26 lines
1.8 KiB
BibTeX
26 lines
1.8 KiB
BibTeX
@article{Butler,
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abstract = {EMBERS is an anticipatory intelligence system forecasting population-level events in multiple countries of Latin America. A deployed system from 2012, EMBERS has been generating alerts 24x7 by ingesting a broad range of data sources including news, blogs, tweets, machine coded events, currency rates, and food prices. In this paper, we describe our experiences operating EMBERS continuously for nearly 4 years, with specific attention to the discoveries it has enabled, correct as well as missed forecasts, and lessons learnt from participating in a forecasting tournament including our perspectives on the limits of forecasting and ethical considerations.},
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archivePrefix = {arXiv},
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arxivId = {arXiv:1604.00033v1},
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author = {Muthiah, Sathappan and Vullikanti, Anil and Marathe, Achla and Summers, Kristen and Katz, Graham and Doyle, Andy and Arredondo, Jaime and Gupta, Dipak K. and Mares, David and Ramakrishnan, Naren and Butler, Patrick and Khandpur, Rupinder Paul and Saraf, Parang and Self, Nathan and Rozovskaya, Alla and Zhao, Liang and Cadena, Jose and Lu, Chang-tien},
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doi = {10.1145/2939672.2939709},
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eprint = {arXiv:1604.00033v1},
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file = {:home/cocco/Documents/Mendeley Desktop/embers.pdf:pdf},
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isbn = {9781450342322},
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journal = {Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '16},
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keywords = {civil unrest,event forecasting,open source indicators},
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pages = {205--214},
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title = {{EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System}},
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url = {http://dl.acm.org/citation.cfm?doid=2939672.2939709},
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year = {2016}
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}
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@article{Inter,
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title = {La politica ai tempi di facebook},
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author = {Hannes Grassegger e Mikael Krogerus},
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journal = {Internazionale},
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volume = {1186},
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year = {2017},
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month = {Gennaio}
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}
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