1,720,955 research outputs found
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
ANALYSIS STUDENT EMOTIONS AND MENTAL HEALTH ON CUMULATIVE GPA USING MACHINE LEARNING AND SMOTE
This research investigates the impact of emotions and mental health on students' cumulative grade point average (CGPA) using machine learning classification algorithms while addressing data imbalances with the Synthetic Minority Oversampling Technique (SMOTE). Emotional well-being and mental health are acknowledged as vital determinants of academic achievement. Data imbalance, particularly in mental health metrics such as anxiety and depression, frequently compromises forecast accuracy. This study improves the accuracy of CGPA prediction based on emotional and mental health factors by utilizing SMOTE in machine learning models such as logistic regression and random forest. A dataset including 226 university students, including academic records and self-reported mental health evaluations, was evaluated. The random forest model attained an accuracy of 87.63%, exceeding the logistic regression model's accuracy of 86.56%. These findings emphasize the significant role of emotions and mental health in academic outcomes and validate SMOTE’s efficacy in addressing class imbalance. This work offers a fresh technique in educational data mining by revealing the possibility for improved academic achievement forecasts based on psychological characteristics, helping to the development of targeted therapies for students experiencing emotional issues. Implications for educational policy emphasize the significance of mental health support systems in promoting academic achievement. Subsequent research should investigate supplementary psychological variables and comprehensible models to improve predictive accuracy and facilitate evidence-based policymaking
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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
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
PENINGKATAN MODEL ASOSIASI TOKO IKHSAN MENGGUNAKAN ALGORITMA FP-GROWTH
FP-Growth, Data Mining, Purchase Patterns, Marketing Strategies, Retail Store
PENERAPAN ALGORITMA K-MEANS CLUSTERING UNTUK ANALISIS KINERJA PENGIRIMAN PAKET SHOPEE EXPRESS DI HUB TRANSIT KEDAWUNG
Penelitian ini bertujuan menganalisis kinerja pengiriman Shopee Express (SPX) di Hub Transit Kedawung menggunakan algoritma K-Means Clustering. Data sebanyak 359 pengiriman dengan 12 atribut dikumpulkan dari operator SPX. Model Knowledge Discovery in Databases (KDD) digunakan dalam penelitian, meliputi pemilihan data, pra-pemrosesan, transformasi, penerapan algoritma K-Means, dan evaluasi model menggunakan Davies-Bouldin Index (DBI). Tahapan pra-pemrosesan mencakup pembersihan data, pemilihan atribut relevan, dan normalisasi data, sementara transformasi dilakukan untuk mengubah atribut nominal menjadi numerik. Hasil evaluasi menunjukkan nilai DBI terbaik sebesar 0.288 dengan jumlah cluster optimal K = 10. Cluster 4 dan Cluster 6 menunjukkan performa terbaik dengan pengiriman tercepat, sedangkan Cluster 7 dan Cluster 9 memiliki tingkat on-hold tertinggi, disebabkan penerima tidak tersedia atau alamat tidak valid. Atribut seperti Driver ID, Zone ID, dan On-hold Reason menjadi faktor signifikan dalam pengelompokan. Penelitian ini memberikan wawasan bagi manajemen logistik SPX untuk meningkatkan efisiensi operasional dengan strategi seperti optimalisasi rute, peningkatan SOP, dan validasi alamat. Hasilnya diharapkan menjadi dasar untuk penerapan lebih lanjut algoritma clustering dalam manajemen logistik skala besar
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