The use of citation context to detect the evolution of research topics: a large-scale analysis

Jebari, Chaker; Herrera‐Viedma, Enrique; Cobo, Manuel J.

doi:10.1007/s11192-020-03858-y

Cited by 17 publications

(6 citation statements)

References 59 publications

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“…The authors argue that these trends imply that NLP has become a rapid discovery science (Collins, 1994), i.e., a particular shift a scientific field can undergo when it reaches a high level of consensus on its research topics, methods, and technologies, and then starts to continually improve on each other's methods. A number of recent papers also leverages or studies citation context, including ; Jebari et al (2021); Wright and Augenstein (2021); Lauscher et al (2021). Our approach differs from Jurgens et al (2018) in several ways: for example, we do not analyze individual citations, but directly evaluate the stance of a complete paper (as measured by its framing in the paper's abstract); most importantly, we are particularly interested in negative stances, which as relation is absent in the classification scheme of Jurgens et al (2018).…”

Section: Related Workmentioning

confidence: 99%

Detecting Stance in Scientific Papers: Did we get more Negative Recently?

Beese¹,

Begüm²,

Güzeler³

et al. 2022

Preprint

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In this paper, we classify scientific articles in the domain of natural language processing (NLP) and machine learning (ML) into whether (i) they extend the current state-ofthe-art by introduction of novel techniques which beat existing models or whether (ii) they mainly criticize the existing state-ofthe-art, i.e., that it is deficient with respect to some property (e.g., wrong evaluation, wrong datasets, misleading task specification). We refer to contributions under (i) as having a "positive stance" and contributions under (ii) as having a "negative stance" to related work. We annotate over 2k papers from NLP and ML to train a SciBERT based model to automatically predict the stance of a paper based on its title and abstract. We then analyze large-scale trends on over 41k papers from the last ∼35 years in NLP and ML, finding that papers have gotten substantially more positive over time, but negative papers also got more negative and we observe considerably more negative papers in recent years. Negative papers are also more influential in terms of citations they receive.1 This concept is related to positive/negative citations within a paper, which has been annotated in a few works, e.g., Teufel et al. (2006). Our work goes beyond individual citations and assesses the stance of the authors' main message.

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Section: Related Workmentioning

confidence: 99%

Detecting Stance in Scientific Papers: Did we get more Negative Recently?

Beese¹,

Begüm²,

Güzeler³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Detention research themes and creation of two-dimensional strategic diagrams. First, the tool generates the equivalence index to detect the research themes [54]. Then, SciMAT uses the single-centre algorithm [55] to detect the most relevant topics.…”

Section: Bibliometric Analysis: Science Mapping and Performance Analysismentioning

confidence: 99%

Analysis of the Scientific Evolution of the Circular Economy Applied to Construction and Demolition Waste

et al. 2021

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The circular economy (CE) concept applied to construction and demolition waste (CDW) is a developing field of research that entails a large amount of complex and disjointed information; thus, a comprehensive review of scientific contributions could provide a completed perspective. This article aims to analyse the existing knowledge of CE research applied to CDW, using a double integrated analysis, a systematic literature review and a bibliometric analysis. For this purpose, Science Mapping Analysis Tool (SciMAT), a software for the analysis of performance indicators and visualisations of scientific maps, has been used, which offers a complete approach to the field and evaluates the most cited and productive authors and subject areas related to this discipline. The results obtained from the 1440 bibliographic records from 1993 to 2020 show a still-developing scientific field, evolving from concerns about economic aspects to the most recent progresses in the evaluation of sustainable deconstruction. This work will contribute to the existing body of knowledge by establishing connections, mapping networks of researchers and recommending new trends.

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“…For example, systematic reviews in the field of research in codes of ethics analyze between 14 and 107 publications, (ii) the results obtained may be biased because they tend to reflect the authors’ subjective point of view. On the contrary, bibliometric methods allow us to work with a large number of publications, being more suitable for recognizing the intellectual structure of a field of knowledge (Jebari et al., 2021). These methodologies introduce quantitative rigor in the subjective evaluation of scientific literature.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Exploring the intellectual structure of research in codes of ethics: A bibliometric analysis

Delgado-Alemany

Blanco‐González

Diéz‐Martín

2021

Business Ethics Env & Resp

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In this study, we map the intellectual structure of the code of ethics research field by means of a co‐citation bibliometric analysis. To date, this type of analysis is absent from the literature on codes of ethics. Previous literature reviews have clarified definitions, studied contents, and analyzed the effectiveness of codes of ethics. However, the qualitative nature of these reviews does not resolve fundamental issues for understanding the evolution and status of this research field. This study contributes to the field by providing a bibliometric review in which the main research areas, sources of knowledge, trends, interrelationships, and dissemination paths of the domain are shown. Our findings reveal four main lines of research in the field of codes of ethics: corporate agent behavior with respect to codes of ethics, content analysis, effectiveness of codes of ethics, and employees’ attitudes toward codes of ethics. We also show that the study of the contents of codes of ethics is the main connecting bridge in this area of knowledge. Finally, we identify upcoming research topics in the field such as cultural change, the defensive nature of codes of ethics, and the application of organizational theories to code analysis.

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The use of citation context to detect the evolution of research topics: a large-scale analysis

Cited by 17 publications

References 59 publications

Detecting Stance in Scientific Papers: Did we get more Negative Recently?

Detecting Stance in Scientific Papers: Did we get more Negative Recently?

Analysis of the Scientific Evolution of the Circular Economy Applied to Construction and Demolition Waste

Exploring the intellectual structure of research in codes of ethics: A bibliometric analysis

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