1,721,012 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

    Performance Evaluation of Algorithms for Newspaper Article Identification.

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    A typical modern newspaper recognition system operates in distinct phases: i) page segmentation (also called page decomposition or zoning), that is the process of decomposing a page into its structural and logical units (called regions or zones), ii) region (or zone) labeling, where the previously identified units are labeled according to their types (title, text, images, and lines), iii) article identification (or tracking or clustering), in which all the units that belong to a single article are clustered together, and iv) read order identification, in which each item in an article is assigned its reading order inside the article. So far, in the literature, several works appeared describing algorithms and metrics for the first two phases, i.e. page segmentation and region labeling, that indeed play a crucial role in the whole process, however, few results focused on article identification, that is a difficult task mainly due to the rich and complex variety of newspapers layouts. In this paper we propose a methodology to evaluate news-papers article identification algorithms, our approach is based on well-established tools from graph theory: in particular, we reduce the newspaper article clustering problem to a specific graph clustering problem, that is therefore evaluated using the appropriate coverage and performance measures. The advantages of our approach are twofold: on one side, the proposed measures correctly detects that not all the errors are equals, i.e. some errors are worse than others, and the scores are assigned properly. On the other side, we show how to reverse the reduction, in order to exploit the large number of graph clustering algorithm available: indeed, given a graph clustering algorithm, to obtain a full working newspaper article identification algorithm we only need to define a similarity measure between units in the article. We provide some examples, using a specifically designed dataset. Finally, we would like to point out that both our dataset, together with its ground-truth base, and the software tool, that implements the proposed approach, are freely available

    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
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