1,720,969 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    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

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    “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

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    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

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    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

    Author Index

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    FixJS: A Dataset of Bug-fixing JavaScript Commits

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    The field of Automated Program Repair (APR) has received increasing attention in recent years both from the academic world and from leading IT companies. Its main goal is to repair software bugs automatically, thus reducing the cost of development and maintenance significantly. Recent works use state-of-the-art deep learning models to predict correct patches, for these teaching on a large amount of data is inevitable almost in every scenarios. Despite this, readily accessible data on the field is very scarce. To contribute to related research, we present \emph{FixJS}, a dataset containing bug-fixing information of \textasciitilde 2 million commits. The commits were gathered from GitHub and processed locally to have both the buggy (before bug fixing commit) and fixed (after fix) version of the same program. We focused on JavaScript functions, as it is one of the most popular programming language globally and functions are first class objects there. The data includes more than 300,000 samples of such functions, including commit information, before/after states and 3 source code representations

    Feature level metrics based on size and similarity in software product line adoption

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    Introducing software product lines is a natural way to cope with a large number of software variants and hard maintenance. This task can become more complicated with a fourth generation language, namely Magic in our case. Feature extraction is an important task of product line adoption, and the extracted features can amount to large proportions of the code and can be hard to contemplate, thus appropriate methods become necessary to ease the handling of the information gained. In this work we present some feature level metrics aiming to highlight valuable information on both the results attained through extraction and the features themselves which can be used in furthering the process of product line adoption. We present some metrics based on size and pairwise similarity of the features of four different variants of the same system. The knowledge of these metrics, properly measured and used can be vital in aiding product line adoption

    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We 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
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