Author Correction: Unsupervised Scalable Statistical Method for Identifying Influential Users in Online Social Networks (Scientific Reports, (2018), 8, 1, (6955), 10.1038/s41598-018-24874-2)

The original version of this Article contained an error in Affiliation 3, which was incorrectly given as ‘Department of Mathematical Sciences, Universidad EAFIT, Universidad Nacional de Colombia, Medellín, Colombia’. The correct affiliation is listed below: Department of Mathematical Sciences, Universidad EAFIT, Medellín, Colombia This error has now been corrected in the HTML and PDF versions of the Article and in the accompanying Supplementary Material file. © 2019, The Author(s)

Unsupervised Scalable Statistical Method for Identifying Influential Users in Online Social Networks

Billions of users interact intensively every day via Online Social Networks (OSNs) such as Facebook, Twitter, or Google+. This makes OSNs an invaluable source of information, and channel of actuation, for sectors like advertising, marketing, or politics. To get the most of OSNs, analysts need to identify influential users that can be leveraged for promoting products, distributing messages, or improving the image of companies. In this report we propose a new unsupervised method, Massive Unsupervised Outlier Detection (MUOD), based on outliers detection, for providing support in the identification of influential users. MUOD is scalable, and can hence be used in large OSNs. Moreover, it labels the outliers as of shape, magnitude, or amplitude, depending of their features. This allows classifying the outlier users in multiple different classes, which are likely to include different types of influential users. Applying MUOD to a subset of roughly 400 million Google+ users, it has allowed identifying and discriminating automatically sets of outlier users, which present features associated to different definitions of influential users, like capacity to attract engagement, capacity to attract a large number of followers, or high infection capacity. © 2018 The Author(s)

Author Correction: Unsupervised Scalable Statistical Method for Identifying Influential Users in Online Social Networks

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.</jats:p

Investigaciones en administración y políticas públicas

El Estado aborda dicha planificación definiendo los fundamentos ideológicos- conceptuales en los cuales se enmarcará el plan, coordinando y dirigiendo el proceso y las acciones a seguir y convocando a los diversos actores de la sociedad. El objetivo del presente artículo es dar cuenta de dicha planificación estratégica, entendida como un proceso de elaboración de una política pública. Para ello se presentarán en un primer apartado las nuevas modalidades de gestión vinculadas a las nuevas demandas de las sociedades actuales en continuo crecimiento y transformación. Dentro de estas nuevas modalidades, se puede encontrar a la planificación estratégica, entendida como tecnología de gestión integrada por un conjunto de instrumentos que permiten mejorar las capacidades delosequipos de gestión en orden a realizar las operaciones gerenciales necesarias para generar mayores niveles de eficiencia yeficaci

Personal tributes to Mario Gerla

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