1,721,001 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
Nuisance hardened data compression for fast likelihood-free inference
No full textInternational audienceWe show how nuisance parameter marginalized posteriors can be inferred directly from simulations in a likelihood-free setting, without having to jointly infer the higher dimensional interesting and nuisance parameter posterior first and marginalize a posteriori. The result is that for an inference task with a given number of interesting parameters, the number of simulations required to perform likelihood-free inference can be kept (roughly) the same irrespective of the number of additional nuisances to be marginalized over. To achieve this, we introduce two extensions to the standard likelihood-free inference set-up. First, we show how nuisance parameters can be recast as latent variables and hence automatically marginalized over in the likelihood-free framework. Secondly, we derive an asymptotically optimal compression from N data to n summaries – one per interesting parameter - such that the Fisher information is (asymptotically) preserved, but the summaries are insensitive to the nuisance parameters. This means that the nuisance marginalized inference task involves learning n interesting parameters from n ‘nuisance hardened’ data summaries, regardless of the presence or number of additional nuisance parameters to be marginalized over. We validate our approach on two examples from cosmology: supernovae and weak-lensing data analyses with nuisance parametrized systematics. For the supernova problem, high-fidelity posterior inference of Ω_m and w_0 (marginalized over systematics) can be obtained from just a few hundred data simulations. For the weak-lensing problem, six cosmological parameters can be inferred from just || simulations, irrespective of whether 10 additional nuisance parameters are included in the problem or not
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Bayesian analysis of weak gravitational lensing
Get PDFThis thesis is concerned with how to extract cosmological information from observations of weak gravitational lensing – the modification of observed galaxy images due to gravitational lensing by the large-scale structure of the Universe.
Firstly, we are concerned with how we can use all possible observa- tional probes of weak lensing to squeeze out as much cosmological information as possible from future surveys. Up until now, the tra- ditional approach to cosmological weak lensing analyses have focused on the distortion of shapes of distant galaxies measured across the sky – cosmic shear. However, shearing of galaxy shapes is only half the picture – weak lensing also magnifies the sizes and fluxes of observed objects and this lensing magnification field contains the same cosmo- logical information as the cosmic shear field, whilst being subject to a different set of systematic effects. As such, weak lensing magnifica- tion is an exciting complement to cosmic shear and a holistic approach to weak lensing, combining shear and magnification, promises tighter constraints on cosmology, better control of systematics, and more ro- bust science at the end-of-the-day. We develop the theoretical and statistical formalism for performing a cosmological weak lensing anal- ysis using shape, size and flux information together and demonstrate that significant information gains and synergies can be expected from the addition of this new lensing observable – cosmic magnification.
Secondly, we are interested in how we can use the statistics of the lensing fields to constrain cosmology via an analysis that is prin- cipled in its propagation of uncertainties, optimal in its use of the full information-content of the data, and exact under clearly stated
and well understood model assumptions. We introduce a totally fresh perspective on weak lensing data analysis – Bayesian hierar- chical modelling (BHM) – that promises to achieve all of these goals. The BHM approach provides a general framework for analysing weak lensing data that accounts for the full statistical interdependency of all model components in the weak lensing analysis pipeline, allowing information to flow freely from (in principle) raw pixel and photo- metric data through to cosmological inferences. We develop efficient Bayesian sampling schemes that explore the joint posterior of the shear maps and power spectra (and cosmological parameters) from a catalogue of estimated shapes and redshifts. We demonstrate that these algorithms bring the benefits of the Bayesian approach whilst being computationally practical for current and future surveys, and are readily extendable to extract information beyond the two-point statistics of the lensing fields or to incorporate the full weak lensing pipeline in a global principled analysis, presenting significant advan- tages over traditional estimator-based methods. We apply the newly developed Bayesian hierarchical approaches to the current state-of- the-art cosmic shear data from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS), constraining cosmological parameters and models from weak lensing using Bayesian hierarchical inference – the first application to weak lensing data.Open Acces
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