Information Cascades
In: THE NEW PALGRAVE DICTIONARY OF ECONOMICS, Second Edition, Steven N. Durlauf and Lawrence E. Blume, eds., Palgrave Macmillan/U.K., 2008
In: THE NEW PALGRAVE DICTIONARY OF ECONOMICS, Second Edition, Steven N. Durlauf and Lawrence E. Blume, eds., Palgrave Macmillan/U.K., 2008
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In: Journal of Finance, Forthcoming
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In: University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2019-30
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In: NBER Working Paper No. w30820
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In: NBER Working Paper No. w12767
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In this talk I introduce Transcendental Information Cascades, a method to understand the temporal dynamics of naturally occurring complex systems through the lens of a specific kind of spatio-temporal network that represents information token recurrence. The method suits very well for exploratory data analysis when it is unknown what is going on at the very low levels of a system's dynamics, and allows switching between looking at individual events or accumulated event sequences. I will present one application of this method in a digital humanities project where we analysed the entire corpus of Charles Dickens's novels and discuss the potential it has for other application areas such as the analysis of brain wave recordings, patent mining or the study of online communities for example. These are the slides of a talk at the RWTH Aachen University, Chair for Computational Social Sciences and Humanities (Germany, date of the talk 06-03-2018) {"references": ["Popper, K., 2013. Knowledge and the Body-Mind Problem: In defence of interaction. Routledge.", "Berners-Lee, Tim; Mark Fischetti (1999). Weaving the Web: The Original Design and Ultimate Destiny of the World Wide Web by its inventor. Britain: Orion Business. ISBN 0-7528-2090-7.", "Luczak-Roesch, M., Tinati, R., Simperl, E., Van Kleek, M., Shadbolt, N., & Simpson, R. (2014). Why won't aliens talk to us? Content and community dynamics in online citizen science. Proceedings of the Eighth AAAI Conference on Weblogs and Social Media, {ICWSM} 2014, Ann Arbor, Michigan, USA, June 1-4, 2014.", "Bikhchandani, Sushil, David Hirshleifer, and Ivo Welch. \"A theory of fads, fashion, custom, and cultural change as informational cascades.\" Journal of political Economy (1992): 992-1026.", "Cheng, Justin, et al. \"Can cascades be predicted?.\" Proceedings of the 23rd international conference on World wide web. International World Wide Web Conferences Steering Committee, 2014.", "Markus Luczak-Roesch, Ramine Tinati, and Nigel Shadbolt. 2015. When Resources Collide: Towards ...
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In: Management Science
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The precise mechanisms by which the information ecosystem polarizes society remain elusive. Focusing on political sorting in networks, we develop a computational model that examines how social network structure changes when individuals participate in information cascades, evaluate their behavior, and potentially rewire their connections to others as a result. Individuals follow proattitudinal information sources but are more likely to first hear and react to news shared by their social ties and only later evaluate these reactions by direct reference to the coverage of their preferred source. Reactions to news spread through the network via a complex contagion. Following a cascade, individuals who determine that their participation was driven by a subjectively "unimportant" story adjust their social ties to avoid being misled in the future. In our model, this dynamic leads social networks to politically sort when news outlets differentially report on the same topic, even when individuals do not know others' political identities. Observational follow network data collected on Twitter support this prediction: We find that individuals in more polarized information ecosystems lose cross-ideology social ties at a rate that is higher than predicted by chance. Importantly, our model reveals that these emergent polarized networks are less efficient at diffusing information: Individuals avoid what they believe to be "unimportant" news at the expense of missing out on subjectively "important" news far more frequently. This suggests that "echo chambers"—to the extent that they exist—may not echo so much as silence.
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In: PBFJ-D-22-00814
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