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André Lhuillier, CSS PhD student. André’s talk entitled “Why Little Samson Didn’t Defeat The Hedgehog: A Story Of Social Influence And The Relevance Of Distribution For Successful Information Goods"
Abstract: In 1992 during one of the fiercest battles of the so called ‘console wars’, a modest game was released in the mist of the industry frenzy. Although ‘Little Samson’ is recognized by those who know it as a great game, it remains unknown for most of the consumers today. On the other side of the battlefield, Sega’s thriving Hedgehog was convincing everyone that they have seized their main competitor ‘Mario Kart’. Despite this momentary victory in consumer’s memory and affection, the real winner was not in the center of the industry’s attention. Having less media presence, the sequel of Super Mario Land for the Game Boy was the most purchased game with almost 200% units of what ‘Sonic 2’ sold. This kind of unpredictable and divergent behavior is a unique characteristic of information goods markets. In this presentation I survey the last 30 years of the video game sector and show its particular composition and evolution. Following De Vany’s approach to Hollywood movie industry I dwell into an analysis of this industry with special emphasis in consumer behavior. Re-visiting De Vany’s proposal I make a simple ABM approach to model and show how placement or distribution properties may induce long tail distributions. Following the relevance of information diffusion and the development of hype in this industry another model is presented. In this case the relevance of a consumer social system and its dynamics. After an analysis of the industry history, consumer’s social influence, sales and distribution/access is reviewed; I present several findings and propose a model to understand them. A final discussion will be opened with the presentation of data on Valve Company digital platform Steam.
Our bus company is from Atlanta, called "Star Coaches", every time we go there we eat a bunch of greasy food. This time we woke up, ate the greasy food and then we spent the whole day inside the bus, cleaning, taking photos, pretending we were driving... and then we tried to sleep a bit more.
Testing Mr Clayson's wonderful IE CSS discovery, with some quick changes.
All browsers get the basic version. IE7 (above) and modern browsers get the full CSS after that, but IE6 gets it's own special stylesheet.
Acadia was designed in Canada for the Hydrographic Survey of Canada and built by Swan Hunter & Wigham Richardson at Newcastle-on-Tyne in England. She was launched in May 1913 and made her first voyage in July 1913.
Live /Estragon @ Bologna.
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Christopher L. Barrett, Executive Director, Virginia Bioinformatics Institute/Professor of Computer Science, Virginia Tech. Dr. Barrett’s talk entitled “Massively Interactive Systems: Thinking and Deciding in the Age of Big Data"
Abstract: This talk discusses advanced computationally assisted reasoning about large interaction-dominated systems. Current questions in science, from the biochemical foundations of life to the scale of the world economy, involve details of huge numbers and levels of intricate interactions. Subtle indirect causal connections and vastly extended definitions of system boundaries dominate the immediate future of scientific research. Beyond sheer numbers of details and interactions, the systems are variously layered and structured in ways perhaps best described as networks. Interactions include, and often co-create, these morphological and dynamical features, which can interact in their own right. Such “massively interacting” systems are characterized by, among other things, large amounts of data and branching behaviors. Although the amount of associated data is large, the systems do not even begin to explore their entire phase spaces. Their study is characterized by advanced computational methods. Major methodological revisions seem to be indicated.
Heretofore unavailable and rapidly growing basic source data and increasingly powerful computing resources drive complex system science toward unprecedented detail and scale. There is no obvious reason for this direction in science to change. The cost of acquiring data has historically dominated scientific costs and shaped the research environment in terms of approaches and even questions. In the several years, as the costs of social data, biological data and physical data have plummeted on a per-unit basis and as the volume of data is growing exponentially, the cost drivers for scientific research have clearly shifted from data generation to storage and analytical computation-based methods. The research environment is rapidly being reshaped by this change and, in particular, the social and bio–sciences are revolutionized by it. Moreover, the study of socially– and biologically–coupled systems (e.g., societal infrastructures and infectious disease public health policy analysis) is in flux as computation-based methods begin to greatly expand the scope of traditional problems in revolutionary ways.
How does this situation serve to guide the development of “information portal technology” for complex system science and for decision support? An example of an approach to detailed computational analysis of social and behavioral interaction with physical and infrastructure effects in the immediate aftermath of a devastating disaster will be described in this context.