This paper studies the production of dissertations in eight research fields in thenatural sciences, the social sciences and the humanities. In using doctoral dissertations itbuilds on De Solla Prices seminal study which used PhD dissertations as one of severalindicators of scientific growth (Price, Little science, big science, 1963). Data from theProQuest: Dissertations and Theses database covering the years 1950–2007 are used todepict historical trends, and the Gompertz function was used for analysing the data. Adecline in the growth of dissertations can be seen in all fields in the mid-eighties andseveral fields show only a modest growth during the entire period. The growth profiles ofspecific disciplines could not be explained by traditional dichotomies such as pure/appliedor soft/hard, but rather it seems that the age of the discipline appears to be an importantfactor. Thus, it is obvious that the growth of dissertations must be explained using severalfactors emerging both inside and outside academia. Consequently, we propose that theoutput of dissertations can be used as an indicator of growth, especially in fields like thehumanities, where journal or article counts are less applicable.

In this study we investigated whether open access could assist the broader dissemination of scientific research in Climate Action (Sustainable Development Goal 13) via news outlets. We did this by comparing (i) the share of open and non-open access documents in different Climate Action topics, and their news counts, and (ii) the mean of news counts for open access and non-open access documents. The data set of this study comprised 70,206 articles and reviews in Sustainable Development Goal 13, published during 2014–2018, retrieved from SciVal. The number of news mentions for each document was obtained from Altmetrics Details Page API using their DOIs, whereas the open access statuses were obtained using Unpaywall.org. The analysis in this paper was done using a combination of (Latent Dirichlet allocation) topic modelling, descriptive statistics, and regression analysis. The covariates included in the regression analysis were features related to authors, country, journal, institution, funding, readability, news source category and topic. Using topic modelling, we identified 10 topics, with topics 4 (meteorology) [21%], 5 (adaption, mitigation, and legislation) [18%] and 8 (ecosystems and biodiversity) [14%] accounting for 53% of the research in Sustainable Development Goal 13. Additionally, the results of regression analysis showed that while keeping all the variables constant in the model, open access papers in Climate Action had a news count advantage (8.8%) in comparison to non-open access papers. Our findings also showed that while a higher share of open access documents in topics such as topic 9 (Human vulnerability to risks) might not assist with its broader dissemination, in some others such as topic 5 (adaption, mitigation, and legislation), even a lower share of open access documents might accelerate its broad communication via news outlets.

Although there are now several bibliographic databases of research publications, such as Google Scholar, Pubmed, Scopus, and the Web of Science (WoS), and some also include counts of citations, there is at present no similarly comprehensive database of the rapidly growing number of clinical practice guidelines (CPGs), with their references, which sometimes number in the hundreds. CPGs have been shown to be useful for the evaluation of clinical (as opposed to basic) biomedical research, which often suffers from relatively low counts of citations in the serial literature. The objectives were to introduce a new citation database, clinical impact (R), and demonstrate how it can be used to evaluate research impact of clinical research publications by exploring the characteristics of CPG citations of two sets of papers, as well as show temporal variation of clinical impactand the WoS. The paper includes the methodology used to retain the data and also the rationale adopted to achieve data quality. The analysis showed that although CPGs tend preferentially to cite papers from their own country, this is not always the case. It also showed that cited papers tend to have a more clinical research level than uncited papers. An analysis of diachronous citations in both clinical impactand the WoS showed that although the WoS citations showed a decreasing trend after a peak at 2-3 years after publication, this was less clear for CPG citations and a longer timescale would be needed to evaluate their impact on these documents.

This is a cross-field literature review and comparison of the fields webometrics (cybermetrics) and web (data) mining.

This article studies interdisciplinarity and the intellectual base of 34 literaturejournals using citation data from Web of Science. Data from two time periods, 1978–1987and 1998–2007 were compared to reveal changes in the interdisciplinary citing ofmonographs. The study extends the analysis to non-source publications; using the classificationof monographs to show changes in the intellectual base. There is support forincreased interdisciplinary citing of sources, especially to the social sciences, and changesin the intellectual base reflect this. The results are explained using theories on the intellectualand social organization of scientific fields and the use of bibliometric methods onthe humanities is discussed. The article demonstrates how citation analysis can provideinsights into the communication patterns and intellectual structure of scholarly fields in thearts and humanities.

The prospects of altmetrics are especially encouraging for research fields in thehumanities that currently are difficult to study using established bibliometric methods. Yet,little is known about the altmetric impact of research fields in the humanities. Consequently,this paper analyses the altmetric coverage and impact of humanities-orientedarticles and books published by Swedish universities during 2012. Some of the mostcommon altmetric sources are examined using a sample of 310 journal articles and 54books. Mendeley has the highest coverage of journal articles (61 %) followed by Twitter(21 %) while very few of the publications are mentioned in blogs or on Facebook. Books,on the other hand, are quite often tweeted while both Mendeley’s and the novel data sourceLibrary Thing’s coverage is low. Many of the problems of applying bibliometrics to thehumanities are also relevant for altmetric approaches; the importance of non-journalpublications, the reliance on print as well the limited coverage of non-English languagepublications. However, the continuing development and diversification of methods suggeststhat altmetrics could evolve into a valuable tool for assessing research in thehumanities.

The prospects of altmetrics are especially encouraging for research fields in the humanities that currently are difficult to study using established bibliometric methods. Yet, little is known about the altmetric impact of research fields in the humanities. Consequently, this paper analyses the altmetric coverage and impact of humanities-oriented articles and books published by Swedish universities during 2012. Some of the most common altmetric sources are examined using a sample of 310 journal articles and 54 books. Mendeley has the highest coverage of journal articles (61 %) followed by Twitter (21 %) while very few of the publications are mentioned in blogs or on Facebook. Books, on the other hand, are quite often tweeted while both Mendeley’s and the novel data source Library Thing’s coverage is low. Many of the problems of applying bibliometrics to the humanities are also relevant for altmetric approaches; the importance of non-journal publications, the reliance on print as well the limited coverage of non-English language publications. However, the continuing development and diversification of methods suggests that altmetrics could evolve into a valuable tool for assessing research in the humanities.

The method of author cocitation analysis (ACA) was first presented by White and Griffith in 1981 as a “literature measure of intellectual structure” and its applicability for the mapping of areas of science has since then been tested in various bibliometric science mapping studies. In this study, an experimental method of calculating the first or single author cocitation frequency is presented and compared with the standard method. Applying Ward’s method of clustering, the analysis revealed that the two approaches did not produce similar results and a tentative interpretation of deviations was that the experimental method provided with a more detailed depiction of the specialty structure. It was also concluded that a number of additional research questions need to be resolved before a comprehensive understanding of the suggested method’s merits and demerits is reached.

Motivated by the merging of four Swedish counties to a larger administrative and political unit with increased responsibilities, a comprehensive study of regional–foreign research collaboration was carried out. Various multivariate methods were applied for the depiction of collaborative networks of various compositions and at various levels of aggregation. Other aspects investigated concerned the influence of institutions and countries on regional–foreign collaboration and the relation between collaboration and research fields. Findings showed that foreign research collaboration was concentrated to three major regional institutions, each with a characteristic collaborative context. The influence of domestic collaboration was notable with regard to medical research while collaboration within the field of physics and astronomy was characteristic for pure regional–foreign collaboration, which was the dominating type of research collaboration throughout the period of observation (1998–2006).

This paper presents a citation analysis of the cognitive structure of current cardiovascularresearch. Used methods are co-citation analysis, bibliographic coupling and quantitative analysisof title words. Tables and graphs reveal: (1) The journal co-citation structure; (2) the cognitivecontent and the bibliometric structure of clusters based on co-citation; (3) the cognitive contentand the bibliometric structure of clusters based on bibliographic coupling. A predominance ofdifferent research aspects on coronary artery disease was found in clusters based on co-citations aswell as in clusters based on bibliographic coupling.

We describe ongoing research where the aim is to apply recent results from the research field of information fusion to bibliometric analysis and information retrieval. We highlight the importance of ‘uncertainty’ within information fusion and argue that this concept is crucial also for bibliometrics and information retrieval. More specifically, we elaborate on three research strategies related to uncertainty: uncertainty management methods, explanation of uncertainty and visualization of uncertainty. We exemplify our strategies to the classical problem of author name disambiguation where we show how uncertainty can be modeled explained and visualized using information fusion. We show how an information seeker can benefit from tracing increases/decreases of uncertainty in the reasoning process. We also present how such changes can be explained for the information seeker through visualization techniques, which are employed to highlight the complexity involved in the process of modeling and managing uncertainty in bibliometric analysis. Finally we argue that a further integration of information fusion approaches in the research area of bibliometrics and information retrieval may results in new and fruitful venues of research.

This article analyzes "happiness studies" as an emerging field of inquiry throughout various scientific disciplines and research areas. Utilizing four operationalized search terms in the Web of Science; "happiness", "subjective well-being", "life satisfaction" and "positive affect", a dataset was created for empirical citation analysis. Combined with qualitative interpretations of the publications, our results show how happiness studies has developed over time, in what journals the citing papers have been published, and which authors and researchers are the most productive within this set. We also trace various trends in happiness studies, such as the social indicators movement, the introduction of positive psychology and various medical and clinical applications of happiness studies. We conclude that "happiness studies" has emerged in many different disciplinary contexts and progressively been integrated and standardized. Moreover, beginning at the turn of the millennium, happiness studies has even begun to shape an autonomous field of inquiry, in which happiness becomes a key research problem for itself. Thus, rather than speaking of a distinct "happiness turn", our study shows that there have been many heterogeneous turns to happiness, departing in a number of different disciplines.

Webometrics and web mining are two fields where research is focused on quantitative analyses of the web. This literature review outlines definitions of the fields, and then focuses on their methods and applications. It also discusses the potential of closer contact and collaboration between them. A key difference between the fields is that webometrics has focused on exploratory studies, whereas web mining has been dominated by studies focusing on development of methods and algorithms. Differences in type of data can also be seen, with webometrics more focused on analyses of the structure of the web and web mining more focused on web content and usage, even though both fields have been embracing the possibilities of user generated content. It is concluded that research problems where big data is needed can benefit from collaboration between webometricians, with their tradition of exploratory studies, and web miners, with their tradition of developing methods and algorithms.

This study investigates the scholarly field of sustainability science between 2001 and 2021 from the perspective of 18 frequently cited journals. For this purpose, the article employs the concept of the “scientific field” developed by the sociologist Pierre Bourdieu and the associated methodology of Geometric Data Analysis (GDA). Thus, two GDA approaches, the Principal Component Analysis (PCA) and the Multiple Correspondence Analysis (MCA), as well as analyses of co-citation and co-authorship relations, were used to identify the positions of these journals in the field. One key finding is the historical shift from an earlier dominance of chemistry-related journals to publications more broadly concerned with sustainability research. The MCA analyses show that the selection of research topics is in line with a “weak” rather than “strong” interpretation of the concept “sustainability.” Networks based on co-authorship relations reveal an overall increment in this type of collaboration, both at the level of organizations and countries. Since 2008, Chinese universities have notably increased their presence in the output of the journals examined in the study. Three strategies in shaping the field through its journals are discernable: publications strongly characterized by a systems theory perspective, notably Sustainability Science; generalist journals committed to sustainability research in a broader meaning; and publications that address sustainability issues mainly within a specific discipline. 

Citation and coauthor networks offer an insight into the dynamics of scientific progress. We can also view them as representations of a causal structure, a logical process captured in a graph. From a causal perspective, we can ask questions such as whether authors form groups primarily due to their prior shared interest, or if their favourite topics are ‘contagious’ and spread through co-authorship. Such networks have been widely studied by the artificial intelligence community, and recently a connection has been made to nonlocal correlations produced by entangled particles in quantum physics—the impact of latent hidden variables can be analyzed by the same algebraic geometric methodology that relies on a sequence of semidefinite programming (SDP) relaxations. Following this trail, we treat our sample coauthor network as a causal graph and, using SDP relaxations, rule out latent homophily as a manifestation of prior shared interest only, leading to the observed patternedness. By introducing algebraic geometry to citation studies, we add a new tool to existing methods for the analysis of content-related social influences.