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Name: Martin Hilbert @UCDavis.edu
Type: User
Company: University of California, Davis
Bio: foremost social scientist (...please take this as an excuse for what you may find here...)
Blog: www.martinhilbert.net
Name: Martin Hilbert @UCDavis.edu
Type: User
Company: University of California, Davis
Bio: foremost social scientist (...please take this as an excuse for what you may find here...)
Blog: www.martinhilbert.net
These two scripts calculate entropies (incl. conditional and joint) and mutual information (in Shannon's sense) from DATA and from given PROBABILITIES, including statistical significance tests
This R script calculates and measures and creates the graphs presented in the paper Crutchfield & Feldman, (2003). It was developed by Mahima Agarwal and Martin Hilbert, being adopted from the python scripts of the dit library from Ryan James
Shannon information partition from empirical data and from distribution
calculates percentage of stationary partitions for temporal sequence of categorical (qualitative) events
A Python implementation of epsilon-machines & -transducers derivation, by Dave Darmon (with additions by Timothy Zhang) via CSSR (Causal State Splitting Reconstruction)
Versions of this code has been used in 3 complementary studies about the social effects of YouTube's recommender engine (among other platforms): (1) Hilbert, Ahmed, Cho, Liu, Luu. "Communicating with Algorithms: A Transfer Entropy Analysis of Emotions-based Escapes from Online Echo Chambers". Communication Methods and Measures. 2018;12(4):260-275. (2) Hilbert, Liu, Luu, Fishbein. "Behavioral Experiments With Social Algorithms: An Information Theoretic Approach to Input–Output Conversions". Communication Methods and Measures. 2019;0(0):1-20. (3) Cho, Ahmed, Hilbert, Liu, Luu. "Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization", Journal of Broadcasting & Electronic Media
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