2,143 research outputs found
The scientific influence of nations on global scientific and technological development
Determining how scientific achievements influence the subsequent process of
knowledge creation is a fundamental step in order to build a unified ecosystem
for studying the dynamics of innovation and competitiveness. Relying separately
on data about scientific production on one side, through bibliometric
indicators, and about technological advancements on the other side, through
patents statistics, gives only a limited insight on the key interplay between
science and technology which, as a matter of fact, move forward together within
the innovation space. In this paper, using citation data of both research
papers and patents, we quantify the direct influence of the scientific outputs
of nations on further advancements in science and on the introduction of new
technologies. Our analysis highlights the presence of geo-cultural clusters of
nations with similar innovation system features, and unveils the heterogeneous
coupled dynamics of scientific and technological advancements. This study
represents a step forward in the buildup of an inclusive framework for
knowledge creation and innovation
Disruption indices and their calculation using web-of-science data:Indicators of historical developments or evolutionary dynamics?
Science and technology develop not only along historical trajectories, but also as next-order regimes that periodically change the landscape. Regimes can incur on trajectories which are then disrupted. Using citations and references for the operationalization, we discuss and quantify both the recently proposed “disruption indicator” and the older indicator for “critical transitions” among reference lists as changes which may necessitate a rewriting of history. We elaborate this with three examples in order to provide a proof of concept. We shall show how the indicators can be calculated using Web-of-Science data. The routine is automated (available at ) so that it can be upscaled in future research. We suggest that “critical transitions” can be used to indicate disruption at the regime level, whereas disruption is developed at the trajectory level. Both conceptually and empirically, however, continuity is grasped more easily than disruption
Breaking down the relationship between academic impact and scientific disruption
We examine the tension between academic impact - the volume of citations received by publications - and scientific disruption. Intuitively, one would expect disruptive scientific work to be rewarded by high volumes of citations and, symmetrically, impactful work to also be disruptive. A number of recent studies have instead shown that such intuition is often at odds with reality. In this paper, we break down the relationship between impact and disruption with a detailed correlation analysis in two large data sets of publications in Computer Science and Physics. We find that highly disruptive papers tend to be cited at higher rates than average. Contrastingly, the opposite is not true, as we do not find highly impactful papers to be particularly disruptive. Notably, these results qualitatively hold even within individual scientific careers, as we find that - on average - an author's most disruptive work tends to be well cited, whereas their most cited work does not tend to be disruptive. We discuss the implications of our findings in the context of academic evaluation systems, and show how they can contribute to reconcile seemingly contradictory results in the literature
Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)
Opinion mining and sentiment analysis has become ubiquitous in our society, with
applications in online searching, computer vision, image understanding, artificial intelligence and
marketing communications (MarCom). Within this context, opinion mining and sentiment analysis
in marketing communications (OMSAMC) has a strong role in the development of the field by
allowing us to understand whether people are satisfied or dissatisfied with our service or product
in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To
the best of our knowledge, there is no science mapping analysis covering the research about opinion
mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science
mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work
during the last two decades in this interdisciplinary area and to show trends that could be the basis
for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer
and InCites based on results from Web of Science (WoS). The results of this analysis show the
evolution of the field, by highlighting the most notable authors, institutions, keywords,
publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La
reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la
Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐
FEDERJA‐148)” and The APC was funded by the same research gran
Citation advantage of COVID-19 related publications
With the global spread of the COVID-19 pandemic, scientists from various
disciplines responded quickly to this historical public health emergency. The
sudden boom of COVID-19 related papers in a short period of time may bring
unexpected influence to some commonly used bibliometric indicators. By a
large-scale investigation using Science Citation Index Expanded and Social
Sciences Citation Index, this brief communication confirms the citation
advantage of COVID-19 related papers empirically through the lens of Essential
Science Indicators' highly cited paper. More than 8% of COVID-19 related papers
published during 2020 and 2021 were selected as Essential Science Indicators
highly cited papers, which was much higher than the set global benchmark value
of 1%. The citation advantage of COVID-19 related papers for different Web of
Science categories/countries/journal impact factor quartiles were also
demonstrated. The distortions of COVID-19 related papers' citation advantage to
some bibliometric indicators such as journal impact factor were discussed at
the end of this brief communication.Comment: Journal of Information Science (2023
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