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This work by Alessandro Panconesi delves into how big data transforms our understanding of social networks. It discusses the interconnectedness of individuals through short acquaintance chains, exemplified by a 30% success rate in message delivery. With a focus on the predictive power of computational statistics and the emergence of hybrid science, the text also examines ethical implications such as privacy concerns. Drawing upon classic literature, it raises critical questions about the surveillance of society by powerful entities and the necessity of new algorithms in data processing.
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BIG DATA in a small world Alessandro Panconesi Informatica
Outcome 30% of the letters reached the target Average (median) chain length was roughly six
Conjectures Take any two people in the world, and they will be connected by a very short chain of acquaintances
A matter of scale 300 60,000
A matter of scale 230,000,000 300 60,000
A matter of scale 230,000,000 300 750,000,000 60,000
A matter of scale 230,000,000 300 750,000,000 60,000 Non trivial computational issues
Google Flu Trends Nature 457, 1012-1014 (2009)
More Evidence Movies Hits Stocks? …
No one would have believed in the first years of the XXI century that this world was being watched keenly and closely by awesome computing and financial powers; that as people busied themselves about their various concerns they were scrutinised and studied, perhaps almost as narrowly as a person with a microscope might scrutinise the transient creatures that swarm and multiply in a drop of water. … Adapted from “The War of the Worlds” by H.G.Wells
All'inizio del XXI secolo nessuno avrebbe mai creduto che il nostro pianeta fosse sotto osservazione da parte di entità cibernetico-finanziarie di inimmaginabile potenza e che mentre l'umanità si affaccendava nella sua quotidianità i suoi movimenti venivano osservati da vicino da occhi cupidi, allo steso modo in cui i batteri che pullulano e si moltiplicano sono studiati attentamente al microscopio… Adapted from “The War of the Worlds” by H.G.Wells
FINAL REMARKS • Paradigm shift in the social sciences? • Computational Statistics (more predictive power) • Hybrid science: data processing CANNOT be naïve • New algorithms are the key • Ethical caveats apply (privacy etc)