Chilean sport sciences scientific production indexed in the Web of Science (1981-2016)

9 p.Objetivo: realizar un análisis bibliométrico de la producción científica chilena de Ciencias del deporte indexada en la Web of Science hasta 2016. Métodos: se analizaron los artículos y revisiones de Ciencias del deporte de Chile incluidos en los índices de la Colección principal de Web of Science hasta 2016. Los datos se recopilaron y filtraron en el programa Endnote X6 y luego se exportaron a Excel 2013, Bibexcel e Histcite para su análisis. La bibliometría se centró en la productividad, los sujetos y los patrones de colaboración. Resultados: Se encontraron un total de 152 documentos publicados desde 1981 hasta 2016. Las ciencias de la vida fueron el área de investigación principal (104), mientras que la fisiología (36) y la teoría del entrenamiento deportivo (30) fueron los sujetos más representados. La media de autores por artículo fue de 5,26 y el porcentaje de colaboración estuvo principalmente entre el 94% y el 100%. Ramírez-Campillo fue el autor más prolífico (24) y Caniuqueo logró el mayor índice de colaboración (10.83). Se descubrieron dos redes, con 20 y 10 académicos respectivamente y que representan 19 instituciones diferentes. Un grupo de 53 revistas diferentes ha difundido publicaciones de Ciencias del Deporte de Chile, pero 12 de ellas recolectaron el 60.53% de la producción total. Conclusión: la producción científica chilena de Ciencias del Deporte indexada en la Web of Science muestra el desarrollo progresivo y el fortalecimiento de este campo del conocimiento, claramente orientado a las Ciencias de la Vida, el trabajo en equipo y la colaboración internacional. También se debe destacar el establecimiento de una red que incluye académicos de Australia, Brasil, Canadá, Chile y España, que está impulsando la investigación de Ciencias del Deporte en este paísS

The use of bibliometrics for assessing research : possibilities, limitations and adverse effects

Researchers are used to being evaluated: publications, hiring, tenure and funding decisions are all based on the evaluation of research. Traditionally, this evaluation relied on judgement of peers but, in the light of limited resources and increased bureaucratization of science, peer review is getting more and more replaced or complemented with bibliometric methods. Central to the introduction of bibliometrics in research evaluation was the creation of the Science Citation Index (SCI)in the 1960s, a citation database initially developed for the retrieval of scientific information. Embedded in this database was the Impact Factor, first used as a tool for the selection of journals to cover in the SCI, which then became a synonym for journal quality and academic prestige. Over the last 10 years, this indicator became powerful enough to influence researchers’ publication patterns in so far as it became one of the most important criteria to select a publication venue. Regardless of its many flaws as a journal metric and its inadequacy as a predictor of citations on the paper level, it became the go-to indicator of research quality and was used and misused by authors, editors, publishers and research policy makers alike. The h-index, introduced as an indicator of both output and impact combined in one simple number, has experienced a similar fate, mainly due to simplicity and availability. Despite their massive use, these measures are too simple to capture the complexity and multiple dimensions of research output and impact. This chapter provides an overview of bibliometric methods, from the development of citation indexing as a tool for information retrieval to its application in research evaluation, and discusses their misuse and effects on researchers’ scholarly communication behavior

Influence maximization for dynamic allocation in voter dynamics

In this paper, we study the competition between external controllers with fixed campaign budgets in which one of the controllers attempts to maximize the share of a desired opinion in a group of agents who exchange opinions on a social network subject to voting dynamics. In contrast to allocating all the budgets at the beginning of the campaign, we consider a version of a temporal influence maximization problem, where the controller has the flexibility to determine when to start control. We then explore the dependence of optimal starting times to achieve maximum vote shares at a finite time horizon on network heterogeneity. We find that, for short time horizons, maximum influence is achieved by starting relatively later on more heterogeneous networks than in less homogeneous networks, while the opposite holds for long time horizons