1,721,014 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
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
Synthetic network generation with realistic cluster connectivity
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo termsThe student, Lahari Anne, accepted the attached license on 2025-03-20 at 21:48.The student, Lahari Anne, submitted this Thesis for approval on 2025-03-20 at 22:07.This Thesis was approved for publication on 2025-03-24 at 10:55.DSpace SAF Submission Ingestion Package generated from Vireo submission #21686 on 2025-10-19 at 18:09:11Evaluating the effectiveness of community detection methods is challenging due to the scarcity of real-world networks with known ground-truth communities. To address this, synthetic networks with predefined communities serve as valuable benchmarks. Among various synthetic network generators, Stochastic Block Models (SBMs) are widely used as they can approximate real-world network properties when provided with input parameters derived from real-world networks. However, SBMs often generate disconnected clusters, even when the input clustering exhibits fully connected communities, leading to structural inconsistencies that may affect the accuracy of performance evaluations for community detection algorithms. In this study, we introduce the REalistic Cluster Connectivity Simulator (RECCS), a post-processing framework designed to enhance SBM-generated networks by improving their fit to the cluster edge connectivity observed in real-world networks. RECCS modifies the synthetic network structure to better capture intra-cluster connectivity while preserving other essential network and clustering properties. This approach is evaluated on large-scale real-world networks containing up to 13.9 million nodes. The results show that RECCS generally improves the alignment of synthetic networks with empirical cluster connectivity, with some minimal trade-offs observed in other network properties. These findings suggest that RECCS offers a useful solution for generating synthetic benchmarks that more closely reflect real-world community structures, highlighting both its potential and limitations for community detection research
A comparison of community search with community detection
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo termsThe student, Vidya Kamath Pailodi, accepted the attached license on 2024-04-12 at 18:34.The student, Vidya Kamath Pailodi, submitted this Thesis for approval on 2024-04-12 at 19:08.This Thesis was approved for publication on 2024-04-25 at 14:00.DSpace SAF Submission Ingestion Package generated from Vireo submission #20390 on 2024-09-16 at 00:34:07Clustering is a widely used technique to study the topological features of complex real-world networks. Community detection is a commonly used method that uses a top-down graph partitioning approach to often find disjoint subsets. These methods often produce a large fraction of singleton clusters, and the clusters do not typically form well-connected communities. They also face the resolution limit problem, which fails to identify communities of smaller sizes. Moreover, many of these methods cannot handle large networks. Recently, many studies have discussed the advantages of an efficient bottom-up approach called "Community Search", which extracts a community around a particular node of interest. In this thesis, we compare the Iterative K-Core (IKC) community detection algorithm and the Community Search k-core (CSK) method based on the principle of the minimum degree of a node in a cluster. A comparative study is conducted to discuss the advantages of the CSK method in addressing the limitations of community detection by applying these methods to a large scientific network of 14 million documents in exosome research, namely, the Curated Exosome Network (CEN). Our results demonstrate that the CSK extracts larger clusters than the IKC method for a given query node and are well-connected. CSK extracts more number of distinct clusters than IKC, and the extracted clusters typically overlap. Moreover, CSK allows a node to be part of multiple communities. Cluster quality metrics such as conductance, connectivity, and modularity showed correlations with CSK cluster sizes, which were not observed for IKC clusters. Finally, preliminary observations suggest that clustering based on topological features correlates with thematic similarity. Our observations suggest that CSK can be advantageous in generating cohesive clusters of varying sizes and cluster qualities, and helpful in exploring the topological structure surrounding a seed node in a complex real-world network
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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