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The role of preprints in the scientific production and their part in citations have been growing over the past 10 years. In this paper we study preprint citations in several different aspects: the progression of preprint citations over time, their relative frequencies in relation to the IMRaD structure of articles, their distributions over time, per preprint database and per PLOS journal. We have processed the PLOS corpus that covers 7 journals and a total of about 240,000 articles up to January 2021, and produced a dataset of 8460 preprint citation contexts that cite 12 different preprint databases. Our results show that preprint citations are found with the highest frequency in the Method section of articles, though small variations exist with respect to journals. The PLOS Computational Biology journal stands out as it contains more than three times more preprint citations than any other PLOS journal. The relative parts of the different preprint databases are also examined. While ArXiv and bioRxiv are the most frequent citation sources, bioRxiv’s disciplinary nature can be observed as it is the source of more than 70% of preprint citations in PLOS Biology, PLOS Genetics and PLOS Pathogens. We have also compared the lexical content of preprint citation contexts to the citation content to peer-reviewed publications. Finally, by performing a lexicometric analysis, we have shown that preprint citation contexts differ significantly from citation contexts of peer-reviewed publications. This confirms that authors make use of different lexical content when citing preprints compared to the rest of citations.

The organization of scientific papers typically follows a standardized pattern, the well-known IMRaD structure introduction, methods, results, and discussion. Using the full text of 45,000 papers published in the PLoS series of journals as a case study, this paper investigates, from the viewpoint of bibliometrics, how references are distributed along the structure of scientific papers as well as the age of these cited references. Once the sections of articles are realigned to follow the IMRaD sequence, the position of cited references along the text of articles is invariant across all PLoS journals, with the introduction and discussion accounting for most of the references. It also provides evidence that the age of cited references varies by section, with older references being found in the methods and more recent references in the discussion. These results provide insight into the different roles citations have in the scholarly communication process.

This is the sixth publication in the series of biennial international conferences, The Future of Information Sciences (INFuture) organised by the Department of Information and Communication Sciences, Faculty of Humanities and Social Sciences, University of Zagreb. This year it is co-organised with the Miroslav Krleža Institute of Lexicography. The title of the conference is INFuture2017: Integrating ICT in Society. The conference explores the influence the information and communication sciences have on the society as a whole.

EC3 is intended to extract relevant information from large heterogeneous and multilingual text data, in particular in WEB 3.0. The project is based on an original method: contextual exploration. EC3 does not need syntactic analysis, statistical analysis or a "general" ontology. EC3 uses only small ontologies called "linguistic ontologies" that express the linguistic knowledge of a user who must concentrate on the relevant information from one point of view. This is why EC3 works very quickly on large corpus, whose components can be both whole books as well as "short texts": SMS to books. At the output, EC3 offers a visual representation of information using an original approach: the "Memory Islands". EC3 is implanted in the ACASA / LIP6 team. EC3 is tested on the large digitized corpus provided by the Labex OBVIL «Observatoire de la Vie Litteraire», in partnership with the Bibliotheque Nationale de France (http://obvil.paris-sorbonne.fr/). OBVIL intends to develop all the resources offered by digitization and computer applications to examine French literature from the sixteenth to the twentieth century, English and American literature, Italian literature, Spanish literature, in its most traditional formats and media Or the most innovative.

Depuis l’entree en vigueur en mai 2018 du Reglement general sur la protection des donnees (RGPD), la protection des donnees personnelles est une obligation pour toutes les entreprises de l’Union europeenne. Comment faire face a cet enjeu majeur, difficile a traiter ? Plusieurs mesures techniques sont prevues, en particulier l’anonymisation et la pseudonymisation.

International audience; The workshop "Mining Scientific Papers: Computational Linguistics and Bibliometrics" (CLBib 2015), co-located with the 15th International Society of Scientometrics and Informetrics Conference (ISSI 2015), brought together researchers in Bibliometrics and Computational Linguistics in order to study the ways Bibliometrics can benefit from large-scale text analytics and sense mining of scientific papers, thus exploring the interdisciplinarity of Bibliometrics and Natural Language Processing (NLP). The goals of the workshop were to answer questions like: How can we enhance author network analysis and Bibliometrics using data obtained by text analytics? What insights can NLP provide on the structure of scientific writing, on citation networks, and on in-text citation analysis? This workshop is the first step to foster the reflection on the interdisciplinarity and the benefits that the two disciplines Bibliometrics and Natural Language Processing can drive from it.

International audience

International audience; This article focuses on a Natural Language Processing (NLP) approach for the analysis of citation functions in scientific papers. Bibliometricstudies traditionally rely on citation metadata and count the number of times a publication has been cited.

International audience; Nous nous intéressons à la représentation des informations géographiques extraites d'articles scientifiques. En utilisant des outils de Traitement Automatique des Langues et de géo-codage, nous avons traité la revue PLOS Neglected Tropical Diseases afin de produire des données spatiales liées aux articles sous forme de Linked Data. Les résultats montrent une exploitation spatiale et temporelle des données représentant les zones du monde concernées par les maladies tropicales à différentes échelles.

International audience

International audience; The latest advances in research in the field of bibliometrics take into consideration in-text references. The purpose of this paper is to focus on citation contexts that express negational citations and which are relatively rare in articles. Our goal is to automate the extraction of negational citation contexts and to put them in relation to positions in the text progression of articles. After extracting sentences from the full text body of articles, we construct linguistic resources in order to identify some of the negational citation discursive patterns. We show the distribution of negational citations in the IMRaD structure. The identification of negational citations has numerous potential applications and might be used to improve information retrieval of scientific papers.

International audience; Comment traiter les langues naturelles par des systèmes de performance autres que le cerveau humain ? L'ouvrage Traitement automatique des langues naturelles. De l'analyse à l'application, rassemble des contributions issues de plusieurs champs disciplinaires comme la linguistique, l'informatique, la philosophie et l'analyse du discours. Il expose deux aspects primordiaux de tout traitement automatique : l'analyse et l'application informatique. Les analyses présentées sont de nature philosophique ou linguistique. Certaines de ces analyses s'inscrivent dans le cadre de la théorie des actes du discours, d'autres dans le cadre de théories linguistiques formelles. Les applications informatiques, quant à elles, bien que basées sur des analyses pour la plupart linguistiques, démontrent que cet aspect du traitement automatique des langues naturelles est primordial pour tester la robustesse des modèles et le bien-fondé des analyses.

International audience; Bibliometrics is more and more interested in the full text processing and the study of the structure of scientific papers. The contexts of in-text references present in articles are particularly relevant for such studies. This work describes the construction of the InTeReC dataset, which is an in-text reference corpus that aims to promote experimental reproducibility and to provide a standard dataset for further research. The InTeReC dataset is a set of sentences containing in-text references together with all the data necessary for their recontextualization in papers using standard CSV format. This should encourage the implementation of natural language processing tools for Bibliometric studies and related research in information retrieval and visualization.

International audience

This thesis focuses on the development of a tool for the automatic processing of Modern Standard Arabic, at the morphological and semanticlevels, with the final objective of Information Extraction on technological innovations. As far as the morphological analysis is concerned, our tool includes several successive processing stages that allow to label and disambiguate occurrences in texts : a morphological layer (Gibran 1.0), which relies on Arabic pattern as distinctive features ; a contextual layer (Gibran 2.0), which uses contextual rules ; and a third layer (Gibran 3.0), which uses a machine learning model. Our methodology is evaluated using the annotated corpus Arabic-PADT UD treebank. The evaluations obtain an F-measure of 0.92 and 0.90 for the morphological analyses. These experiments demontrate the possibility of improving such a corpus through linguistic analyses. This approach allowed us to develop a prototype of information extraction on technological innovations for the Arabic language. It is based on the morphological analysis and syntaxico-semantic patterns. This thesis is part of a doctoral-entrepreneurial course., Cette recherche porte sur le développement d’un outil de traitement automatique de la langue arabe standard moderne, au niveau morphologique et sémantique, avec comme objectif final l’extraction d’information dans le domaine de l’innovation technologique en entreprise. En ce qui concerne l’analyse morphologique, notre outil comprend plusieurs traitements successifs qui permettent d’étiqueter et de désambiguïser les occurrences dans les textes : une couche morphologique (Gibran 1.0), qui s’appuie sur les schèmes arabes commetraits distinctifs ; une couche contextuelle (Gibran 2.0), qui fait appel à des règles contextuelles ; et une troisième couche (Gibran 3.0) qui fait appel à un modèle d’apprentissage automatique. Notre méthodologie est évaluée sur le corpus annoté Arabic-PADT UD treebank. Les évaluations obtiennent une F-mesure de 0,92 et 0,90 pour les analyses morphologiques. Ces expérimentations montrent, entre autres, la possibilité d’améliorer une telle ressource par les analyses linguistiques. Cette approche nous a permis de développer un prototype d’extrac-tion d’information autour de l’innovation technologique pour la langue arabe. Il s’appuie sur l’analyse morphologique et des patrons syntaxico-sémantiques. Cette thèse s’inscrit dans un parcours docteur-entrepreneur.