This study investigates whether negative citations in articles and comments posted on post-publication peer review platforms are both equally contributing to the correction of science. These 2 types of written evidence of disputes are compared by analyzing their occurrence in relation to articles that have already been retracted or corrected. We identified retracted or corrected articles in a corpus of 72,069 articles coming from the Engineering field, from 3 journals (Science, Tumor Biology, Cancer Research) and from 3 authors with many retractions to their credit (Sarkar, Schön, Voinnet). We used Scite to retrieve contradicting citations and PubPeer to retrieve the number of comments for each article, and then we considered them as traces left by scientists to contest published results. Our study shows that contradicting citations are very uncommon and that retracted or corrected articles are not more contradicted in scholarly articles than those that are neither retracted nor corrected but they do generate more comments on Pubpeer, presumably because of the possibility for contributors to remain anonymous. Moreover, post-publication peer review platforms, although external to the scientific publication process contribute more to the correction of science than negative citations. Consequently, post-publication peer review venues, and more specifically the comments found on it, although not contributing to the scientific literature, are a mechanism for correcting science. Lastly, we introduced the idea of strengthening the role of contradicting citations to rehabilitate the clear expression of judgment in scientific papers. Article Highlights  Negative citations are very uncommon.  Retracted or corrected papers are not more contradicted than others in scholarly articles.  Post-publication peer review platforms contribute more to the correction of science than in-text negative citations to papers.

The abstract is known to be a promotional genre where researchers tend to exaggerate the benefit of their research and use a promotional discourse to catch the reader's attention. The COVID‐19 pandemic has prompted intensive research and has changed traditional publishing with the massive adoption of preprints by researchers. Our aim is to investigate whether the crisis and the ensuing scientific and economic competition have changed the lexical content of abstracts. We propose a comparative study of abstracts associated with preprints issued in response to the pandemic relative to abstracts produced during the closest pre‐pandemic period. We show that with the increase (on average and in percentage) of positive words (especially effective ) and the slight decrease of negative words, there is a strong increase in hedge words (the most frequent of which are the modal verbs can and may ). Hedge words counterbalance the excessive use of positive words and thus invite the readers, who go probably beyond the ‘usual’ audience, to be cautious with the obtained results. The abstracts of preprints urgently produced in response to the COVID‐19 crisis stand between uncertainty and over‐promotion, illustrating the balance that authors have to achieve between promoting their results and appealing for caution.

An abstract is not only a mirror of the full article; it also aims to draw attention to the most important information of the document it summarizes. Many studies have compared abstracts with full texts for their informativeness. In contrast to previous studies, we propose to investigate this relation based not only on the amount of information given by the abstract but also on its importance. The main objective of this paper is to introduce a new metric called GEM to measure the "generosity" or representativeness of an abstract. Schematically speaking, a generous abstract should have the best possible score of similarity for the sections important to the reader. Based on a questionnaire gathering information from 630 researchers, we were able to weight sections according to their importance. In our approach, seven sections were first automatically detected in the full text. The accuracy of this classification into sections was above 80% compared with a dataset of documents where sentences were assigned to sections by experts. Second, each section was weighted according to the questionnaire results. The GEM score was then calculated as a sum of weights of sections in the full text corresponding to sentences in the abstract normalized over the total sum of weights of sections in the full text. The correlation between GEM score and the mean of the scores assigned by annotators was higher than the correlation between scores from different experts. As a case study, the GEM score was calculated for 36,237 articles in environmental sciences retrieved from the French ISTEX database. The main result was that GEM score has increased over time. Moreover, this trend depends on subject area and publisher. No correlation was found between GEM score and citation rate or open access status of articles. We conclude that abstracts are more generous in recent publications and cannot be considered as mere teasers. This research should be pursued in greater depth, particularly by examining structured abstracts. GEM score could be a valuable indicator for exploring large numbers of abstracts, by guiding the reader in his/her choice of whether or not to obtain and read full texts.

The dataset includes search queries that can be used to identify scientific publications related to the United Nations Sustainable Development Goals (SDGs). We propose a new approach to mitigate the polysemy of terms as much as possible by targeting the most relevant subject areas for each SDG. In addition, we also used a text-mining tool to identify as many relevant phrases as possible. Publications identified through this process cannot be considered as evidence of the commitment of authors and their institutions to actions towards the targets established by the UN. However, they can be an accurate indicator of which research is relevant to the issues addressed by the SDGs, whether or not it is a direct contribution.

This article proposes an analysis of research dedicated to permafrost. Its originality is twofold: it covers a corpus (n=16,249) that has never been reviewed before and also makes use of a methodology based on successive textual analysis processes. With the text-mining of additional corpuses, we produce lists of qualified terms to fine-tune the indexing of the main corpus and isolate relevant terminology dedicated to infrastructure and soil properties. With these enrichments combined with other terminological extractions (such as place names recognition), we reveal the internal structure of permafrost research with the help of visual mapping and easily prove that permafrost research is multidisciplinary and multi-topical The semantic map and the diachronic analysis of terms clusters show that the interest had turned since the 1980s towards the role of climate change but also on China's needs for its highway and railway construction sites. The very strong and growing impact of Chinese research, focused on the Tibetan area, is one of the highlights of our data. Furthermore, we propose a focus on infrastructure vulnerability and use soil properties as a proxy to measure the existing interactions between two distinct research communities. The results suggest that research has mainly focused so far on the feasibility of building on frozen ground and exploiting soils, but remains at an early stage of addressing the impact of global warming on infrastructure degradation and its resilience. This study offers insights to permafrost experts, but also provide a methodology that could be reused for other investigations.