1,720,973 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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    Statistika penelitian(Analisis Manual dan IBM SPSS)

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    Buku ini disusun agar para pembaca memperoleh konsep yang kuat dan mampu menerapkan teknik analisa data kuantitatif secara manual sekaligus mampu membuktikannya melalui software IBM SPSS dalam mengambil suatu keputusan penelitian yang tepat dan akurat, buku ini memberikan penjelasan yang simple, mudah dipahami dan disertai dengan contoh-contoh aplikasi penelitian di lapangan

    Gender Di Mata Hakim Agama

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    Statistik SEM : Structural Equation Modeling Dengan Lisrel

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    LISREL adalah software statistik pintar yang mampu menyelesaikan berbagai macam analisis, seperti analisis Structural Equation Modeling (SEM) dan analisis jalur (path analysis) dengan tingkat akurasi yang tinggi. Buku ini diperuntukkan bagi para peneliti, lembaga-lembaga riset, mahasiswa program sarjana (S1) maupun pascasarjana (S2/S3). Melalui software LISREL ini, diharapkan dapat membantu dan mempermudah analisis data dengan model penelitian yang sekompleks apa pun. Buku ini menyajikan penjelasan bagaimana langkah-langkah menganalisis data penelitian model SEM (Structural Equation Modeling) menggunakan LISREL secara praktis dan simpel dengan penjelasan yang mudah dipahami. Secara ringkas, materi dalam buku ini meliputi: · Kajian Teoretis SEM, Ukuran Sampel (Sample Size), Spesifikasi Model Persamaan Struktural, Identifikasi Model Persamaan Struktural, dan Metode Estimasi. · Persiapan Instalasi Software, Operasionalisasi LISREL, Menu PRELIS Data, Menu SIMPLIS Project, Menu Syntax Only, Menu LISREL Project, dan Menu Path Diagram. · Interpretasi output estimasi LISREL, di antaranya: Ukuran Kecocokan Model (Goodness of Fit), Perhitungan Koefisien Pengaruh Langsung, Pengaruh Tidak Langsung, dan Pengaruh Total. · Modifikasi Model SEM, Bentuk Model 2nd Order CFA, SIMPLIS Model 2nd Order CFA, Mengatasi Error Message (Heywood Cases), dan Interpretasi Model 2nd Order CFA. · Menyusun Skor Variabel Laten, SIMPLIS Skor Variabel Laten. · Analisis SEM Multisample, Analisis SEM Multisample Keseluruhan, Analisis SEM Multi Sampel Parsial (Baseline), Multisample dengan Parameter Ditetapkan Sama, dan Multisample dengan Parameter Berbeda. · Analisis SEM dengan Data Dikotomis dan Interpretasi Output Estimasi. · Contoh Aplikasi SEM dengan 6 Variabel Laten dan Contoh Aplikasi SEM dengan 8 Variabel Laten, dimulai dari penentuan ukuran sampel, Spesifikasi Model, Metode Estimasi, Hipotesis Penelitian, dan Pembahasan secara komprehensif
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