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See the blog post for more info: SXSW 2005 Wrap-Up
This photo is licensed under a Creative Commons license. If you use this photo, please list the photo credit as "Scott Beale / Laughing Squid" and link the credit to laughingsquid.com.
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.
A National Historic Site, this survey vessel built in 1913 helped map much of the east coast of Canada, as well as the Arctic, and Hudson's Bay. It served in the Canadian Navy in both WWI and WWII, and is the only remaining Canadian ship to have done so.
INDIO, CA UNITED STATES - APRIL 17: (L to R) Lovefoxxx of CSS is photographed on April 17, 2011 at Coachella in Indio, CA (Photo by Wendy Redfern/Redferns)
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.
About Colin Walcott | Collin Walcott | Colin resides in Toronto, Canada - His occupation is a User Experience Designer (UX/UI) for Applications and Devices supported on Web and Multiple Mobile Platforms. Skill set covers front end issues with design, wireframe Application screens & flows, generate HTML, CSS, animation, workflows, navigation, icons and creative for applied use. Colin's extracurricular interests exist in Post production for Video, audio editing and mastering tracks, Photography, 2D/3D and Music (trombone). View Colin Walcott's professional profile on LinkedIn - collin Collin+Walcott Colin+Walcott
Ovi Chris Rouly, Ph.D. Candidate,Department of Computational Social Science, George Mason University. Chris’s talk entitled “At The Root Of Sociality: Working Towards Emergent, Permanent, Social Affines"
Abstract: Complexity science often uses generative models to study and explain the emergent behavior of humans, human culture, and human patterns of social organization. In spite of this, little is actually known about how the lowest levels of human social organization came into being. That is, little is actually known about how the earliest members of our hominini tribe transitioned from being presumably small-groups of ape-like polygynous/promiscuous individuals (beginning perhaps with Ardipithecus or Australopithecus after the time of the Pan-Homo split in the late Pliocene to early Pleistocene eras) into family units having stable breeding-bonds, extended families, and clans. What were the causal mechanisms (biological, possibly cognitive, social, and environmental, etc.) that were responsible for the conversion? To confound the issue, it is also possible the conversion process itself was a complex system replete with input sensitivities and path dependencies i.e., a nested complex system. One author has referred to similar processes and their distinctive social arrangements as, “the deep structure of society” (Chapais, 2010). This paper reviews ongoing research attempting to model-then-understand a few of the underlying social, environmental, and biological systems present at the root of human sociality.
thanks a bunch card set... click over to the blog to see a little treat bag as well: justmeprints.blogspot.ca/2012/11/thanks-bunch-css-release...
@ XOYO, 23rd August
The light was terrible for photos and I only had my compact. And that's my excuse :p @ XOYO, 23rd August
The light was terrible for photos and I only had my compact. And that's my excuse :p