Review of: "ScientoMiner ICR - the Gephi plugin for importing scholarly citations data from Crossref services"
نویسندگان
چکیده
منابع مشابه
Purposeful Searching for Citations of Scholarly Publications
Citation data contains the citations among scholarly publications. The data can be used to find relevant sources during research, identify emerging trends and research areas, compute metrics for comparing authors or journals, or for thematic clustering. Manual administration of citation data is limited due to the large number of publications. In this work, we hence lay the foundations for the a...
متن کاملSemantic Annotation of Scholarly Documents and Citations
Scholarly publishing is in the middle of a revolution based on the use of Web-related technologies as medium of communication. In this paper we describe our ongoing study of semantic publishing and automatic annotation of scholarly documents, presenting several models and tools for the automatic annotation of structural and semantic components of documents. In particular, we focus on citations ...
متن کاملCharacterising Citations in Scholarly Articles: An Experiment
This work presents some experiments in letting humans annotate citations according to CiTO, an OWL ontology for describing the function of citations. We introduce a comparison of the performance of different users, and show strengths and difficulties that emerged when using that particular model to characterise citations of scholarly articles.
متن کاملIdentifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact
Evaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation-based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause unfairness and inaccuracy to the article impact evaluation. In this study, in order to discover the...
متن کاملDyCoNet: A Gephi Plugin for Community Detection in Dynamic Complex Networks
Community structure detection has proven to be important in revealing the underlying organisation of complex networks. While most current analyses focus on static networks, the detection of communities in dynamic data is both challenging and timely. An analysis and visualisation procedure for dynamic networks is presented here, which identifies communities and sub-communities that persist acros...
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ژورنال
عنوان ژورنال: Qeios
سال: 2020
ISSN: 2632-3834
DOI: 10.32388/9lzbat