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Decoding our digital traces: Suzy Moat at TEDxZurich скачать в хорошем качестве

Decoding our digital traces: Suzy Moat at TEDxZurich 12 лет назад

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Decoding our digital traces: Suzy Moat at TEDxZurich
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Decoding our digital traces: Suzy Moat at TEDxZurich

Every day, we interact with countless technological systems, which support our communication, our transport, our shopping activities, and much more. These interactions are generating increasing volumes of "big data", documenting our collective behaviour at an unprecedented scale. Suzy Moat explains how bringing social science, natural science and engineering together can help us decode these digital traces of human behaviour, to understand our decisions today -- and anticipate our decisions tomorrow. Dr. Suzy Moat is a computational social scientist. Her research investigates what our behaviour on the Internet might tell us about the decisions we make in the real world, by analysing gigantic data sets created by our everyday use of technology. In collaboration with Tobias Preis and colleagues, her recent work has provided evidence that Internet users from richer countries search for more information about the future, and that patterns in Google and Wikipedia usage could have been used to anticipate stock market moves. Originally trained as a computer scientist, a cognitive scientist and a linguist, Moat was awarded a Ph.D. from the University of Edinburgh and won a series of prizes during her studies. Her research has been featured by television, radio and press worldwide, including recent pieces on CNN and the BBC. In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)

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