Professor of Information Science; researching big data: webometrics, altmetrics, and sentiment analysis; developing quantitative web methods for Twitter, social networks, YouTube, and various types of link and impact metrics; conducting impact assessments for organisations, such as the UNDP.
Thelwall, M. & Delgado, M. (2015, in press). Arts and humanities research evaluation: No metrics please, just data. Journal of Documentation, 71(4).[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.]
Thelwall, M. & Sud, P. (in press). Mendeley readership counts: An investigation of temporal and disciplinary differences. Journal of the Association for Information Science and Technology. [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.]
Thelwall, M. & Wilson, P. (in press). Mendeley readership Altmetrics for medical articles: An analysis of 45 fields, Journal of the Association for Information Science and Technology. 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.]
Mohammadi, E., Thelwall, M. & Kousha, K. (in press). Can Mendeley bookmarks reflect readership? A survey of user motivations. Journal of the Association for Information Science and Technology. 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.]
Thelwall, M. & Wilson, P. (2014). Distributions for cited articles from individual subjects and years. Journal of Informetrics, 8(4), 824-839. [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.]
Kousha, K. & Thelwall, M. (in press). Can Amazon.com reviews help to assess the wider impacts of books? Journal of the Association for Information Science and Technology.[Amazon book reviews (number and sentiment) are useful academic book impact indicators. Book reviews tend to reflect the wider popularity of books rather than their purely academic impact.]
Sud, P. & Thelwall, M. (2014). Linked title mentions: A new automated link search candidate. Scientometrics, 101(3), 1831-1849. [A new automatic link search method, linked title mentions, in Webometric Analyst can give more accurate results that URL citations or title mentions in certain circumstances.]
Thelwall, M. & Kousha, K. (2015). ResearchGate: Disseminating, communicating and measuring scholarship? Journal of the Association 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.]
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 [Health research bloggers tend to cover others' work, seem to aim at a general audience, and often include critical comments.]
Kousha, K. & Thelwall, M. (2015). An automatic method for extracting citations from Google Books. Journal of the Association 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.]
Kousha, K. & Thelwall, M. (2014). Disseminating research with web CV hyperlinks. Journal of the Association for Information Science and Technology, 65(8), 1615–1626. [Few EU researchers are fully exploiting their CVs to publicise their research.]
Thelwall, M. & Kousha, K. (2014). Academia.edu: Social network or academic network? Journal of the Association for Information Science and Technology, 65(4), 721-731. [Academia.edu reflects a combination of scholarly and social network site norms.]
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 [Altmetrics can associate with higher citation counts, but changes in the uptake of social web services over time makes it invalid to compare scores for articles from different time periods, even a single year.]
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., Buckley, K., & Paltoglou, G. (2012). Sentiment strength detection for the social web. Journal of the American Society for Information Science and Technology, 63(1), 163-173.[Describes and evaluates an improved sentiment analysis approach to detect the strength of positive and negative sentiment in a wide variety of types of social web texts.]
Eccles, K.E., Thelwall, M., & Meyer, E.T. (2012). Measuring the web impact of digitised scholarly resources. Journal of Documentation, 68(4), 512-526.
Wilkinson, D. & Thelwall, M. (2011). Researching personal information on the public Web: Methods and ethics, Social Science Computer Review, 29(4), 387-401.(please email for a copy). Related e-research ethics article.
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.] [read a summary in this science blog]
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., & Kappas, A. (2010). Sentiment strength detection in short informal text. Journal of the American Society for Information Science and Technology, 61(12), 2544-2558. [Describes and evaluates a new sentiment analysis approach to detect the strength of positive and negative sentiment in short informal social web texts.] [sentistrength 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.]
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. [abstract and publisher copy]
Angus, E., Thelwall, M., Stuart, D. (2010). Flickr’s potential as an academic image resource: an exploratory study. Journal of Librarianship and Information Science, 42(4) 268–278.
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.
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. [Note that seven Price medallists (Moravscik MJ; Merton RK; Vlachy, J; Irvine, J; Nalimov VV; Martin BR; Rousseau R) were omitted from the table of results - these are all clearly highly influential information scientists but did not meet one of the technical criteria mentioned in the methods for conducting the analysis.]
Thelwall, M. (2009). Homophily in MySpace, Journal of the American Society for Information Science and Technology, 60(2), 219-231.
Thelwall, M. (2009). MySpace comments. Online Information Review, 33(1), 58-76. [An analysis of words used in MySpace comments]
Prabowo, R., Thelwall, M., Hellsten I., & Scharnhorst A., (2008). Evolving debate in online communication: A graph analytical approach, Internet Research.18(5), 520-540.
Holmberg, K. & Thelwall, M. (2009). Local government web sites in Finland: A geographic and webometric analysis, Scientometrics, 79(1), 157-169.
Zuccala, A., Thelwall, M., Oppenheim, C., & Dhiensa, R. (2007). Web intelligence analyses of digital libraries: A case study of the National Electronic Library for Health (NeLH). Journal of Documentation, 63(4), 558-589.
Thelwall, M., Harries, G., & Wilkinson, D. (2003). Why do web sites from different academic subjects interlink? Journal of Information Science, 29(6), 445-463.
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.
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), 59-66.
Thelwall, M. (2003). Web use and peer interconnectivity metrics for academic web sites, Journal of Information Science, 29(1), 11-20.
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.
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]
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. (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. (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. (2013). Big Data and Social Web Research Methods [free in-progress draft copy]. University of Wolverhampton. [This is an updated and extended free ebook based upon the book below and four extra chapters from a forthcoming book. It can be read on its own or as an update to the book below] [28 August 2014 update; a previous version of this book was called: Webometrics and social web research methods]
Dr David Minguillo, Mapping R&D support infrastructures: a scientometric and webometric study of UK science parks. 2010-2013: Director of studies.
Dr Emma Stuart, Image tagging: How do motivations to tag compare with tagging practices? 2007-2012: Director of studies.
Dr Brian Cugelman, Online social marketing: Website factors in behavioural change. 2007-2010: Director of studies.
Dr Kim Holmberg, Webometric network analysis: Mapping cooperation and geopolitical connections between local government administration on the web. Åbo Akademi University, Finland. External PhD advisor.
Dr Jonathan Levitt, Factors affecting citation levels: An international multidisciplinary analysis. 2006-2008: Director of studies.
Dr David Stuart, Online university-industry-government relationships. 2004-2007: Director of studies.
Dr Nigel Payne, Longitudinal studies of academic web links. 2004-2007: Director of studies.
Björneborn, Small world phenomena on the Web, 2002-2003: Second
supervisor (project supervisor) at the Royal School of Library and Information
Science, Copenhagen, Denmark. Main supervisor: Professor Peter
Ingwersen. Winner of the 2004 ASIST Proquest/UMI Doctoral Dissertation Award.
Dr Xuemei Li, The development of methodologies to investigate web interlinking of academic departments: The case of university computer science departments in Europe, 2001-2005: Director of studies.
PhD Examinations (30)
11 Information science
8 Computational linguistics
7 Computer science
3 Social science (sociology/politics, communication studies, and cultural studies)
1 Physics (complex systems)
BSc (Hons) I Mathematics, Lancaster University 1986
PhD Mathematics, Lancaster University 1989
Bass guitarist in the Atomic Rooster tribute band Nutha Clucker.