Exploring linguistic characteristics of highly browsed and downloaded academic articles

Linguistic positivity in soft and hard disciplines: temporal dynamics, disciplinary variation, and the relationship with research impact

Previous studies have investigated the use of positive/negative language in academic discourse, and have found a tendency toward using more positive language in academic writing. However, little is known about whether the features and dynamics of linguistic positivity vary across disciplines. In addition, the relationship between linguistic positivity and research impact deserves further evaluation. To address these issues, the present study investigated linguistic positivity in academic writing from a cross-disciplinary perspective. Based on a 111-million-word corpus of research article abstracts collected from the Web of Science, the study examined the diachronic trends of positive/negative language in eight academic disciplines, and explored the relationship between linguistic positivity and citation counts. The results demonstrated that the increase in linguistic positivity is a common phenomenon across the examined academic disciplines. In addition, hard disciplines showed a higher and faster-growing degree of linguistic positivity compared with soft disciplines. Last, a significant positive correlation was identified between citation counts and the degree of linguistic positivity. Reasons for the temporal dynamics and disciplinary variation of linguistic positivity were explored, and implications for the scientific community were discussed.

The relationship between citations and the linguistic traits of specific academic discourse communities identified by using social network analysis

For a research article (RA) to be accepted, not only for publication, but also by its readers, it must display proficiency in the content, methodologies and discourse conventions of its specific discipline. While numerous studies have investigated the linguistic characteristics of different research disciplines, none have utilised Social Network Analysis techniques to identify communities prior to analysing their language use. This study aims to investigate the language use of three highly specific research communities in the fields of Psychology, Physics and Sports Medicine. We were interested in how these language features are related to the total number of citations, the eigencentrality within the community and the intra-network citations of the individual RAs. Applying Biber’s Multidimensional Analysis approach, a total of 771 RA abstracts published between 2010 and 2019 were analysed. We evaluated correlations between one of three network characteristics (citations, eigencentrality and in-degree), the corpora’s dimensions and 72 individual language features. The pattern of correlations suggest that features cited by other RAs within the discourse community network are in almost all cases different from those that are cited by RAs from outside the network. This finding highlights the challenges of writing for both a discipline-specific and a wider audience.

The evolutionary pattern of language in scientific writings: A case study of Philosophical Transactions of Royal Society (1665–1869)

Scientific writings, as one essential part of human culture, have evolved over centuries into their current form. Knowing how scientific writings evolved is particularly helpful in understanding how trends in scientific culture developed. It also allows us to better understand how scientific culture was interwoven with human culture generally. The availability of massive digitized texts and the progress in computational technologies today provide us with a convenient and credible way to discern the evolutionary patterns in scientific writings by examining the diachronic linguistic changes. The linguistic changes in scientific writings reflect the genre shifts that took place with historical changes in science and scientific writings. This study investigates a general evolutionary linguistic pattern in scientific writings. It does so by merging two credible computational methods: relative entropy; word-embedding concreteness and imageability. It thus creates a novel quantitative methodology and applies this to the examination of diachronic changes in the Philosophical Transactions of Royal Society (PTRS, 1665–1869). The data from two computational approaches can be well mapped to support the argument that this journal followed the evolutionary trend of increasing professionalization and specialization. But it also shows that language use in this journal was greatly influenced by historical events and other socio-cultural factors. This study, as a “culturomic” approach, demonstrates that the linguistic evolutionary patterns in scientific discourse have been interrupted by external factors even though this scientific discourse would likely have cumulatively developed into a professional and specialized genre. The approaches proposed by this study can make a great contribution to full-text analysis in scientometrics.