring WorldCat Identities as an altmetric information source: A library catalog analysis experiment in the field of Scientometrics. Scientometrics, https://doi.org/10.1007/s11192-020-03814-w [WorldCat Identities can be a useful tool for researcher-level book impact assessment but it is undermined by massive ebooks library deals.]
5. [Mendeley] Thelwall, M. (2020). Coronavirus research before 2020 is more relevant than ever, especially when interpreted for COVID-19. Quantitative Science Studies. [Research about human coronaviruses attracted new citations more rapidly during COVID-19 than before, but articles translating it for COVID-19 in early 2020 were even more rapidly cited.]
6. [All] Thelwall, M. (2020). Measuring societal impacts of research with altmetrics? Common problems and mistakes. Journal of Economic Surveys. [Identifies problems to avoid with altmetrics studies.]
7. [All] Thelwall, M. (2020). The pros and cons of the use of altmetrics in research assessment. Scholarly Assessment Reports, 2(1), 2. [Summarises the advantages and disadvantages of altmetrics for research assessment, including advice for practice.]
8. [Mendeley, Facebook, News, Reddit, Tweets]Kousha, K. & Thelwall, M. (2020). COVID-19 publications: Database coverage, citations, readers, tweets, news, Facebook walls, Reddit posts. Quantitative Science Studies, 1(3), 1068-1091. [Covid publishing and citing is increasing rapidly; Tweeter counts are effective on the day of publication at indicating likely important articles - Mendeley reader counts are better after three weeks.]
9. [Mendeley]Kousha, K., Thelwall, M. (2020). Google Books, Scopus, Microsoft Academic and Mendeley for impact assessment of doctoral dissertations: A multidisciplinary analysis of the UK. Quantitative Science Studies, 1(2), 479–504, Advance Publication. https://10.1162/qss_a_00042 [Systematic methods introduced to extract citations to dissertations for Google Books, Scopus, Microsoft Academic, and Mendeley; Disciplinary differences in the citing rate of dissertations and the best source for dissertation citations.]
10. [Facebook] Mohammadi, E., Gregory, K., Thelwall, M., Barahmand, N. (2020). Which health and biomedical topics generate the most Facebook interest and the strongest citation relationships? Information Processing and Management, 57(3). [Publisher version]. [Identifies biomedical areas attracting more Facebook interest and with stronger relationships between Facebook and citation counts.]
11. [Facebook] Mohammadi, E., Barahmand, N., & Thelwall, M. (2019). Who shares health and medical scholarly articles on Facebook? Learned Publishing, 33(1), 111–118. [A small minority of Facebook posting about biomedical research is by academics.]
12. [Mendeley] Thelwall, M. (2020). Mendeley reader counts for US computer science conference papers and journal articles. Quantitative Science Studies, 1(1), 347–359. [Mendeley reader counts have a substantial advantage over citation counts as ain impact indicator for recently-published conference papers due to their greater speed.]
13. [News] Kousha, K. & Thelwall, M. (2019). An automatic method to identify citations to journals in news stories: A case study of the UK newspapers citing Web of Science journals, Journal of Data and Information Science, 4(3), 73-95. [Introduces a program to process ProQuest news articles and find citations to journals; assesses which journals are cited by the UK press.]
14. [Mendeley] Kousha, K. & Thelwall, M. (2019). Can Google Scholar and Mendeley help to assess the scholarly impacts of dissertations? Journal of Informetrics, 13(3), 467-484. [publisher version] [Google Scholar queries and Mendeley reader count can be used to systematically identify citation data for large numbers of dissertations for research evaluation purposes.]
15. [Syllabi] Mas Bleda, A. & Thelwall, M. (2018). Assessing the teaching value of non-English academic books: The case of Spain. Revista Española de Documentación Científica, 41(4), e222. [Online syllabus mentions can help to assess the teaching value of Spanish-language books, but manual checks are necessary if assessing individual books.]
16. [Mendeley] Thelwall, M. (2018). Does female-authored research have more educational impact than male-authored research? Journal of Altmetrics. 1(1), p.3. [local copy][Female first-authored articles attract more student Mendeley readers than male-authored articles in Spain, Turkey, the UK and USA but not India.] [Nature Career brief about this][THES article] [Nature Index article]
17. [All] Thelwall, M. (2018). Altmetric prevalence in the social sciences, arts and humanities: Where are the online discussions? Journal of Altmetrics, 1(1), p.4. [There is surprisingly little social web discussion about arts and humanities journal articles.]
18. [ResearchGate] Lepori, B., Thelwall, M. & Hoorani, B. H. (2018). Which US and European higher education institutions are visible in ResearchGate and what affects their RG Score? Journal of Informetrics, 12(3), 806-818. [publisher version] [Institutional ResearchGate scores reflect research volume rather than research visibility.]
19. [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.]
20. [Mendeley]Thelwall, M. (2018). Early Mendeley readers correlate with later citation counts. Scientometrics, 115(3), 1231–1240. [publisher full text view only] [Mendeley reader counts within a month of publication correlate significantly with citation counts 20 months later in 10 fields, so it is reasonable to use early reader counts as evidence of likely long term citation impact.]
21. [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.]
22. [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.]
23. [Mendeley] Thelwall, M. (2018). Differences between journals and years in the proportions of students, researchers and faculty registering Mendeley articles. [read-only publisher version] Scientometrics, 115(2), 717-729. doi:10.1007/s11192-018-2689-7 [There are substantial differences between journals in the proportions of different types of reader in Mendeley, so Mendeley reader counts for different journals and fields represent different reader demographics. There are also substantial differences between journals in similar areas for the rate at which Mendeley readers accumulate.]
24. [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.]
25. [Mendeley] Thelwall, M. (2019).  Do Mendeley reader counts indicate the value of arts and humanities research?  Journal of Librarianship & Information Science, 51(3), 781-788. [Mendeley readership counts reflect Scopus citation counts in the arts and humanities as strongly as in other areas of scholarship.]
26. [Mendeley] Thelwall, M. (2017). Are Mendeley reader counts high enough for research evaluations when articles are published? Aslib Journal of Information Management, 69(2), 174-183. doi:10.1108/AJIM-01-2017-0028 [Articles in 10 disciplines attracted 0.1 to 0.8 Mendeley readers per article in the month in which they first appeared in Scopus. This is about ten times more than the average Scopus citation count.]
27. [Mendeley] Maflahi, N, & Thelwall, M. (2018). How quickly do publications get read? The evolution of Mendeley reader counts for new articles. Journal of the Association for Information Science and Technology,69(1), 158–167. doi:10.1002/asi.23909 [Articles may have substantial numbers of readers by their publication date, making reader counts useful for immediate impact assessment. This depends on the length of the journal's publication backlog.]
28. [ResearchGate] Thelwall, M., & Kousha, K. (2017). ResearchGate versus Google Scholar: Which finds more early citations? Scientometrics, 112(2), 1125-1131. doi:10.1007/s11192-017-2400-4 [ResearchGate index more early citations than Scopus and the Web of Science but less than Google Scholar.]
29. [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.
30. [Mendeley] Aduku, J., Thelwall, M. & Kousha, K. (2017). Do Mendeley reader counts reflect the scholarly impact of conference papers? An investigation of Computer Science and Engineering. Scientometrics, 112(1), 573-581. doi:10.1007/s11192-017-2367-1 [Mendeley reader counts are more useful for computing types of engineering than for building and manufacturing engineering, in terms of conference papers.]
31. [Drug guidelines] Thelwall, M., Kousha, K. & Abdoli, M. (2017). Is medical research informing professional practice more highly cited? Evidence from AHFS DI Essentials in Drugs.com. Scientometrics, 112(1), 509-527. doi:10.1007/s11192-017-2292-3 [It is possible to systematically harvest citations to academic research from the drug guidelines. Papers in guidelines reference lists tend to be more highly cited than average for the publishing journal.]
32. [Mendeley] Thelwall, M. (2017). Does Mendeley provide evidence of the educational value of journal articles? Learned Publishing, 30(2), 107-113. doi:10.1002/leap.1076. [Mendeley student reader counts are broadly in line with Mendeley researcher reader counts for most subject areas except maths, where undergraduates avoid most papers.]
33. [All] Thelwall, M. (2017). Three practical field normalised alternative indicator formulae for research evaluation.  Journal of Informetrics, 11(1), 128–151. 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.] [EMNPC worked examples; MNLCS worked examples]
34. [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.]
35. [All] Thelwall, M. (2017). Web indicators for research evaluation: A practical guide. San Rafael, CA: Morgan & Claypool. [Book: Gives an overview of all the steps needed from data collection to analysis and interpretation for web indicators, including practical advice.]
36. [SlideShare] Thelwall, M. & Kousha, K. (2017). SlideShare presentations, citations, users and trends: A professional site with academic and educational uses. Journal of the Association for Information Science and Technology, 68(8), 1989-2003. [SlideShare is a presentation-centred site with a predominantly professional user base that is a useful source of non-academic information for scholars and students.]
37. [Patent citations, online presentation mentions, online course syllabus mentions, Wikipedia mentions, Mendeley reader counts, Altmetric.com data] Mas-Bleda, A. & Thelwall, M. (2016). Can alternative indicators overcome language biases in citation counts? A comparison of Spanish and UK research. Scientometrics, 109(3), 2007-2030. doi:10.1007/s11192-016-2118-8 [General web and social web indicators increase the apparent bias of indicators against Spanish research in comparison to the UK, probably due to lower social web uptake in Spain.]
38. [Clinical trials] Thelwall, M. & Kousha, K. (2016). Are citations from clinical trials evidence of higher impact research? An analysis of ClinicalTrials.gov. Scientometrics, 109(2), 1341-1351. doi:10.1007/s11192-016-2112-1 [Citations can be gathered from online clinical trials records and used as a health impact indicator.]
39. [All] Thelwall, M. (2016). Interpreting correlations between citation counts and other indicators. Scientometrics, 108(1), 337-347. doi:10.1007/s11192-016-1973-7 [The magnitude of correlations between citation counts and other indicators depends on the average citation counts and average indicator values as well as the underlying association between them, so correlations for different data sets are often not comparable.] R code and results. [Read-only publisher version]
40. [All] Thelwall, M. (2016). Data science altmetrics. Journal of Data and Information Science, 1(2), 7-12. doi:10.20309/jdis.201610. [Discusses altmetrics from a big data perspective.]
41. [Google Code software] Thelwall, M. & Kousha, K. (2016). Academic software downloads from Google Code: Useful usage indicators? Information Research. 21(1), paper 709.  [Download counts can be a useful indicator of the wider uptake of academic software.]
42. [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.]
43. [Wikipedia] Kousha, K. & Thelwall, M. (2017). Are Wikipedia citations important evidence of the impact of scholarly articles and books? Journal of the Association for Information Science and Technology, 68(3), 762-779. doi:10.1002/asi.23694 [Citations from Wikipedia are frequent enough to be useful impact indicators for books in the humanities.]
44. [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.]
45. [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.]
46. [Web citations and links] Thelwall, M., & Kousha, K. (2015). Web indicators for research evaluation, part 1: Citations and links to academic articles from the web. El Profesional de la Información, 24(5), 587-606. doi:10.3145/epi.2015.sep.08 [Reviews research into generating academic indicators from the web.]
47. [All social media] Thelwall, M., & Kousha, K. (2015). Web indicators for research evaluation, part 2: Social media metrics. El Profesional de la Información, 24(5), 607-620. doi:10.3145/epi.2015.sep.09 [Reviews research into generating academic indicators from social media.]
48. [All social media] Kousha, K. & Thelwall, M. (2015). Web indicators for research evaluation, part 3: Books and non-standard outputs. El Profesional de la Información, 24(6), 724-736. doi:10.3145/epi.2015.nov.04 [Reviews research into generating academic indicators for books and other non-standard research outputs from the web.]
49. [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.]
50. [Mendeley] Thelwall, M. (2017). Why do papers have many Mendeley readers but few Scopus-indexed citations and vice versa? Journal of Librarianship & Information Science, 49(2), 144-151. doi:10.1177/0961000615594867 [A list of reasons why articles can have many Mendeley readers but few Scopus-indexed citations and vice versa.]
51. [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.]
52. [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.]
53. [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.]
54. [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.]
55. [Mendeley] Thelwall, M. & Maflahi, N. (2016). Guideline references and academic citations as evidence of the clinical value of health research. Journal of the Association for Information Science and Technology, 67(4), 960-966. doi:10.1002/asi.23432. [Articles cited in UK Clinical Knowledge Summaries are more highly cited and more highly read in Mendeley than comparable articles and so such articles make a contribution to both knowledge and practice.]
56. [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.]
57. [Mendeley] Maflahi, N. & Thelwall, M. (2016). When are readership counts as useful as citation counts? Scopus vs. Mendeley for LIS journals. Journal of the Association for Information Science and Technology, 67(1), 191-199. [Based upon four key LIS journals, finds that Mendeley reader counts are reasonable proxies for citation counts for articles that are 1-10 years old.]
58. [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.]
59. [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.]
60. [Mendeley] Thelwall, M. & Maflahi, N. (2015). Are scholarly articles disproportionately read in their own country? An analysis of Mendeley readers. Journal of the American Society for Information Science and Technology, 66(6), 1124–1135. doi:10.1002/asi.23252 [Articles tend to be read more in a country if some of the authors are from that country.]
61. [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.].
62. [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.]
63. [Twitter] Holmberg, K. & Thelwall, M. (2014). Disciplinary differences in Twitter scholarly communication, Scientometrics, 101(2), 1027-1042. [Shows that the extent to which researchers use Twitter for conversations, information sharing and research-relevant topics varies by discipline.]
64. [All altmetrics] Sud, P. & Thelwall, M. (2014). Evaluating altmetrics. Scientometrics, 98(2),1131-1143.[Summarises methods to evaluate altmetrics and recommends evaluation strategies.]
65. [Twitter] Thelwall, M. Tsou, A., Weingart, S., Holmberg, K., & Haustein, S. (2013). Tweeting links to academic articles, Cybermetrics, 17(1).
66. [Mendeley] Mohammadi, E. & Thelwall, M. (2014). Mendeley readership altmetrics for the social sciences and humanities: Research evaluation and knowledge flows. Journal of the American Society for Information Science and Technology 65(8), 1627-1638.[Shows that Mendeley readership data can give evidence of knowledge transfer between disciplines.]
67. [Grey literature] Wilkinson, D., Sud, P., & Thelwall, M. (2014). Substance without citation: Evaluating the online impact of grey literature. Scientometrics, 98(2), 797-806. [publisher version]
68. [Blogs] Shema, H., Bar-Ilan, J., & Thelwall, M. (2014). Do blog citations correlate with a higher number of future citations? Research blogs as a potential source for alternative metrics. Journal of the American Society for Information Science and Technology, 65(5), 1018–1027.[Shows that blog citations can be used to predict future scholarly citations.]
69. [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
70. [F1000] Mohammadi, E., & Thelwall, M.(2013). Assessing non-standard article impact using F1000 labels. Scientometrics, 97(2), 383-395.
71. [Web] Eccles, K.E., Thelwall, M., & Meyer, E.T. (2012). Measuring the web impact of digitised scholarly resources. Journal of Documentation, 68(4), 512-526.
72. [Blogs] Shema, H., Bar-Ilan, J., & Thelwall, M. (2012). Research blogs and the discussion of scholarly information. PLoS ONE, 7(5): e35869.
73. [YouTube views] Kousha, K., Thelwall, & Abdoli, M. (2012). The role of online videos in research communication: A content analysis of YouTube videos cited in academic publications. Journal of the American Society for Information Science and Technology, 63(9), 1710–1727.
74. [CiteULike, Mendeley] Li, X., Thelwall, M., & Giustini, D. (2012). Validating online reference managers for scholarly impact measurement, Scientometrics, 91(2), 461-471.
75. [Any altmetric]Thelwall, M. (2012). Journal impact evaluation: A webometric perspective, Scientometrics, 92(2), 429-441.
76. [F1000, Mendeley] Li, X., & Thelwall, M. (2012). F1000, Mendeley and traditional bibliometric indicators. 17th International Conference on Science and Technology Indicators (Vol. 3, pp. 1–11).
77. [Image copies] Kousha, K. & Thelwall, M. & Rezaie, S. (2010). Can the impact of scholarly images be assessed online?  An exploratory study using image identification technology, Journal of the American Society for Information Science and Technology, 61(9), 1734–1744.
78. [Google Scholar, Google Books, Google Blogs, PowerPoint, course reading lists] Kousha, K., Thelwall, M. & Rezaie, S. (2010). Using the Web for research evaluation: The Integrated Online Impact indicator, Journal of Informetrics, 4(1), 124-135.
79. [Web syllabuses] Kousha, K. & Thelwall, M. (2008). Assessing the impact of disciplinary research on teaching:  An automatic analysis of online syllabuses, Journal of the American Society for Information Science and Technology, 59(13), 2060-2069.
80. [PowerPoint] Thelwall, M. & Kousha, K. (2008). Online presentations as a source of scientific impact?: An analysis of PowerPoint files citing academic journals. Journal of the American Society for Information Science and Technology, 59(5), 805 – 815.
81. [Web] Kousha, K. & Thelwall, M. (2007). The web impact of open access social science research. Library and Information Science Research, 29(4), 495-507
82. [Google Scholar] Kousha, K. & Thelwall, M. (2008). Sources of Google Scholar citations outside the Science Citation Index: A comparison between four science disciplines. Scientometrics, 74(2), 273-294.
83. [Web] Kousha, K. & Thelwall, M. (2007). How is science cited on the web? A classification of Google unique web citations. Journal of the American Society for Information Science and Technology, 58(11), 1631-1644.
84. [Web citations, Web/URL citations] Kousha, K. & Thelwall, M. (2007). Google Scholar citations and Google Web/URL citations: A multi-discipline exploratory analysis, Journal of the American Society for Information Science and Technology, 57(6), 1055-1065.
85. [Web citations, URL citations] Kousha, K. & Thelwall, M. (2006). Motivations for URL citations to open access LIS library and information science articles. Scientometrics , 68(3), 501-517.

Book Citation Analysis

1. Kousha, K., Thelwall, M. (2020). Google Books, Scopus, Microsoft Academic and Mendeley for impact assessment of doctoral dissertations: A multidisciplinary analysis of the UK. Quantitative Science Studies. Advance Publication. https://10.1162/qss_a_00042 [Systematic methods introduced to extract citations to dissertations for Google Books, Scopus, Microsoft Academic, and Mendeley; Disciplinary differences in the citing rate of dissertations and the best source for dissertation citations.]
2. Kousha, K. & Thelwall, M. (2018). Can Microsoft Academic help to assess the citation impact of academic books? Journal of Informetrics,12(3), 972-984. [Automatic Microsoft Academic queries find more citations to books than the Web of Science Book Citation Index.]
3. Kousha, K., Thelwall, M. & Abdoli, M. (2017). Goodreads reviews to assess the wider impacts of books. Journal of the Association for Information Science and Technology, 68(8), 2004-2016. [Most arts, humanities and social sciences scholarly books in Scopus have at least one Goodreads review - counting Goodreads reviews gives a new impact indicator.]Kousha, K. & Thelwall, M. (2016). An automatic method for assessing the teaching impact of books from online academic syllabi. Journal of the Association for Information Science and Technology, 67(12), 2993-3007. [Citations from online academic syllabi are a practical source of evidence for the educational impact of books.]
4. Thelwall, M. & Sud, P. (2014). No citation advantage for monograph-based collaborations? Journal of Informetrics, 8(1), 276-283.[Solo monographs tend to be as highly cited as co-authored monographs, unlike the case of articles.]
5. 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.]
6. Abdullah, A. & Thelwall, M. (2014). Can the impact of non-Western academic books be measured? An investigation of Google Books and Google Scholar for Malaysia. Journal of the American Society for Information Science and Technology, 65(12), 2498–2508. 10.1002/asi.23145. [Citations from Google Books can be found for the monographs and edited volumes of at least one non-Western nation.]
7. Kousha, K., Thelwall, & Rezaie, S. (2011). Assessing the citation impact of books: The role of Google Books, Google Scholar and Scopus. Journal of the American Society for Information Science and Technology, 62(11) 2147–2164.
8. Kousha, K. & Thelwall, M. (2009). Google Book Search: Citation analysis for social science and the humanities, Journal of the American Society for Information Science and Technology, 60(8), 1537-1549.

Gender and sexuality in academic research (bibliometric studies)

1. Thelwall, M.  Devonport, T.J., Makita, M, Russell, K. & Ferguson, L. (2023). Academic LGBTQ+ terminology 1900-2021: Increasing variety, increasing inclusivity? Journal of Homosexuality, 70(11), 2514-2538. https://doi.org/10.1080/00918369.2022.2070446 [The LGBTQ+ related journal articles have almost continually increased in prevalence since 1900. Many different terminologies have emerged with activist, health professional and academic origins, but none currently dominate.]
2. Thelwall, M. Abdullah, A, & Fairclough, R. (2022). Researching women and men 1996-2020: Is androcentrism still dominant? Quantitative Science Studies, 3(1), 244-264. [The proportion of research about women has steadily increased in recent decades, with more research now about women than about men.]
3. Thelwall, M. & Mas-Bleda, A. (2020). A gender equality paradox in academic publishing: Countries with a higher proportion of female first-authored journal articles have larger first author gender disparities between fields. Quantitative Science Studies, 1(3), 1260-1282. [Differences between fields in the proportion of female first authors are greater in countries with more female first authors, suggesting that increased overall gender equality does not lessen gender disparities in all fields, and may even strengthen gender disparities in some fields, such as maths. A possible cause is increased pressure for gender conformity in life choices in more gender-equal societies. This suggests that systemic interventions may be necessary to overcome female minorities in some STEM fields.]
4. Thelwall, M., Abdoli, M., Lebiedziewicz, A. & Bailey, C. (2020). Gender disparities in UK research publishing: Differences between fields, methods and topics. El Profesional de la Información, 29(4), e290415. [Gender differences in research publishing topics and methods in the UK match the people/things and communal/agentic goals theories.]
5. 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.]
6. Thelwall, M. & Sud, P. (2020). Greater female first author citation advantages do not associate with reduced or reducing gender disparities in academia. Quantitative Science Studies, 1(3), 1283-1297. [A weak tendency in the USA and New Zealand for female citation advantages to be stronger in fields with fewer women, but no other association evidence. No evidence of female citation advantages or disadvantages to be a cause or effect of changes in the proportions of women in a field for any country. Inappropriate uses of career-level citations are a likelier source of gender inequities.]
7. Thelwall, M. (2020). Gender differences in citation impact for 27 fields and 6 English speaking countries 1996-2014. Quantitative Science Studies, 1(2), 599–617. [There is an overall female first author citation advantage first-authored research for 27 broad fields and 6 large English-speaking countries (Australia, Canada, Ireland, New Zealand, UK and USA) 1996-2014, but reversed in most broad fields in all countries for some years.]
8. Thelwall, M. (2020). Author gender differences in psychology citation impact 1996-2018. International Journal of Psychology, 55(4), 684–694. [Female first-authored research tends to be more common and more more cited in US psychology research than US first-authored research, and females tend to work in larger teams.]
9. Thelwall, M. (2020). Female citation impact superiority 1996-2018 in six out of seven English-speaking nations. Journal of the Association for Information Science and Technology, 71(8), 979–990. DOI: 10.1002/asi.24316 [Female first-authored research tends to be more cited in Australia, Canada, Ireland, Jamaica, New Zealand, UK but not the USA, although differences in all cases are small.]
10. Thelwall, M., Bailey, C., Makita, M., Sud, P. & Madalli, D. (2019). Gender and Research Publishing in India: Uniformly high inequality? Journal of Informetrics, 13(1), 118–131. [Female participation rates and gender differences between fields participation rates are lower in India than in the USA, and some fields have radically different gender shares.] [Local copy][The Wire article] [Hindu Business Online]
11. Thelwall, M., Bailey, C., Tobin, C. & Bradshaw, N. (2019). Gender differences in research areas, methods and topics: Can people and thing orientations explain the results? Journal of Informetrics, 13(1), 149-169. [There are substantial gender differences (up to a factor of 100) in the research fields, methods and topics of articles published by US academics in 2017; these cannot be fully explained by the people/thing theory of social psychology.] [local copy]
12. Thelwall, M. (2018). Do gendered citation advantages influence field participation? Four unusual fields in the USA 1996-2017. Scientometrics,117(3), 2133-2144. https://doi.org/10.1007/s11192-018-2926-0 [Differing rates of citing male and female first-authored research do not associate with long term changes in the gender composition of a field.]
13. Thelwall, M. (2018). Do females create higher impact research? Scopus citations and Mendeley readers for articles from five countries. Journal of Informetrics, 12(4), 1031-1041. https://doi.org/10.1016/j.joi.2018.08.005 [publisher version] [Nature Index article about this paper] [Female first-authored research tends to have slightly higher average citation impact in Spain, the UK and the USA, and more Mendeley readers in Spain, Turkey, the UK and the USA, but not India. At a technical level, gender comparison results depend on the field normalisation method used, and all previous analyses have arguable allowed highly cited articles to be too influential in calculations.]

Data sharing

1. Khan, N., Thelwall, M. & Kousha, K. (2023). Data sharing and reuse practices: Disciplinary differences and improvements needed. Online Information Review. https://doi.org/10.1108/OIR-08-2021-0423 [Iincludes 23 recommendations to promote data sharing and reuse, including improved data access and usability, formal data citations, new search features and cultural and policy-related disciplinary changes to increase awareness and acceptance.]
2. Khan, N., Thelwall, M., & Kousha, K. (2021). Are data repositories fettered? A survey of current practices, challenges, and future technologies. Online Information Review. https://doi.org/10.1108/OIR-04-2021-0204 [Identifies the current challenges and needs for improving data repository functionalities and user experiences.]
3. Thelwall, M. (2020). Data in Brief: Can a mega-journal for data be useful? Scientometrics, 124(1), 697-709. [Data in Brief papers usually attract attention but only about 1% lead to data reuse.]
4. Khan, N., Pink, C., & Thelwall, M. (2020). Identifying data sharing and reuse with Scholix – Potentials and limitations. Patterns, 1, 100007. [The Scholarly Link Exchange is able to identify data reuse, even though few papers follow standard data citation practices.]
5. Thelwall, M. Munafò, M., Mas-Bleda, A., Stuart, E., Makita, M., Weigert, V., Khan, N., Drax, K. & Kousha, K. (2020). Is useful research data usually shared? An investigation of genome-wide association study summary statistics. Plos One. [Even in an area where data sharing is mandated by funders and specialised repositories exist, a key data type is rarely shared, and sharing statements are rarely explicit enough to detect it.]
6. Thelwall, M. & Kousha, K. (2017). Do journal data sharing mandates work? Life sciences evidence from Dryad. Aslib Journal of Information Management, 69(1), 36-45.  doi:10.1108/AJIM-09-2016-0159 [All relevant articles share data in some life sciences journals, and the data does seem to be used, but it is not clear what it is used for.]

Peer review

1. Kousha, K. & Thelwall, M. (2024). Artificial intelligence to support publishing and peer review: A summary and review. Learned Publishing. https://doi.org/10.1002/leap.1570 [AI can support publishing and peer review but can't make publishing judgements.]
2. Thelwall, M. & Holyst, J. (in press). Can journal reviewers dependably assess rigour, significance, and originality in theoretical papers? Evidence from physics. Research Evaluation. https://doi.org/10.1093/reseval/rvad018 [There is only moderate agreement between reviewers on the core aspects of scientific quality, including rigour, in a nearly ideal case. This is concerning for the security of the wider academic record.]
3. Kousha, K., & Thelwall, M. (2022). Covid-19 refereeing duration and impact in major medical journals. Quantitative Science Studies, 3(1), 1-17. [Refereeing for Covid-related journal articles was quicker, but apparently without compromising quality.]
4. Thelwall, M. (in press). Journal and disciplinary variations in academic open peer review anonymity, outcomes, and length. Journal of Librarianship & Information Science. [For one publisher, there are disciplinary differences in the length, format and strictness of pre-publication reviews. Signed reviews tend to be longer than anonymous reviews but give similar decisions.]
5. Thelwall, M., Allen, L. Papas, E., Nyakoojo, Z., & Weigert, V. (2021). Does the use of open, non-anonymous peer review in scholarly publishing introduce bias? Evidence from the F1000Research post-publication open peer review publishing model. Journal of Information Science, 47(6), 809-820. https://doi.org/10.1177/0165551520938678 [Weak evidence that being based in the same country as an author may influence a reviewer’s decision when their identity and review are public, but being able to read an existing published review prior to submitting a new review does not seem to encourage conformity.]
6. Thelwall, M., Papas, E., Nyakoojo, Z., Allen, L. & Weigert, V. (2020). Automatically detecting open academic review praise and criticism. Online Information Review, 44(5), 1057-1076. [Introduces and validates a transparent program, PeerJudge to detect praise and criticism in open academic peer review reports.] PeerJudge website.
7. Thelwall, M. (2019). Changes in new versions of papers published on F1000Research. F1000Research (non-peer reviewed poster). [Updates to articles on F1000Research tend to involve lengthening the Supplementary Materials,  Data Availability statement, Discussions and Conclusions.]

Academic writing and research design

1. Thelwall, M. (2020). Pot, kettle: Nonliteral titles aren't (natural) science. Quantitative Science Studies. [Humourous or other non-literal titles are relatively rare in the natural sciences compared to other areas of academia and so should be used cautiously in fields where they may be unexpected.] THE article about this paper.
2. 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.]
3. Thelwall, M. (2019). Are classic references cited first? An analysis of citation order within article sections. Scientometrics, 120(2), 723-731. [Initial citations in the Introduction, Background, Discussion and Conclusions may have a general agenda setting nature in many fields because they tend to be more highly cited, but may play little direct role in the new publication.] [view-only publisher version]
4. Thelwall, M. (2019). The rhetorical structure of science? A multidisciplinary analysis of article headings. Journal of Informetrics. 13(3), 555–563. [There seems to be little common structure to scientific articles: no article headings are close to ubiquitous in any broad field and there are substantial field differences in the extent to which most headings are used.]
5. Thelwall, M. & Sud, P. (2018). A comparison of title words for journal articles and Wikipedia pages: Coverage and stylistic differences? El Profesional de la Información, 27(1), 49-64. doi:10.3145/epi.2018.ene.05 [Wikipedia is broadly effective at covering even specialist academic topics, but with stylistic differences.][local copy]
6. Thelwall, M. & Maflahi, N. (2015). How important is computing technology for library and information science research? Library and Information Science Research, 37(1), 42–50. [About two thirds of library and information science articles explicitly mention an aspect of computing in their title, keywords or abstract, showing the widespread importance of computing technology to the discipline.]
7. Thelwall, M. (2017). Avoiding obscure topics and generalising findings produces higher impact research. Scientometrics, 110(1), 307-320. doi:10.1007/s11192-016-2159-z [Research with unusual words in article titles tends to be less cited than average; titles covering multiple concepts and suggesting a purpose may be more cited.]

Academic Collaboration

1. Thelwall, M., Kousha, K., Abdoli, M., Stuart, E., Makita, M., Wilson, P. & Levitt, J. (in press). Why are co-authored academic articles more cited: Higher quality or larger audience? Journal of the Association for Information Science and Technology, 74(7), 791-810. https://doi.org/10.1002/asi.24755 [There are moderately strong positive associations (0.2–0.4) between author numbers and quality scores in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities. Audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields.]
2. Thelwall, M. (2023). Are successful co-authors more important than first authors for publishing academic journal articles? Scientometrics, 128(4), 2211-2232. https://doi.org/10.1007/s11192-023-04663-z [High impact first authors or team members associate with higher impact journal publishing, but more productive first authors and teamd have weaker associations, with low publishing first authors being a slight advantage in some physical and life sciences.]
3. Thelwall, M., Kousha, K., Abdoli, M., Stuart, E., Makita, M., Wilson, P. & Levitt, J. (2023). Is big team research fair in national research assessments? The case of the UK Research Excellence Framework 2021. Journal of Data and Information Science, 8(1), 9-20. https://doi.org/10.2478/jdis-2023-0004 [Over-weighting (i.e., full rather than fractional counting) individual contributions to collaboratively authored outputs affected the scores of archeology and physics departments most in the UK REF2021, suggesting that its implications should be seriously considered in these fields.]
4. Thelwall, M. & Maflahi, N. (2020). Academic collaboration rates and citation associations vary substantially between countries and fields. Journal of the Association for Information Science and Technology, 71(8), 968–978. Doi:10.1002/asi.24315 [There are field and international differences in whether articles with more authors attract more citations. Solo research from India and China has relatively high citation counts.]
5. Thelwall, M. (2020). Large publishing consortia produce higher citation impact research but co-author contributions are hard to evaluate. Quantitative Science Studies, 1(1), 290–302. [Consortia of many authors publishing multiple articles tend to publish research with substantially above the average citation impact, but author contributions are often difficult to detect.]
6. Levitt, J. & Thelwall, M. (2016). Long term productivity and collaboration in information science. Scientometrics, 108(3), 1103-1117. doi:10.1007/s11192-016-2061-8 [The long term productivity of information scientists seems to be highest if they tend to work alone or collaborate with one other author.]
7. Sud, P. & Thelwall, M. (2016). Not all international collaboration is beneficial: The Mendeley readership and citation impact of biochemical research collaboration.  Journal of the Association for Information Science and Technology, 67(8), 1849-1857. doi:10.1002/asi.2351 [Although the benefits of international collaboration seem to be an accepted truth throughout science, this article suggests that collaboration with some countries may not be beneficial, at least at a statistical level.]
8. Didegah, F., & Thelwall, M. (2013). Which factors help authors produce the highest impact research? Collaboration, journal and document properties. Journal of Informetrics, 7(4), 861-873
9. Levitt, J., & Thelwall, M. (2010). Does the higher citation of collaborative research differ from region to region? A case study of economics, Scientometrics, 85(1), 171-183.
10. Levitt, J., & Thelwall, M. (2009). Citation levels and collaboration within Library and Information Science, Journal of the American Society for Information Science and Technology, 60(3), 434-442.

Bibliometrics and Scientometrics (excluding gender, data, collaboration, altmetrics)

1. Thelwall, M. & Pinfield, S. (2024). The accuracy of field classifications for journals in Scopus. Scientometrics.[There are large field differences in the extent to which cross-field and specialist journals publish articles that match their Scopus narrow fields.]
2. Thelwall, M. & Kousha, K. (in press). Technology assisted research assessment: Algorithmic bias and transparency issues. Aslib Journal of Information Management. https://doi.org/10.1108/AJIM-04-2023-0119 [A literature review.] T
3. Thelwall, M., Simrick, S., Viney, I. & Van den Besselaar, P. (in press). What is research funding, how does it influence research, and how is it recorded? Key dimensions of variation. Scientometrics. https://doi.org/10.1007/s11192-023-04836-w [A discussion of research funding dimensions.]
4. Kousha, K. & Thelwall, M. (in press). Factors associating with or predicting more cited or higher quality journal articles. Annual Review of Information Science and Technology. https://doi.org/10.1002/asi.24810 [A review of article and other properties that associate with or predict higher quality or more cited journal articles.]
5. Thelwall, M., Kousha, K., Stuart, E., Makita, M., Abdoli, M., Wilson, P. & Levitt, J. (2023). Do bibliometrics introduce gender, institutional or interdisciplinary biases into research evaluations? Research Policy, 52(8), 104829. https://doi.org/10.1016/j.respol.2023.104829 [The main bias found is against departments publishing higher quality research; there was also a minor male-favouring gender bias for bibliometrics compared to peer review.]
6. Thelwall, M., Kousha, K., Makita, M., Abdoli, M., Stuart, E., Wilson, P. & Levitt, J. (2023). In which fields do higher impact journals publish higher quality articles? Scientometrics, 128, 3915-3933. https://doi.org/10.1007/s11192-023-04735-0 [publisher view-only preprint] [Shows the extent to which journal impact associates with article research quality varies between fields and that high impact journals never only publish high quality articles.] PubPeer comments on the article with important additional caveats about the results.
7. Thelwall, M., Kousha, K., Stuart, E., Makita, M., Abdoli, M., Wilson, P. & Levitt, J. (2023). In which fields are citations indicators of research quality? Journal of the Association for Information Science and Technology? , 74(8), 941-953. https://doi.org/10.1002/asi.24767 [Identifies fields in which citation counts data can reasonably be used for research quality indicators but shows that there is no field with a citation threshold for that guarantees that a paper is the highest quality.]
8. Thelwall, M., Kousha, K., Wilson, P. Makita, M., Abdoli, M., Stuart, E., Levitt, J., Knoth, P., & Cancellieri, M. (in press). Predicting article quality scores with machine learning: The UK Research Excellence Framework. Quantitative Science Studies.https://doi.org/10.1162/qss_a_00258 [Introduces and assesses machine learning methods to assess the quality of academic research from metadata.]
9. Thelwall, M., Kousha, K., Abdoli, M., Stuart, E., Makita, M., Font-Julián, C. I., Wilson, P. & Levitt, J. (in press). Is research funding always beneficial? A cross-disciplinary analysis of UK research 2014-20. Quantitative Science Studies, 4(2), 501–534. https://doi.org/10.1162/qss_a_00254 [Funded research is likely to be higher quality overall, for all the largest research funders, and statistically signficantly for 30 out of 34 REF Units of Assessment (disciplines or sets of disciplines).]
10. Thelwall, M., Kousha, K., Stuart, E., Makita, M., Abdoli, M., Wilson, P. & Levitt, J. (2023). Does the perceived quality of interdisciplinary research vary between fields? Journal of Documentation, 79(6), 1514-1531. https://doi.org/10.1108/JD-01-2023-0012 [preprint] [There are some systematic differences between fields in the average scores given to interdisciplinary research.]
11. Thelwall, M., Kousha, K., Abdoli, M., Stuart, E., Makita, M., Wilson, P. & Levitt, J. (2023). Terms in journal articles associating with high quality: Can qualitative research be world-leading? Journal of Documentation, 79(5), 1110-1123. https://doi.org/10.1108/JD-12-2022-0261 [Identifies words associaing with higher or lower quality socres in REF2021, suggesting that associated topics and methods may receive higher or lower REF2021 scores.]
12. Thelwall, M., & Maflahi, N. (2022). Research Co-authorship 1900-2020: Continuous, universal, and ongoing expansion. Quantitative Science Studies. [The reasonably steady and universal (across all fields) increases in academic coauthorship over 121 years show no sign of slowing.]
13. Thelwall, M. (2022). Can the quality of published academic journal articles be assessed with machine learning? Quantitative Science Studies, 3(1), 208-226. [Assesses AI prediction strategies using journal thirds as a proxy for article quality. Prediction of article quality with high accuracy may be possible for a subset of articles in some fields; Text inputs are likely to reveal journal topics and styles, so it is impossible to avoid indirectly harnessing publication venue.]
14. Thelwall, M. & Sud, P. (2022). Scopus 1900-2020: Growth in articles, abstracts, countries, fields, and journals. Quantitative Science Studies, 3(1), 37-50. [Maps the growth of Scopus, including its abstracts, 1900-2020.]
15. Fairclough, R. & Thelwall, M. (in press). Questionnaires mentioned in academic research 1996-2019: Rapid increase but declining citation impact. Learned Publishing. [Questionnaires seem to be increasingly used in academic research, but may be losing their citation advantage.]
16. Li, X., Mohammadi, E., & Thelwall, M. (2021). How are encyclopedias cited in academic research? Wikipedia, Britannica, Baidu Baike, and Scholarpedia. Profesional de la Información. [Encyclopedias have minor value for academic research, often for background and definitions, with the most suitable one varying between fields and countries; the popularity of crowdsourced encyclopedias may be waning.]
17. Thelwall, M. & Thelwall, S. (2021). How has Covid-19 affected published academic research? A content analysis of journal articles mentioning the virus. Journal of Data and Information Science, 6(4), 1–12. https://doi.org/10.2478/jdis-2021-0030 [Two thirds of academic articles mentioning Covid-19 were related biomedicine or health services; most others covered the pandemic economy, society, safety, or education. Covid-19 had changed the value of other reported research or its context.]
18. Thelwall, M. (2021). Alternative medicines worth researching? Citation analyses of acupuncture, chiropractic, homeopathy, and osteopathy 1996-2017. Scientometrics, 126(10), 8731-8747. [local copy] https://doi.org/10.1007/s11192-021-04145-0 [A descriptive citation anlaysis of acupuncture, chiropractic, homeopathy, and osteopathy journal articles indexed in Scopus 1996–2020.]
19. Maflahi, N. & Thelwall, M. (2021). Domestic researchers with longer careers generate higher average citation impact but it does not increase over time. Quantitative Science Studies, 2(2), 560-587. [Citation impact seems to decrease at the end of careers, although longer-term researchers tend to have higher citation impact overall.]
20. Thelwall, M. & Nevill, T. (in press). Is research with qualitative data more prevalent and impactful now? Interviews, case studies, focus groups and ethnographies. [publisher version] Library & Information Science Research. https://doi.org/10.1016/j.lisr.2021.101094 [Qualitative data is increasingly used in academic research.]
21. Khan, N., Thelwall, M., & Kousha, K. (in press). Measuring the impact of biodiversity datasets: Data reuse, citations and altmetrics. Scientometrics. [Standard data citation practices are usually not followed when Global Biodiversity Information Facility (GBIF) datasets are reused.]
22. Thelwall, M. & Sud, P. (2021). Do new research issues attract more citations? A comparison between 25 Scopus subject categories. Journal of the Association for Information Science and Technology, 72(3), 269-279.[Academic fields evolve through topics, style, national focus and language; New topics are more cited in some fields but less cited in others.]
23. 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.]
24. 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.]
25. Thelwall, M. & Mas-Bleda, A. (in press). How does nursing research differ internationally? A bibliometric analysis of six countries. International Journal of Nursing Practice. [Nursing research is internationally fragmented by journal. Some aspects of nursing research are absent from some countries, such as papers about nursing administration and management.]
26. Thelwall, M. (2019). Should citations be counted separately from each originating section? Journal of Informetrics, 13(3), 658–678. [At a global scale, the standard section containing a citation (e.g., Introduction, Methods, Discussion) is not a reliable indicator of the reason why the article was cited.]
27. Thelwall, M. (2019). The influence of highly cited papers on field normalised indicators. Scientometrics, 118(2), 519–537. [Individual outliers can influence field normalised indicators enough to influence policy decisions based on them.]
28. Mas-Bleda, A. & Thelwall, M. (2018). Do prestigious Spanish scholarly book publishers have more teaching impact? Aslib Journal of Information Management, 70(6), 673-690. DOI: 10.1108/AJIM-04-2018-0094 [Prestigious publishers in Spain tend to publish books with higher teaching impact.]
29. Martín-Martín, A., Orduna-Malea, E., Thelwall, M. & Delgado, E. (2018). Google Scholar, Web of Science, and Scopus: a systematic comparison of citations in 252 subject categories. Journal of Informetrics, 12(4), 1160-1177. [publisher version] [Google Scholar finds nearly all WoS (95%) and Scopus (92%) citations. The extra citations were from non-journal sources (48%-65%). Many were non-English (19%-38%).]
30. Thelwall, M. (2018). Dimensions: A competitor to Scopus and the Web of Science? Journal of Informetrics, 12(2), 430–435. 10.1016/j.joi.2018.03.006. [The new scholarly database Dimensions has coverage and citation counts that are similar to Scopus but it is free for many purposes.]
31. Thelwall, M. (2018). Can Microsoft Academic be used for citation analysis of preprint archives? The case of the Social Science Research Network. Scientometrics, 115(2), 913-928. doi:10.1007/s11192-018-2704-z ][publisher read only version][Microsoft Academic has quite comprehensive coverage of preprint archives. It can be used for citation analyses of them in conjunction with a list of their publications from another source.]
32. Kousha, K, Thelwall, M. & Abdoli, M. (2018). Can Microsoft Academic assess the early citation impact of in-press articles? A multi-discipline exploratory analysis. Journal of Informetrics, 12(1), 287-298. [wire] [Microsoft Academic can find more citations to in press articles than Scopus and seems to be a better source of early impact evidence.]
33. Thelwall, M. (2018). Microsoft Academic automatic document searches: accuracy for journal articles and suitability for citation analysis. Journal of Informetrics, 12(1), 1-9. doi:10.1016/j.joi.2017.11.001 [Automatic Microsoft Academic journal article queries can find articles with a high level of accuracy in all fields and the resulting document set is equivalent to Scopus sets for citation analysis in most fields.]
34. Thelwall, M. (2017). Microsoft Academic: A multidisciplinary comparison of citation counts with Scopus and Mendeley for 29 journals. Journal of Informetrics.11(4), 1201-1212. doi:10.1016/j.joi.2017.10.006 [Microsoft Academic finds 6% more citations than Scopus (and 51% more for the current year, based on 29 large journals.]
35. Thelwall, M. (2017). Confidence intervals for normalised citation counts: Can they delimit underlying research capability? Journal of Informetrics, 11(4), 1069-1079. doi:10.1016/j.joi.2017.09.002 [local copy] [It is reasonable to use confidence intervals to estimate underlying research capability and prediction intervals to estimate future research output, although system changes over time mean that they should be used cautiously.]
36. 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.]
37. Thelwall, M. & Fairclough, R. (2017). The research production of nations and departments: A statistical model for the share of publications. Journal of Informetrics, 11(4), 1142-1157.doi:10.1016/j.joi.2017.10.001 [Modelling the share of the world's publications from a country or department to predict future production or estimate underlying research capacity.]
38. Thelwall, M. & Levitt, J.M.  (2018). National scientific performance evolution patterns: retrenchment, successful expansion, or overextension. Journal of the Association for Information Science and Technology, 69(5), 720-727. doi:10.1002/asi.23969 [There is a negative correlation between expansion and relative citation impact but their relationship varies by country.]
39. Thelwall, M. & Fairclough, R. (2017). The accuracy of confidence intervals for field normalised indicators. Journal of Informetrics, 11(2), 530-540. doi:10.1016/j.joi.2017.03.004 [The MNLCS (Mean Normalised Log-transformed Citation Score) confidence interval formula is conservative for large groups but almost always safe. Bootstrap MNCS (Mean Normalised Citation Score) confidence intervals can be very unsafe, although their accuracy increases with sample sizes.] -> [software; additional data and graphs]
40. Kousha, K.& Thelwall, M. (2017). News stories as evidence for research? BBC citations from articles, books and Wikipedia. Journal of the Association for Information Science and Technology, 68(8), 2017-2028. doi:10.1002/jasist.23862 [News stories provide a novel source of information about real world activities that is cited by journal articles, although news stories about research are also widely cited.]
41. 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.]
42. 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.]
43. 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.
44. Thelwall, M. (2016). Are there too many uncited articles? Zero inflated variants of the discretised lognormal and hooked power law distributions. Journal of Informetrics, 10(2), 622-633. doi:10.1016/j.joi.2016.04.014 [Shows that sets of articles from a Scopus category can have too many uncited articles, due to the indexing of non-academic periodicals. Introduces the zero inflated discretised lognormal distribution and the zero inflated hooked power law distribution to deal with this issue, with software and data.]code and data for this paper. Video 1 and 2 of the effect of modelling different numbers of uncited articles.
45. Thelwall, M. (2016). Are the discretised lognormal and hooked power law distributions plausible for citation data? Journal of Informetrics, 10(2), 454-470. doi:10.1016/j.joi.2016.03.001. [Although the discretised lognormal and hooked power law distributions fit citation data reasonably well, they have slightly wrong shapes and it is impossible to verify that any distribution is an exact match.]->code and graphs for paper.
46. Thelwall, M. (2016). Not dead, just resting: The practical value of per publication citation indicators. Journal of Informetrics, 10(2), 667-670. doi:10.1016/j.joi.2015.12.009
47. Thelwall, M. & Thelwall, S. (2016). Development studies research 1975-2014 in academic journal articles: The end of economics? El Profesional de la Información, 25(1), 47-58.
48. Thelwall, M. (2016). The discretised lognormal and hooked power law distributions for complete citation data: Best options for modelling and regression. Journal of Informetrics, 10(2), 336-346. doi:10.1016/j.joi.2015.12.007. [For regression analyses, the best option is to use ordinary least squares regression applied to the natural logarithm of citation counts plus one.] code, data and results for paper.
49. Thelwall, M. (in press). The precision of the arithmetic mean, geometric mean and percentiles for citation data: An experimental simulation modelling approach. Journal of Informetrics, 10(1), 110-123. doi:10.1016/j.joi.2015.12.001 [The geometric mean is more precise than the arithmetic mean and percentile indicators, at least for sets of articles with the same lognormal scale parameter, and so is preferable for citation indicators unless heavier weighting is needed to be given to more highly cited articles.] -> code and results for the paper; geometric mean simple explanation blog post.
50. Thelwall, M., & Sud, P. (2016). National, disciplinary and temporal variations in the extent to which articles with more authors have more impact: Evidence from a geometric field normalised citation indicator. Journal of Informetrics, 10(1), 48-61. doi:10.1016/j.joi.2015.11.007 [The geometric Mean Normalized Citation Score is introduced to compare sets of articles from different fields and years. Domestic journal articles with more authors tend to have more citations, but with disciplinary, national and temporal differences and the exception of Russia.] -> geometric mean simple explanation blog post.
51. Li, X., Thelwall, M. & Kousha, K. (2015). The role of arXiv, RePEc, SSRN and PMC in formal scholarly communication, Aslib Journal of Information Management, 67(6), 614 - 635. [Subject repositories attract substantial numbers of citations from subject areas outside of their primary focus.]
52. Fairclough, R., & Thelwall, M. (2015). More precise methods for national research citation impact comparisons. Journal of Informetrics, 9(4), 895-906. doi:10.1016/j.joi.2015.09.005 [The geometric mean is the most precise indicator of citation impact for a nation's research within a single field, followed by the percentage in the top 50% and then the arithmetic mean. Percentages in the top 10% and 1% are relatively imprecise indicators, as are regression parameters.] geometric mean simple explanation blog post.
53. 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.]
54. Thelwall, M. (2015). Are medical articles highlighting detailed statistics more cited? Anales de Documentacion, 18(2), doi:10.6018/analesdoc.18.2.%20225201 [Medical articles mentioning more detailed statistics tend to be more cited.]
55. Thelwall, M. & Fairclough, R. (2015). The influence of time and discipline on the magnitude of correlations between citation counts and quality scores. Journal of Informetrics, 9(3), 529–541. doi:10.1016/j.joi.2015.05.006 [Mixing sets of articles from different years or fields can substantially reduce the strength of the correlation between quality and citation counts.] [data and software]
56. Thelwall, M. & Fairclough, R. (2015). Geometric journal impact factors correcting for individual highly cited articles. Journal of Informetrics, 9(2),263–272. [Shows that using the geometric mean rather than the arithmetic mean in journal impact factors reduces the impact of individual highly cited articles, although the differences are not large.]
57. Thelwall, M. & Wilson, P. (2016). Does research with statistics have more impact? The citation rank advantage of structural equation modelling. Journal of the Association for Information Science and Technology, 67(5), 1233–1244. doi:10.1002/asi.23474 [Articles using structural equation modelling and related methods tend to get more citations and more Mendeley readers than do comparable articles, although the extent varies by discipline and technique.]
58. Minguillo, D. & Thelwall, M. (2015). Research excellence and university-industry collaboration in UK science parks. Research Evaluation, 24(2), 181-196.
59. Minguillo, D., & Thelwall, M. (2015). Which are the best innovation support infrastructures for universities? Evidence from R&D output and commercial activities. Scientometrics, 102(1), 1057-1081.
60. Minguillo, D., Tijssen, R. & Thelwall, M. (2015). Do science parks promote research and technology? A scientometric analysis of the UK. Scientometrics, 102(1), 701-725.
61. Thelwall, M. & Wilson, P. (2014). Regression for citation data: An evaluation of different methods. Journal of Informetrics, 8(4), 963–971. [The best regression strategy for citation is to add 1, take the log and then use ordinary least squares regression.]
62. 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.]
63. 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.
64. Didegah, F., & Thelwall, M. (2013). Determinants of research citation impact in nanoscience and nanotechnology. Journal of the American Society for Information Science and Technology, 64(5), 1055–1064.
65. Didegah, F., Thelwall, M. & Gazni, A. (2012). An international comparison of journal publishing and citing behaviours, Journal of Informetrics 6(4), 516-531.
66. 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
67. Levitt, J., & Thelwall, M. (2011). A combined bibliometric indicator to predict article impact. Information Processing & Management, 47(2), 300-308
68. Levitt, J., & Thelwall, M. (2009). The most highly cited library and information science articles: Interdisciplinarity, first authors and citation patterns. Scientometrics, 78(1), 45-67.
69. Levitt, J., & Thelwall, M. (2008). Is multidisciplinary research more highly cited? A macro-level study. Journal of the American Society for Information Science and Technology, 59(12), 1973-1984.
70. Levitt, J., & Thelwall, M. (2008). Patterns of annual citation of highly cited articles and the prediction of their citation ranking: A comparison across subjects, Scientometrics, 77(1), 41-60.