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of written evidence of disputes are compared by analyzing their occurrence in relation to articles that have already been retracted or corrected.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.

Recent intensive eco-city development in China has been accompanied by rising enthusiasm for environmental sustainability indicators. Whilst there are calls for the indicators to be standardised, and criticism of the difficulties in applying them, little effort has been made to understand their scientific rationale. This article employs a comprehensive bibliometric analysis to investigate the use of environmental indicators from the Tianjin Eco-City Key Performance Indicators by the international scientific community working on urban sustainability. The findings draw a clear picture of the place of Tianjin Eco-City's indicators in the international scientific literature. China's ecological problems are found to attract interest not only from domestic researchers but also researchers outside the country. The indicators are used not only for urban planning and management but also for a wide range of urbanrelated and non-urban-related purposes. The scientific rationale of the eleven indicators is specifically addressed, revealing a number of underlying questions about the Tianjin Eco-City indicators.

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.

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.

L'auto-archivage des publications scientifiques a été initié dans les années 1970 par des scientifiques et a connu un grand développement depuis 1991 et le lancement de l'archive des physiciens arXiv. Suite à la Budapest Open Access Initiative (BOAI), il a pris le nom d'« Open Access » en 2001. Aujourd'hui, on distingue l'auto-archivage traditionnel des archives ouvertes ou Green Open Access du modèle Gold Open Access qui connaît un développement important ces dernières années. Avec ce dernier modèle, ce sont désormais les auteurs et leurs institutions qui financent les frais de publication afin que leurs productions soient accessibles en open access, directement sur le site de l'éditeur (à la différence du modèle Green), sans période d'embargo et dans la mise en forme finale.

Data is one of the most used terms in scientific vocabulary. This article focusses on the relationship between data and research by analyzing the contexts of occurrence of the word data in a corpus of 72,471 research articles (1980–2012) from two distinct fields (Social sciences, Physical sciences). The aim is to shed light on the issues raised by research on data, namely the difficulty of defining what is considered as data, the transformations that data undergo during the research process and how they gain value for researchers who hold them. Relying on the distribution of occurrences throughout the texts and over time, it demonstrates that the word data mostly occurs at the beginning and at the end of research articles. Adjectives and verbs accompanying the noun data turn out to be even more important than data itself in specifying data. The increase in the use of possessive pronouns at the end of the articles reveals that authors tend to claim ownership of their data at the very end of the research process. Our research demonstrates that even if data handling operations are increasingly frequent, they are still described with imprecise verbs that do not reflect the complexity of these transformations. Peer Review https://publons.com/publon/10.1162/qss_a_00220