Climate Imaginaries: Natural Language Processing

Published: 9 November 2022| Version 1 | DOI: 10.17632/r9tm4sm7gj.1
Brandon Reynante


NLP analysis of youth-authored climate fiction stories written as part of an "engineering fiction" learning experience. NLP Analysis Files (1) NLP Analysis.R: R script for quantifying linguistic abstractness of text. (2) NLP_input.csv: raw text of introductory and final short stories for 12 different student groups. (3) specificity.csv: specificity scores for nouns in WordNet version 3.0 from a prior study (Bolognesi et al., 2020). (4) LCM.dic: dictionary of verbs that were manually coded into Linguistic Category Model categories (Seih et al., 2017). NLP Statistics Files (5) NLP Stats.R: R script for calculating statistics (t-test, effect size, power) of story linguistic abstractness scores. (6) NLP_stats_data.csv: raw data of story linguistic abstractness scores.



Psychology, Education, Climate Change, Narrative