Anatomy of a trending topic : Methods for the visualisation of retweet chains [Anatomie eines Trending Topics: Methoden zur Visualisierung von Retweet-Ketten]

Twitter and other social networking sites play an ever more present role in the spread of current events. The dynamics of information dissemination through digital network structures are still relatively unexplored, however. At what time an issue is taken up by whom? Who forwards a message when to whom else? What role do individual communication participants, existing digital communities or the technical foundations of each network platform play in the spread of news? In this chapter we discuss, using the example of a video on a current sociopolitical issue in Australia that was shared on Twitter, a number of new methods for the dynamic visualisation and analysis of communication processes. Our method combines temporal and spatial analytical approaches and provides new insights into the spread of news in digital networks. [Social media dienen immer häufger als Disseminationsmechanismen für Medieninhalte. Auf Twitter ermöglicht besonders die Retweet-Funktion den schnellen und weitläufgen Transfer von Nachrichten. In diesem Beitrag etablieren neue methodische Ansätze zur Erfassung, Visualisierung und Analyse von Retweet-Ketten. Insbesondere heben wir hervor, wie bestehende Netzwerkanalysemethoden ergänzt werden können, um den Ablauf der Weiterleitung sowohl temporal als auch spatial zu erfassen. Unsere Fallstudie demonstriert die verbreitung des videoclips einer am 9. Oktober 2012 spontan gehaltenen Wutrede der australischen Premierministerin Julia Gillard, in der sie Oppositionsführer Tony Abbott als Frauenhasser brandmarkte. Durch die Erfassung von Hintergrunddaten zu den jeweiligen NutzerInnen, die sich an der Weiterleitung des Videoclips beteiligten, erstellen wir ein detailliertes Bild des Disseminationsablaufs im vorliegenden Fall. So lassen sich die wichtigsten AkteurInnen und der Ablauf der Weiterleitung darstellen und analysieren. Daraus entstehen Einblicke in die allgemeinen verbreitungsmuster von Nachrichten auf Twitter].

Proceso acusatorio : ¿hashtag constitucional?

Resumen: El proceso penal de cuño acusatorio no solo es trending topic dada su inminente implementación, sino que también constituye el hashtag más representativo de una Constitución imbuida por el principio republicano de gobierno, la división de poderes y la premisa de no autocontrol. La imparcialidad miliaria de un sistema respetuoso de la separación de funciones (acusación, defensa, juicio) solo puede conquistarse en un modelo de este signo, que a través de otros principios potencia la expresión constitucional al máximum. Empero, un “derecho penal líquido” ligado umbilicalmente a un principio de oportunidad emparentado al modelo acusatorio, nos abre el camino hacia nuevos interrogantes sobre los peligros inherentes a una incertidumbre e inestabilidad normativa, que impedirían solidificar la ley en un bien perdurable. Es que el encumbramiento de una oportunidad oscurantista conduce a la banalización de la justicia, el imperio de la arbitrariedad y una selectividad vacua de contrapesos. De modo que, sin resortes aptos, los vasos capilares y derechos contenidos en la Constitución Nacional resultarán indefectiblemente afectados. Pues si el proceso penal no contempla mecanismos de coagulación eficaz, la liquidez caótica de la ley penal propenderá a desangrar y disolver la manifestación constitucional. Por tanto, el desafío de los ingenieros de los sistemas de administración de justicia consiste en ajustar los paradigmas procesales a los dictámenes de la Ley Materna, con el afán de que ese dar a cada uno lo suyo, definido por el bien común político, se vuelva realidad en cada intervención del Poder Judicial y permita superar falaces antinomias

Multimodal viral communication: a social semiotic analysis of the popular Spanish "Ola ke ase" meme

Multimodality – the interdependence of semiotic resources in text – is an existential element of today’s media. The term multimodality attends systematically to the social interpretation of a wide range of communicational forms used in meaning making. A primary focus of social- semiotic multimodal analysis is on mapping how modal resources are used by people in a given social context. In November 2012 the “Ola ke ase” catchphrase, which is a play on “Hola ¿qué hace?”, appeared for the first time in Spain and immediately has been adopted as a Twitter hashtag and an image macro series. Its viral spread on social networks has been tremendous, being a trending topic in various Spanish-speaking countries. The objective of analysis is how language and image work together in the “Ola ke ase” meme. The interplay between text and image in one of the original memes and some of its variations is quantitatively analysed applying a social-semiotic approach. Results demonstrate how the “Ola ke ase” meme functions through its multimodal character and the non-standard orthography. The spread of uncountable variations of the meme shows the social process that goes on in the meaning making of the semiotic elements.

Introducción a Blender

El mundo de la animación 3D está en plena actualidad en este momento. Salas de cine, programas de televisión y la publicidad nos muestran constantemente personajes y objetos animados creados por ordenador. Son muchos los programas que pueden usarse para la realización de animación en 3D. En este proyecto vamos a centrarnos en Blender. Blender es un programa de animación y modelado que se puede obtener de manera gratuita por internet. Se trata de un programa de software libre, por lo que constantemente está siendo modificado gracias a la aportación de usuarios anónimos por internet. El objetivo de este proyecto es la creación de un corto de animación de un minuto de duración con Blender, para lo cual serán necesarias una serie de pautas iniciales sobre cómo funciona Blender y sus posibilidades. La primera parte de este proyecto es una guía básica sobre Blender y sus características. Capítulo a capítulo se irán describiendo la interfaz del programa y la creación de objetos (modelado, asignación de materiales y texturas) para luego aprender a animarlos y a visualizarlos como imágenes o video. La segunda parte se centra en el corto MOL. Creado a partir de los conocimientos adquiridos en la guía anterior, añadiendo en algunos casos, nuevas propiedades necesarias para su elaboración. Se describirán cada uno de los elementos y su creación. Esta guía pretende ser un referente para aquel que quiera introducirse en el mundo de la animación 3D con Blender. The world of 3D animation is a trending topic nowadays. Cinema, television and advertising constantly show us characters and animated objects created with computer graphics. There are many programs that can be used to perform 3D animations. In this project we will focus on Blender. Blender is a modeling and animation program that is available for free online. Blender is an open source program, so it is constantly being modified and improved by anonymous online users. The objective of this project is to create a one-minute animation short with Blender, for which we will require an initial set of guidelines on how Blender works and its possibilities. The first part of this project is a basic guide and will only cover basic features of Blender. In each chapter we will describe the interface and how to create objects (modeling, assigning materials and textures) and then we will learn to animate these objects and to display them as images or video. The second part focuses on the short film MOL. Created from the knowledge gained in the previous guide adding, in same cases, new properties necessary for its creation. We will describe each of the elements involved in the making of. This guide is intended to be a referent guide for anyone who wants to enter the world of 3D animation with Blender.

A distributed knowledge management infrastructure based on a Topic Map grid

Modern enterprise knowledge management systems typically require distributed approaches and the integration of numerous heterogeneous sources of information. A powerful foundation for these tasks can be Topic Maps, which not only provide a semantic net-like knowledge representation means and the possibility to use ontologies for modelling knowledge structures, but also offer concepts to link these knowledge structures with unstructured data stored in files, external documents etc. In this paper, we present the architecture and prototypical implementation of a Topic Map application infrastructure, the ‘Topic Grid’, which enables transparent, node-spanning access to different Topic Maps distributed in a network.

Adaptive dual control of topic-based information retrieval

Information Retrieval is an important albeit imperfect component of information technologies. A problem of insufficient diversity of retrieved documents is one of the primary issues studied in this research. This study shows that this problem leads to a decrease of precision and recall, traditional measures of information retrieval effectiveness. This thesis presents an adaptive IR system based on the theory of adaptive dual control. The aim of the approach is the optimization of retrieval precision after all feedback has been issued. This is done by increasing the diversity of retrieved documents. This study shows that the value of recall reflects this diversity. The Probability Ranking Principle is viewed in the literature as the “bedrock” of current probabilistic Information Retrieval theory. Neither the proposed approach nor other methods of diversification of retrieved documents from the literature conform to this principle. This study shows by counterexample that the Probability Ranking Principle does not in general lead to optimal precision in a search session with feedback (for which it may not have been designed but is actively used). Retrieval precision of the search session should be optimized with a multistage stochastic programming model to accomplish the aim. However, such models are computationally intractable. Therefore, approximate linear multistage stochastic programming models are derived in this study, where the multistage improvement of the probability distribution is modelled using the proposed feedback correctness method. The proposed optimization models are based on several assumptions, starting with the assumption that Information Retrieval is conducted in units of topics. The use of clusters is the primary reasons why a new method of probability estimation is proposed. The adaptive dual control of topic-based IR system was evaluated in a series of experiments conducted on the Reuters, Wikipedia and TREC collections of documents. The Wikipedia experiment revealed that the dual control feedback mechanism improves precision and S-recall when all the underlying assumptions are satisfied. In the TREC experiment, this feedback mechanism was compared to a state-of-the-art adaptive IR system based on BM-25 term weighting and the Rocchio relevance feedback algorithm. The baseline system exhibited better effectiveness than the cluster-based optimization model of ADTIR. The main reason for this was insufficient quality of the generated clusters in the TREC collection that violated the underlying assumption.

Investigating the performance of automatic new topic identification across multiple datasets 1

Recent studies on automatic new topic identification in Web search engine user sessions demonstrated that neural networks are successful in automatic new topic identification. However most of this work applied their new topic identification algorithms on data logs from a single search engine. In this study, we investigate whether the application of neural networks for automatic new topic identification are more successful on some search engines than others. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that query logs with more topic shifts tend to provide more successful results on shift-based performance measures, whereas logs with more topic continuations tend to provide better results on continuation-based performance measures.

Effect of topic domain and task type on Web image searching

Many user studies in Web information searching have found the significant effect of task types on search strategies. However, little attention was given to Web image searching strategies, especially the query reformulation activity despite that this is a crucial part in Web image searching. In this study, we investigated the effects of topic domains and task types on user’s image searching behavior and query reformulation strategies. Some significant differences in user’s tasks specificity and initial concepts were identified among the task domains. Task types are also found to influence participant’s result reviewing behavior and query reformulation strategies.

Licensing age issues : deliberations from a workshop devoted to this topic

Objective: To highlight the issues and discuss the research evidence regarding safety, mobility, and other consequences of different licensing ages. Methods: Information included is based on presentations and discussions at a one-day workshop on licensing age issues, and a review and synthesis of the international literature. Results: The literature indicates that higher licensing ages are associated with safety benefits. There is an associated mobility loss, more likely to be an issue in rural states. Legislative attempts to raise the minimum age for independent driving in the United States, e.g., from 16 to 17, have been resisted, although in some states the age has been raised indirectly through graduated driver licensing (GDL) policies. Conclusions: Jurisdictions can achieve reductions in teenage crashes by raising the licensing age. This can be done directly, or indirectly by strengthening GDL systems, in particular extending the minimum length of the learner period.