The European Journal of Operational Research (EJOR) published its first issue in 1977. This paper presents a general overview of the journal over its lifetime by using bibliometric indicators. We discuss its performance compared to other journals in the field and identify key contributing countries/ institutions/ authors as well as trends in research topics based on the Web of Science Core Collection database. The results indicate that EJOR is one of the leading journals in the area of operational research (OR) and management science (MS), with a wide range of authors from institutions and countries from all over the world publishing in it. Graphical visualization of similarities (VOS) provides further insights into how EJOR links to other journals and how it links researchers across the globe.

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Since the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems published its first issue in 1993, it has made important contributions to the research field of computer science. In this study, based on the dataset of the publications published in this journal between 1993 and 2016 retrieved from Web of Science, a general overview of this journal is performed using bibliometric methods and visualized networks. First, the productive and influential publications, authors, institutions, countries/territories, and supraregions are analysed based on the total number of citations, publications, and different citation thresholds. Second, network visualization analysis is applied to illustrate the links and connections between terms by using the VOSviewer software. Moreover, the most cited journals and common author keywords of three continents, including North America, Europe, and Asia, are also presented. This paper will hopefully help researchers understand the research patterns of this journal.

Despite their importance for stakeholders in the criminal justice system, few methods have been developed for determining which criminal behavior variables will produce accurate sentence predictions. Some approaches found in the literature resort to techniques based on indirect variables, but not on the social network behavior with exception of the work of Baker and Faulkner [ASR 58: 837–860, 1993]. Using information on the Caviar Network narcotics trafficking group as a real-world case, we attempt to explain sentencing outcomes employing the social network indicators. Specifically, we report the ability of centrality measures to predict a) the verdict (innocent or guilty) and b) the sentence length in years. We show that while the set of indicators described by Baker and Faulkner yields good predictions, introduction of the additional centrality measures generates better predictions. Some ideas for orienting future research on further improvements to sentencing outcome prediction are discussed.A pesar de la importancia para diferentes actores involucrados en el sistema judicial, se han desarrollados pocos métodos para determinar las variables del comportamiento organizado que permiten predecir las sentencias judiciales de redes criminales. Algunas aproximaciones encontradas en la literatura especializada usa variables indirectas al comportamiento organizado y no en el comportamiento en red de estas organizaciones. Nosotros usamos información real sobre un caso de red criminal real que operó en Montreal (Canadá) y analizamos la comunicación entre los miembros de la red para determinar si su comportamiento comunicacional permite predecir el veredicto así como los años de sentencia. Encontramos que los modelos de regresión obtenidos y las variables de centralidad nodal utilizadas por nosotros logra un mejor capacidad predictiva. Finalmente, se discuten algunas ideas dirigidas a mejorar la predicción de sentencias judiciales desde las medidas de redes sociales

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