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Context matters: Improving the uses of big data for forecasting civil unrest: Emerging phenomena and big data.

, , , , , and . ISI, page 169-172. IEEE, (2013)

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Most Relevant Explanation in Bayesian Networks., , and . CoRR, (2014)From Gamergate to FIFA: Identifying Polarized Groups in Online Social Media., , and . IEEE BigData, page 3991-3995. IEEE, (2018)Semi-supervised Learning of Visual Causal Macrovariables., , , , , , and . FLAIRS, AAAI Press, (2023)Information Dynamic Spectrum Predicts Critical Transitions., and . Complex, volume 126 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 267-280. Springer, (2012)Using publicly visible social media to build detailed forecasts of civil unrest., , , , , , and . Secur. Informatics, 3 (1): 4 (2014)Information dynamic spectrum characterizes system instability toward critical transitions., and . EPJ Data Sci., 3 (1): 28 (2014)Interactive construction of graphical decision models based on causal mechanisms., and . Eur. J. Oper. Res., 199 (3): 873-882 (2009)Annealed MAP, , and . CoRR, (2012)Automated classification of extremist Twitter accounts using content-based and network-based features., , and . IEEE BigData, page 2545-2549. IEEE Computer Society, (2016)Causal Abstraction Via Emergence for Predicting Bilateral Trade., , and . CAWS, volume 160 of Proceedings of Machine Learning Research, page 39-51. PMLR, (2021)