PLOS ONE RESEARCH ARTICLE Local information sources received the most attention from Puerto Ricans during the aftermath of Hurricane Maria 1 2 1 Benjamin Freixas EmeryID *, Meredith T. Niles , Christopher M. Danforth , Peter Sheridan Dodds1 1 Computational Story Lab, Vermont Complex Systems Center, The Vermont Advanced Computing Core, Department of Mathematics & Statistics, The University of Vermont, Burlington, VT, United States of America, 2 Department of Nutrition and Food Sciences, The University of Vermont, Burlington, VT, United States of a1111111111 America a1111111111 a1111111111 *
[email protected] a1111111111 a1111111111 Abstract In September 2017, Hurricane Maria made landfall across the Caribbean region as a cate- gory 4 storm. In the aftermath, many residents of Puerto Rico were without power or clean OPEN ACCESS running water for nearly a year. Using both English and Spanish tweets from September 16 Citation: Emery BF, Niles MT, Danforth CM, Dodds to October 15 2017, we investigate discussion of Maria both on and off the island, construct- PS (2021) Local information sources received the ing a proxy for the temporal network of communication between victims of the hurricane and most attention from Puerto Ricans during the aftermath of Hurricane Maria. PLoS ONE 16(6): others. We use information theoretic tools to compare the lexical divergence of different e0251704. https://doi.org/10.1371/journal. subgroups within the network. Lastly, we quantify temporal changes in user prominence pone.0251704 throughout the event. We find at the global level that Spanish tweets more often contained Editor: Naoki Masuda, University at Buffalo, messages of hope and a focus on those helping.