Abstract
The NLP4NLP corpus contains articles published in 34 major conferences and journals in the field of speech and natural language processing over a period of 50 years (1965-2015), comprising 65,000 documents, gathering 50,000 authors, including 325,000 references and representing approximately 270 million words. This paper presents an analysis of this corpus regarding the evolution of the research topics, with the identification of the authors who introduced them and of the publication where they were first presented, and the detection of epistemological ruptures. Linking the metadata, the paper content and the references allowed us to propose a measure of innovation for the research topics, the authors and the publications. In addition, it allowed us to study the use of language resources, in the framework of the paradigm shift between knowledge-based approaches and content-based approaches, and the reuse of articles and plagiarism between sources over time. Numerous manual corrections were necessary, which demonstrated the importance of establishing standards for uniquely identifying authors, articles, resources or publications.
Highlights
Preliminary RemarksThe aim of this study was to investigate a specific research area, namely Natural Language Processing (NLP), through the related scientific publications, with a large amount of data and a set of tools, and to report various findings resulting from those investigations
We studied several terms that became more popular over time, such as “Annotation” and “Wordnet,” which gained a lot of popularity in 1998 when the first Language Resources and Evaluation Conference (LREC) was organized, “Gaussian Mixture Models (GMM)” and “Support Vector Machines (SVM),” “Wikipedia,” and, recently, “Dataset,” “Deep Neural Networks (DNN)” blooming in the top 40 terms in 2013 and “Tweet” blooming in the top 20 in 2011 (Figure 3)
We examine the copy & paste operations in both directions: we study the configuration with a source paper borrowing fragments of text from other papers of the NLP4NLP collection, in other words, a backward study, and we study in the reverse direction the fragments of the source paper being borrowed by papers of the NLP4NLP collection, in other words, a forward study
Summary
The aim of this study was to investigate a specific research area, namely Natural Language Processing (NLP), through the related scientific publications, with a large amount of data and a set of tools, and to report various findings resulting from those investigations. We will consider the evolution of research topics over time and identify the authors who introduced and mainly contributed to key innovative topics, the use of Language Resources over time and the reuse of papers and plagiarism within and across publications We provide both global figures corresponding to the whole data and comparisons of the various conferences and journals among those various dimensions. Given the poor quality and low number of different sources and papers in the first years, we decided to only consider the period from 1975 to 2015 This innovation measure provides an overall ranking of the terms. The fact that some conferences are annual, while others are biennial brings noise, as we already observed when studying
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