1,720,982 research outputs found
The shape of economics before and after the financial crisis
This paper investigates the impact of the global financial crisis on the
shape of economics as a discipline by analyzing EconLit-indexed journals from
2006 to 2020 using a multilayer network approach. We consider two types of
social relationships among journals, based on shared editors (interlocking
editorship) and shared authors (interlocking authorship), as well as two forms
of intellectual proximity, derived from bibliographic coupling and textual
similarity. These four dimensions are integrated using Similarity Network
Fusion to produce a unified similarity network from which journal communities
are identified. Comparing the field in 2006, 2012, and 2019 reveals a high
degree of structural continuity. Our findings suggest that, despite changes in
research topics after the crisis, fundamental social and intellectual
relationships among journals have remained remarkably stable. Editorial
networks, in particular, continue to shape hierarchies and legitimize knowledge
production
Fine-grained classification of journal articles by relying on multiple layers of information through similarity network fusion: the case of the Cambridge Journal of Economics
This paper explores the possibility of classifying journal articles by exploiting multiple information sources, instead of relying on only one information source at a time. In particular, the Similarity Network Fusion (SNF) technique is used to merge the different layers of information about articles when they are organized as a multiplex network. The method proposed is tested on a case study consisting of the articles published in the Cambridge Journal of Economics. The information about articles is organized in a two-layer multiplex where the first layer contains similarities among articles based on the full-text of articles, and the second layer contains similarities based on the cited references. The unsupervised similarity network fusion process combines the two layers by building a new single-layer network. Distance correlation and partial distance correlation indexes are then used for estimating the contribution of each layer of information to the determination of the structure of the fused network. A clustering algorithm is lastly applied to the fused network for obtaining a classification of articles. The classification obtained through SNF has been evaluated from an expert point of view, by inspecting whether it can be interpreted and labelled with reference to research programs and methodologies adopted in economics. Moreover, the classification obtained in the fused network is compared with the two classifications obtained when cited references and contents are considered separately. Overall, the classification obtained on the fused network appears to be fine-grained enough to represent the extreme heterogeneity characterizing the contributions published in the Cambridge Journal of Economics
A Monte Carlo integration approach to Horvitz-Thompson estimation in replicated environmental designs
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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